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Every oncology program begins with thousands of possible molecules, but only a tiny fraction will ever become clinically successful therapies. The earlier teams can identify which compounds are likely to succeed and which are likely to fail, the more efficiently R&D resources can be deployed.","text",{"type":103,"format":104,"indent":100,"version":4,"children":111,"direction":74,"textStyle":9,"textFormat":100},[112],{"mode":107,"text":113,"type":109,"style":9,"detail":100,"format":100,"version":4},"InSilicoTrials is working with Microsoft to help address this challenge by bringing mechanistic simulation capabilities to Microsoft Discovery. Through modules such as MOL2CLIN, InSilicoTrials is enabling oncology teams to evaluate therapeutic hypotheses before entering costly experimental and clinical stages.",{"type":103,"format":104,"indent":100,"version":4,"children":115,"direction":74,"textStyle":9,"textFormat":100},[116],{"mode":107,"text":117,"type":109,"style":9,"detail":100,"format":100,"version":4},"Built as an enterprise agentic R&D platform, Microsoft Discovery enables scientists and specialized AI agents to reason, plan, simulate, analyze, and iterate together in continuous scientific workflows. The platform combines agentic orchestration, graph-based scientific knowledge, advanced AI reasoning, and scalable Azure high-performance computing into a unified environment for research and development.",{"type":103,"format":104,"indent":100,"version":4,"children":119,"direction":74,"textStyle":9,"textFormat":100},[120],{"mode":107,"text":121,"type":109,"style":9,"detail":100,"format":100,"version":4},"Traditionally, computational methods in oncology have often been used as isolated point solutions, for example predicting binding affinity or optimizing molecular properties.",{"type":103,"format":104,"indent":100,"version":4,"children":123,"direction":74,"textStyle":9,"textFormat":100},[124],{"mode":107,"text":125,"type":109,"style":9,"detail":100,"format":100,"version":4},"The key value is earlier de-risking.",{"type":103,"format":104,"indent":100,"version":4,"children":127,"direction":74,"textStyle":9,"textFormat":100},[128],{"mode":107,"text":129,"type":109,"style":9,"detail":100,"format":100,"version":4},"Starting from a molecular structure, MOL2CLIN can simulate how a compound is likely to behave in patients by integrating:",{"tag":131,"type":132,"start":4,"format":9,"indent":100,"version":4,"children":133,"listType":159,"direction":74},"ul","list",[134,139,144,149,154],{"type":135,"value":4,"format":104,"indent":100,"version":4,"children":136,"direction":74},"listitem",[137],{"mode":107,"text":138,"type":109,"style":9,"detail":100,"format":100,"version":4},"pharmacokinetics and exposure prediction,",{"type":135,"value":140,"format":104,"indent":100,"version":4,"children":141,"direction":74},2,[142],{"mode":107,"text":143,"type":109,"style":9,"detail":100,"format":100,"version":4},"target engagement modeling,",{"type":135,"value":145,"format":104,"indent":100,"version":4,"children":146,"direction":74},3,[147],{"mode":107,"text":148,"type":109,"style":9,"detail":100,"format":100,"version":4},"tumor growth and response simulation,",{"type":135,"value":150,"format":104,"indent":100,"version":4,"children":151,"direction":74},4,[152],{"mode":107,"text":153,"type":109,"style":9,"detail":100,"format":100,"version":4},"safety and off-target assessment,",{"type":135,"value":155,"format":104,"indent":100,"version":4,"children":156,"direction":74},5,[157],{"mode":107,"text":158,"type":109,"style":9,"detail":100,"format":100,"version":4},"and virtual clinical trial simulation on digital twin of patients","bullet",{"type":103,"format":104,"indent":100,"version":4,"children":161,"direction":74,"textStyle":9,"textFormat":100},[162],{"mode":107,"text":163,"type":109,"style":9,"detail":100,"format":100,"version":4},"Instead of waiting until animal studies or early clinical trials to understand whether a candidate may have sufficient efficacy or tolerability, teams can evaluate these questions during discovery itself.",{"type":103,"format":104,"indent":100,"version":4,"children":165,"direction":74,"textStyle":9,"textFormat":100},[166],{"mode":107,"text":167,"type":109,"style":9,"detail":100,"format":100,"version":4},"That enables scientists to ask:",{"tag":131,"type":132,"start":4,"format":9,"indent":100,"version":4,"children":169,"listType":159,"direction":74},[170,174,178,182,186],{"type":135,"value":4,"format":104,"indent":100,"version":4,"children":171,"direction":74},[172],{"mode":107,"text":173,"type":109,"style":9,"detail":100,"format":100,"version":4},"Is this compound likely to achieve clinically meaningful exposure?",{"type":135,"value":140,"format":104,"indent":100,"version":4,"children":175,"direction":74},[176],{"mode":107,"text":177,"type":109,"style":9,"detail":100,"format":100,"version":4},"Does predicted target occupancy support sustained efficacy?",{"type":135,"value":145,"format":104,"indent":100,"version":4,"children":179,"direction":74},[180],{"mode":107,"text":181,"type":109,"style":9,"detail":100,"format":100,"version":4},"How does the projected efficacy compare with current standards of care?",{"type":135,"value":150,"format":104,"indent":100,"version":4,"children":183,"direction":74},[184],{"mode":107,"text":185,"type":109,"style":9,"detail":100,"format":100,"version":4},"Are there predicted toxicity liabilities that make the program non-viable?",{"type":135,"value":155,"format":104,"indent":100,"version":4,"children":187,"direction":74},[188],{"mode":107,"text":189,"type":109,"style":9,"detail":100,"format":100,"version":4},"Which compounds in a portfolio deserve further experimental investment?",{"type":103,"format":104,"indent":100,"version":4,"children":191,"direction":74,"textStyle":9,"textFormat":100},[192],{"mode":107,"text":193,"type":109,"style":9,"detail":100,"format":100,"version":4},"By integrating MOL2CLIN into Microsoft Discovery workflows, these evaluations become part of a scalable scientific reasoning loop rather than isolated simulation exercises. Researchers can continuously refine hypotheses, compare compounds, optimize dose strategies, and prioritize experiments while maintaining human oversight at every critical decision point.",{"type":103,"format":104,"indent":100,"version":4,"children":195,"direction":74,"textStyle":9,"textFormat":140},[196],{"mode":107,"text":197,"type":109,"style":9,"detail":100,"format":140,"version":4},"“Microsoft Discovery is transforming how therapeutic candidates are identified and optimized,” said Mario Torchia, CEO, InSilicoTrials. “By integrating InSilicoTrials’ validated drug development workflows into this ecosystem, we will help extend those insights further along the R&D continuum, ultimately allowing researchers to assess clinical potential earlier and make better-informed development decisions. Together, we can help bridge the gap between scientific discovery and patient impact.”",{"id":199,"type":200,"value":201,"fields":74,"format":9,"version":145,"relationTo":214},"6a35b6783704f9349fb866ca","upload",{"id":202,"alt":203,"updatedAt":204,"createdAt":205,"url":206,"thumbnailURL":74,"filename":207,"mimeType":88,"filesize":208,"width":209,"height":210,"focalX":92,"focalY":92,"sizes":211},1825,"Continuous Agentic RnD Loop","2026-06-19T21:36:56.132Z","2026-06-19T21:36:56.095Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002FPicture1-768x389.png","Picture1-768x389.png",262689,768,389,{"thumbnail":212,"card":213},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},"media",{"type":103,"format":9,"indent":100,"version":4,"children":216,"direction":74,"textStyle":9,"textFormat":100},[],{"type":103,"format":104,"indent":100,"version":4,"children":218,"direction":74,"textStyle":9,"textFormat":100},[219],{"mode":107,"text":220,"type":109,"style":9,"detail":100,"format":100,"version":4},"For oncology R&D organizations, this has important practical implications.",{"type":103,"format":104,"indent":100,"version":4,"children":222,"direction":74,"textStyle":9,"textFormat":100},[223],{"mode":107,"text":224,"type":109,"style":9,"detail":100,"format":100,"version":4},"Late-stage oncology failures remain extraordinarily expensive, and traditional preclinical models frequently fail to predict human outcomes reliably. Mechanistic in silico approaches calibrated against clinical pharmacology and tumor biology provide an opportunity to shift decision-making earlier in the pipeline, before major investments in toxicology, manufacturing, or clinical trials are made.",{"type":103,"format":104,"indent":100,"version":4,"children":226,"direction":74,"textStyle":9,"textFormat":140},[227,229,231,233],{"mode":107,"text":228,"type":109,"style":9,"detail":100,"format":140,"version":4},"“Microsoft Discovery is designed to bring together specialized AI agents, scientific knowledge, and simulation into a unified R&D environment",{"mode":107,"text":230,"type":109,"style":9,"detail":100,"format":100,"version":4},",” said Aseem Datar, Corporate Vice President, Product Innovation for Microsoft Discovery. “",{"mode":107,"text":232,"type":109,"style":9,"detail":100,"format":140,"version":4},"We are excited about expanding the platform with capabilities like MOL2CLIN as partners like InSilicoTrials help enable an end-to-end, agentic discovery workflow",{"mode":107,"text":234,"type":109,"style":9,"detail":100,"format":100,"version":4},".”",{"type":103,"format":104,"indent":100,"version":4,"children":236,"direction":74,"textStyle":9,"textFormat":100},[237],{"mode":107,"text":238,"type":109,"style":9,"detail":100,"format":100,"version":4},"The workflow presented below illustrates how MOL2CLIN operates within Microsoft Discovery to support that transition. Starting from a candidate molecule (SMILES input), the platform predicts exposure, target engagement, tumor response, safety signals, and simulated clinical outcomes in virtual patient populations.",{"id":240,"type":200,"value":241,"fields":74,"format":9,"version":145,"relationTo":214},"6a35b6da3704f9349fb866cb",{"id":242,"alt":243,"updatedAt":244,"createdAt":245,"url":246,"thumbnailURL":74,"filename":247,"mimeType":88,"filesize":248,"width":209,"height":249,"focalX":92,"focalY":92,"sizes":250},1826,"MOL2CLIN 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The question is no longer simply whether a molecule can be synthesized and tested. 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This is where synthetic data can offer powerful, practical value. At InSilicoTrials, we use synthetic data not as a replacement…",[342],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"Natasa Mandic","2026-05-25T07:42:51.053Z","2025-07-21T10:01:56.000Z",[347],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"Blog Section","blog-section","2026-05-25T07:42:25.337Z","\u002Fsynthetic-data-for-rare-subgroups\u002F","text-lead",{"id":354,"alt":355,"updatedAt":356,"createdAt":356,"url":357,"thumbnailURL":74,"filename":358,"mimeType":359,"filesize":360,"width":361,"height":362,"focalX":92,"focalY":92,"sizes":363},1568,"SyntheticData","2026-05-25T08:06:45.487Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F164433-1.jpg","164433-1.jpg","image\u002Fjpeg",1033946,1798,1200,{"thumbnail":364,"card":365},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":367},{"type":99,"format":9,"indent":100,"version":4,"children":368},[369,373,377,381,389,393,397,401,405,417,421,425,435,439,443,452,460,464,478,482],{"type":103,"format":9,"indent":100,"version":4,"children":370},[371],{"text":372,"type":109,"format":100,"version":4},"In drug development, access to diverse and representative patient data is often a limiting factor, especially when studying rare subgroups. This is where synthetic data can offer powerful, practical value. At InSilicoTrials, we use synthetic data not as a replacement for real-world data (RWD), but as a decision-grade tool to augment, simulate, and explore what real data alone can’t reveal.",{"type":103,"format":9,"indent":100,"version":4,"children":374},[375],{"text":376,"type":109,"format":4,"version":4},"Where Does Synthetic Data Fit?",{"type":103,"format":9,"indent":100,"version":4,"children":378},[379],{"text":380,"type":109,"format":100,"version":4},"At InSilicoTrials, we see synthetic data as something that fits in the continuum of prior knowledge-based approaches, like: Published Literature, Meta-Analyses, Bayesian priors and RWD.",{"type":103,"format":9,"indent":100,"version":4,"children":382},[383,385,387],{"text":384,"type":109,"format":100,"version":4},"Like the aforementioned, synthetic data can inform study design, assess robustness, and optimize populations. However, this value is not without its caveats. Synthetic data faces challenges such as dependance on model assumptions, potential for introducing artifacts, and unclear generalizability. It is critical, for correct use, that the limitations of synthetic data are acknowledged and tackled rigorously. That said, synthetic data ",{"text":386,"type":109,"format":4,"version":4},"can ",{"text":388,"type":109,"format":100,"version":4},"bring advantages. In the following, we would like to illustrate a toy scenario showcasing how using synthetic data can help. Specifically, we’ll learn a prior from a large population, and use that to obtain more precise estimates for a small subgroup.",{"type":103,"format":9,"indent":100,"version":4,"children":390},[391],{"text":392,"type":109,"format":4,"version":4},"A Toy Example: Exploring Underrepresented Subgroups",{"type":103,"format":9,"indent":100,"version":4,"children":394},[395],{"text":396,"type":109,"format":100,"version":4},"Suppose we want to analyze a rare subgroup, such as patients in the top 1% of a biomarker distribution. Traditional analysis using RWD alone is problematic: subgroup sizes are small, and statistical estimates become unstable.",{"type":103,"format":9,"indent":100,"version":4,"children":398},[399],{"text":400,"type":109,"format":100,"version":4},"We ask ourselves:",{"type":103,"format":9,"indent":100,"version":4,"children":402},[403],{"text":404,"type":109,"format":140,"version":4},"“Can we infer outcomes in a rare subgroup using synthetic data generated from the full population?”",{"type":103,"format":9,"indent":100,"version":4,"children":406},[407,409],{"text":408,"type":109,"format":100,"version":4},"We prepared a toy setting to explore this question, with R code that can be found here:? ",{"url":410,"type":411,"fields":412,"version":4,"children":415},"https:\u002F\u002Frpubs.com\u002Fpmessina511\u002F1315710","link",{"url":410,"newTab":413,"linkType":414},true,"custom",[416],{"text":410,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":418},[419],{"text":420,"type":109,"format":100,"version":4},"In short, we considered a scenario with a large population (1,000 individuals) and a small subgroup (10 individuals). We used a density estimator trained on the whole dataset, from which synthetic members of the rare subgroup are sampled.",{"type":103,"format":9,"indent":100,"version":4,"children":422},[423],{"text":424,"type":109,"format":100,"version":4},"Our findings? ",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":426,"listType":159},[427,431],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":428},[429],{"text":430,"type":109,"format":100,"version":4},"Synthetic data outperformed RWD in estimating subgroup outcomes",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":432},[433],{"text":434,"type":109,"format":100,"version":4},"Results were consistent across 100 simulations",{"type":103,"format":9,"indent":100,"version":4,"children":436},[437],{"text":438,"type":109,"format":100,"version":4}," We remark that this holds when the subgroup is “in-distribution,” i.e., shares latent traits with the training population",{"type":103,"format":9,"indent":100,"version":4,"children":440},[441],{"text":442,"type":109,"format":4,"version":4},"Takeaways",{"type":103,"format":9,"indent":100,"version":4,"children":444},[445,447,450],{"text":446,"type":109,"format":100,"version":4},"Synthetic data offers a compelling addition to the modern data ecosystem in drug development, particularly as a decision-grade tool for early-phase strategy, simulation, and subgroup analysis. Its greatest strength lies in its ability to augment real-world data and enable robust “what-if” exploration when traditional datasets fall short, ",{"text":448,"type":109,"format":449,"version":4},"provided it is used with methodological care",8,{"text":451,"type":109,"format":100,"version":4},".",{"type":103,"format":9,"indent":100,"version":4,"children":453},[454,456,458],{"text":455,"type":109,"format":100,"version":4},"Our example covers a specific scenario, but it highlights a critical insight: ",{"text":457,"type":109,"format":140,"version":4},"When a rare subgroup shares latent characteristics with the broader true population, synthetic data can fill gaps left by biased or sparse real-world samples. ",{"text":459,"type":109,"format":100,"version":4},"This especially holds in an ideal scenario where the model has been trained on large and diverse datasets capturing the full spectrum of variability relevant to the subgroup, enabling the model to generate realistic and informative synthetic representations. Just like fine-tuning a pre-trained foundation model in machine learning!",{"type":103,"format":9,"indent":100,"version":4,"children":461},[462],{"text":463,"type":109,"format":100,"version":4},"However, again, we remark that synthetic data has important limitations. ",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":465,"listType":159},[466,470,474],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":467},[468],{"text":469,"type":109,"format":100,"version":4},"Synthetic data is only as good as the models and input data on which it is based.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":471},[472],{"text":473,"type":109,"format":100,"version":4},"Although synthetic datasets can reduce sampling variability, they do not eliminate true uncertainty about causal effects, and care must be taken not to misinterpret precision for confidence.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":475},[476],{"text":477,"type":109,"format":100,"version":4},"While synthetic data is often heralded as inherently privacy-safe, it is not private by default and requires formal risk assessments.",{"type":103,"format":9,"indent":100,"version":4,"children":479},[480],{"text":481,"type":109,"format":100,"version":4}," When these caveats are respected and transparent validation is applied, synthetic data can serve as a powerful tool to inform design decisions, simulate populations, and optimize trials—bringing rigor, flexibility, and inclusiveness to the next generation of clinical research.",{"type":103,"format":9,"indent":100,"version":4,"children":483},[484],{"text":485,"type":109,"format":100,"version":4},"Let’s explore together how synthetic data can elevate your early-phase strategy and unlock deeper understanding of subgroups that matter.","2026-05-25T08:07:08.592Z","2026-05-25T07:42:52.719Z",{"id":489,"title":490,"slug":491,"excerpt":492,"authors":493,"reviewedBy":74,"publishedAt":495,"tags":496,"gated":78,"businessEmailRequired":78,"legacyUrl":498,"template":352,"heroImage":499,"intro":74,"lede":74,"citationId":74,"body":511,"updatedAt":658,"createdAt":659,"_status":335},62,"Synthetic Data – Are We All Talking About the Same Thing?","synthetic-data-are-we-all-talking-about-the-same-thing","Synthetic Data' – Are We All Talking About the Same Thing? In the rapidly evolving world of healthcare and drug development, data is the driving force behind innovation. Yet, the lack of cross-institute shared access frameworks and the need to protect patient privacy…",[494],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2025-07-14T08:00:00.000Z",[497],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fsynthetic-data-are-we-all-talking-about-the-same-thing\u002F",{"id":500,"alt":501,"updatedAt":502,"createdAt":502,"url":503,"thumbnailURL":74,"filename":504,"mimeType":88,"filesize":505,"width":506,"height":507,"focalX":92,"focalY":92,"sizes":508},1632,"BLOG_POST_IMAGE_37","2026-05-25T08:06:55.508Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F227057.png","227057.png",1294184,1667,935,{"thumbnail":509,"card":510},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":512},{"type":99,"format":9,"indent":100,"version":4,"children":513},[514,518,526,542,548,552,568,574,578,614,618,630,634,642,647],{"type":103,"format":9,"indent":100,"version":4,"children":515},[516],{"text":517,"type":109,"format":4,"version":4},"Synthetic Data' – Are We All Talking About the Same Thing?",{"type":103,"format":9,"indent":100,"version":4,"children":519},[520,522,524],{"text":521,"type":109,"format":100,"version":4},"In the rapidly evolving world of healthcare and drug development, data is the driving force behind innovation. Yet, the lack of cross-institute shared access frameworks and the need to protect patient privacy pose significant challenges that hinder innovation and demand innovative solutions. One such solution gaining significant momentum is ",{"text":523,"type":109,"format":4,"version":4},"synthetic data",{"text":525,"type":109,"format":100,"version":4},"—artificially generated datasets that closely mirror observed (real) data from a statistical perspective without revealing information about any individual in particular, thus minimizing privacy risks.",{"type":103,"format":9,"indent":100,"version":4,"children":527},[528,530,540],{"text":529,"type":109,"format":100,"version":4},"Our latest collaborative paper, ",{"url":531,"type":411,"fields":532,"version":4,"children":533},"https:\u002F\u002Fascpt.onlinelibrary.wiley.com\u002Fdoi\u002F10.1002\u002Fpsp4.70021",{"url":531,"newTab":413,"linkType":414},[534,536,538],{"text":535,"type":109,"format":100,"version":4},"\"",{"text":537,"type":109,"format":4,"version":4},"Synthetic Data in Healthcare and Drug Development: Definitions, Regulatory Frameworks, Issues",{"text":539,"type":109,"format":100,"version":4},",\"",{"text":541,"type":109,"format":100,"version":4}," explores the potential of synthetic data in transforming healthcare research. In this paper, we collaborated with experts from the UK Medicines and Healthcare Products Regulatory Agency, Unlearn.AI, KU Leuven's Centre for IT & IP Law, University of Oxford's HeLEX, University of Catania, and Humanitas Research Center to bring clarity on what synthetic data is, and how to frame it in the context of external control arms (also referred to as “synthetic control arms” when referring to true\u002Fobserved data (Burcu et al., 2020), hence not fully encompassing the broader scope introduced by recent AI-driven methodologies for generating synthetic data), and highlighting some key challenges, such as regulatory acceptance. ",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":545},"h3","heading",[546],{"text":547,"type":109,"format":4,"version":4},"Why Synthetic Data Matters",{"type":103,"format":9,"indent":100,"version":4,"children":549},[550],{"text":551,"type":109,"format":100,"version":4}," Synthetic data, which can nowadays be created through powerful generative AI algorithms (but not only those), has the potential to significantly enhance the speed, accuracy, and efficiency of drug development. These datasets allow researchers to simulate clinical scenarios without the use of sensitive patient data, thereby reducing privacy concerns. Reducing privacy concerns also means increased accessibility, as real-world data (RWD) and data from randomized controlled trials (RCTs), is notoriously difficult to obtain. Another key aspect of synthetic data is that its generating process can often be “conditioned”: a researcher can set the algorithm to generate arbitrary numbers of patients belonging to specific sub-populations (e.g., minority groups based on sex or ethnicity). This means that what-if scenarios can be explored, assessing how the downstream analysis results change when the a specific sub-population is taken into exam.",{"type":103,"format":9,"indent":100,"version":4,"children":553},[554,556,558,560,562,564,566],{"text":555,"type":109,"format":100,"version":4},"However, the introduction of synthetic data also raises critical questions about ",{"text":557,"type":109,"format":4,"version":4},"provenance",{"text":559,"type":109,"format":100,"version":4},", ",{"text":561,"type":109,"format":4,"version":4},"trust",{"text":563,"type":109,"format":100,"version":4},", and ",{"text":565,"type":109,"format":4,"version":4},"regulatory oversight",{"text":567,"type":109,"format":100,"version":4},". Where does the data originate? How do we ensure it faithfully represents real-world conditions? And how can we validate its utility in clinical research? ",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":569},[570,572],{"text":571,"type":109,"format":4,"version":4},"Key Insights from ",{"text":573,"type":109,"format":4,"version":4},"Our Paper",{"type":103,"format":9,"indent":100,"version":4,"children":575},[576],{"text":577,"type":109,"format":100,"version":4}," We explore several pivotal aspects of synthetic data use in healthcare, offering insights drawn from both our research and the collaborative efforts of our team: ",{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":580,"listType":613},"ol",[581,587,597,607],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":582},[583,585],{"text":584,"type":109,"format":4,"version":4},"Provenance of Synthetic Data",{"text":586,"type":109,"format":100,"version":4}," We highlight the importance of establishing robust provenance mechanisms to track the origin, transformation, and use of synthetic data. More than observed (real) data, , synthetic data requires detailed documentation of the models and processes used in its creation to maintain its credibility.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":588},[589,591,593,595],{"text":590,"type":109,"format":4,"version":4},"Distinguishing Between Synthetic and Observed Data",{"text":592,"type":109,"format":100,"version":4}," We highlight the need of clearly labeling synthetic data to avoid confusion when it is integrated with (true) observed data (e.g., real-world data, historical randomized controlled trials). To address this, we propose the use of ",{"text":594,"type":109,"format":4,"version":4},"data cards",{"text":596,"type":109,"format":100,"version":4},"—structured summaries that document the data’s origins, generation processes, and intended uses, thereby enhancing transparency and reducing misinterpretation.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":598},[599,601,603,605],{"text":600,"type":109,"format":4,"version":4},"Replicability and Validation",{"text":602,"type":109,"format":100,"version":4}," Ensuring that synthetic data can reliably replicate real-world outcomes is essential for its use in research. We call attention to approaches like ",{"text":604,"type":109,"format":4,"version":4},"sequential synthesis",{"text":606,"type":109,"format":100,"version":4}," to improve replicability and validate the consistency of conclusions drawn from synthetic data compared to observed data.",{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":608},[609,611],{"text":610,"type":109,"format":4,"version":4},"Data Privacy and Ethical Considerations",{"text":612,"type":109,"format":100,"version":4}," We explore the privacy risks associated with generative AI models, particularly the possibility of models memorizing real data points.","number",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":615},[616],{"text":617,"type":109,"format":4,"version":4},"The Road Ahead for Synthetic Data in Healthcare",{"type":103,"format":9,"indent":100,"version":4,"children":619},[620,622,624,626,628],{"text":621,"type":109,"format":100,"version":4}," As synthetic data is posed to play a growing role in healthcare research, it is essential for the regulatory landscape to evolve in tandem. While ",{"text":623,"type":109,"format":4,"version":4},"process-driven synthetic data",{"text":625,"type":109,"format":100,"version":4}," (such as pharmacokinetic models) is already accepted by regulatory bodies like the FDA and EMA in drug development, ",{"text":627,"type":109,"format":4,"version":4},"data-driven synthetic data",{"text":629,"type":109,"format":100,"version":4}," (generated via AI models) still lacks clear regulatory definitions and terms for utilization.",{"type":103,"format":9,"indent":100,"version":4,"children":631},[632],{"text":633,"type":109,"format":100,"version":4},"Our paper highlights the need for continued collaboration across various sectors—academic, clinical, regulatory, and industry stakeholders—to drive the development of synthetic data standards. By clearly defining terminology and ensuring transparency in its usage, we believe synthetic data can become a key enabler in clinical research and drug development.",{"type":103,"format":9,"indent":100,"version":4,"children":635},[636,638],{"text":637,"type":109,"format":4,"version":4},"Read the full, open access paper here: ",{"url":531,"type":411,"fields":639,"version":4,"children":640},{"url":531,"newTab":413,"linkType":414},[641],{"text":531,"type":109,"format":4,"version":4},{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":644},"h6",[645],{"text":646,"type":109,"format":100,"version":4},"References",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":648},[649,651,653,654,656],{"text":650,"type":109,"format":100,"version":4},"Burcu, M., Dreyer, N. A., Franklin, J. M., Blum, M. D., Critchlow, C. W., Perfetto, E. M., & Zhou, W. (2020). Real‐world evidence to support regulatory decision‐making for medicines: Considerations for external control arms. ",{"text":652,"type":109,"format":140,"version":4},"Pharmacoepidemiology and Drug Safety",{"text":559,"type":109,"format":100,"version":4},{"text":655,"type":109,"format":140,"version":4},"29",{"text":657,"type":109,"format":100,"version":4},"(10), 1228–1235. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fpds.4975","2026-05-25T08:07:08.543Z","2026-05-25T07:52:17.734Z",{"id":661,"title":662,"slug":663,"excerpt":664,"authors":665,"reviewedBy":74,"publishedAt":667,"tags":668,"gated":78,"businessEmailRequired":78,"legacyUrl":670,"template":671,"heroImage":672,"intro":74,"lede":74,"citationId":74,"body":684,"updatedAt":859,"createdAt":860,"_status":335},61,"FDA's Strategic Roadmap to Phase Out Animal Testing: How Computational Models Are Revolutionizing Drug Development","fdas-strategic-roadmap-to-phase-out-animal-testing-how-computational-models-are-revolutionizing-drug-development","The Paradigm Shift in Preclinical Testing The FDA has announced a strategic shift away from animal testing, citing that over 90% of drugs successful in animals fail FDA approval due to human safety and efficacy issues—especially in cancer, Alzheimer's, and inflammatory…",[666],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2025-05-06T13:48:14.000Z",[669],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Ffdas-strategic-roadmap-to-phase-out-animal-testing-how-computational-models-are-revolutionizing-drug-development\u002F","cover",{"id":673,"alt":674,"updatedAt":675,"createdAt":675,"url":676,"thumbnailURL":74,"filename":677,"mimeType":359,"filesize":678,"width":679,"height":680,"focalX":92,"focalY":92,"sizes":681},1485,"FDA shift from animal testing","2026-05-25T08:06:24.867Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F102964-1.jpg","102964-1.jpg",51597,571,378,{"thumbnail":682,"card":683},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":685},{"type":99,"format":9,"indent":100,"version":4,"children":686},[687,691,703,709,713,717,721,725,729,733,737,741,745,759,763,777,781,795,799,803,807,811,814,824,832,841,850],{"type":103,"format":9,"indent":100,"version":4,"children":688},[689],{"text":690,"type":109,"format":4,"version":4},"The Paradigm Shift in Preclinical Testing",{"type":103,"format":9,"indent":100,"version":4,"children":692},[693,695,701],{"text":694,"type":109,"format":100,"version":4}," The ",{"url":696,"type":411,"fields":697,"version":4,"children":698},"https:\u002F\u002Fwww.fda.gov\u002Fnews-events\u002Fpress-announcements\u002Ffda-announces-plan-phase-out-animal-testing-requirement-monoclonal-antibodies-and-other-drugs",{"url":696,"newTab":413,"linkType":414},[699],{"text":700,"type":109,"format":100,"version":4},"FDA has announced a strategic shift",{"text":702,"type":109,"format":100,"version":4}," away from animal testing, citing that over 90% of drugs successful in animals fail FDA approval due to human safety and efficacy issues—especially in cancer, Alzheimer's, and inflammatory diseases¹˒². Their new roadmap focuses on New Approach Methodologies (NAMs): in vitro human-based systems, in silico computational modeling, and innovative platforms for evaluating immunogenicity, toxicity, and pharmacodynamics in humans².",{"type":103,"format":9,"indent":100,"version":4,"children":704},[705,707],{"text":706,"type":109,"format":4,"version":4},"Preclinical paradox:",{"text":708,"type":109,"format":100,"version":4}," Did you know? Aspirin might never have reached patients if it had to pass modern animal testing, while compounds \"safe\" in animals have proven fatal in humans³ .",{"type":103,"format":9,"indent":100,"version":4,"children":710},[711],{"text":712,"type":109,"format":100,"version":4},"At InSilicoTrials, our computational platforms directly support this transition by providing pharmaceutical companies with human-relevant alternatives that improve predictive accuracy and align with the FDA's stepwise approach to modernizing preclinical testing.",{"type":103,"format":9,"indent":100,"version":4,"children":714},[715],{"text":716,"type":109,"format":4,"version":4},"Why Start with Monoclonal Antibodies?",{"type":103,"format":9,"indent":100,"version":4,"children":718},[719],{"text":720,"type":109,"format":100,"version":4}," The strategic rollout: The agency's carefully sequenced approach begins with mAbs, where animal tests have most dramatically failed human prediction, before expanding to other biologics and eventually all drugs. This science-driven strategy targets the $187 billion mAb market first, where catastrophic failures like TGN1412 have demonstrated that passing animal studies provides false security. By establishing success with mAbs, FDA creates momentum for broader implementation while protecting the most patients in the shortest timeframe⁴˒⁵.",{"type":103,"format":9,"indent":100,"version":4,"children":722},[723],{"text":724,"type":109,"format":100,"version":4},"While mAbs serve as the FDA's starting point, could this be the first domino in a larger shift across the biologics landscape? This broader category includes recombinant proteins, gene therapies, cell-based products, and vaccines, representing a rapidly growing sector of pharmaceutical development. Biologics present unique challenges for traditional animal testing due to their complex structures and species-specific interactions with immune systems.",{"type":103,"format":9,"indent":100,"version":4,"children":726},[727],{"text":728,"type":109,"format":4,"version":4},"How InSilicoTrials Aligns with FDA's New Vision",{"type":103,"format":9,"indent":100,"version":4,"children":730},[731],{"text":732,"type":109,"format":100,"version":4}," InSilicoTrials delivers regulatory-compliant computational solutions that transform drug development in the post-animal testing era.",{"type":103,"format":9,"indent":100,"version":4,"children":734},[735],{"text":736,"type":109,"format":100,"version":4},"The FDA is actively promoting AI and simulation to predict drug behavior in the human body. These approaches can forecast distribution, metabolism, target engagement, and side effects while catching safety issues earlier. By accepting real-world human data from other countries and offering streamlined reviews for companies using robust in silico methods, the FDA is creating powerful incentives for computational innovation.",{"type":103,"format":9,"indent":100,"version":4,"children":738},[739],{"text":740,"type":109,"format":4,"version":4},"Our Advanced Solutions Portfolio",{"type":103,"format":9,"indent":100,"version":4,"children":742},[743],{"text":744,"type":109,"format":4,"version":4},"Comprehensive Drug Modeling:",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":746,"listType":159},[747,751,755],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":748},[749],{"text":750,"type":109,"format":100,"version":4},"PBPK & QSP Models: Simulate biologic therapies and patient responses across virtual populations",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":752},[753],{"text":754,"type":109,"format":100,"version":4},"PK & ADME: Generate predictions based on molecular structures",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":756},[757],{"text":758,"type":109,"format":100,"version":4},"PhysChem + Blood Brain Barrier: Predict BBB penetration and key molecular descriptors",{"type":103,"format":9,"indent":100,"version":4,"children":760},[761],{"text":762,"type":109,"format":4,"version":4},"AI-Driven Safety Assessment:",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":764,"listType":159},[765,769,773],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":766},[767],{"text":768,"type":109,"format":100,"version":4},"Mutagenicity: Non-animal, ICH-compliant QSAR models for predicting genotoxicity",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":770},[771],{"text":772,"type":109,"format":100,"version":4},"Chemotoxicity: Predict immunotherapy effects using digital patient populations",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":774},[775],{"text":776,"type":109,"format":100,"version":4},"Immunogenicity Risk Screen: Mimic CD4+ T-cell assays to assess protein sequence risks",{"type":103,"format":9,"indent":100,"version":4,"children":778},[779],{"text":780,"type":109,"format":4,"version":4},"Target Interaction Analysis:",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":782,"listType":159},[783,787,791],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":784},[785],{"text":786,"type":109,"format":100,"version":4},"Target Affinity Prediction: AI-powered assessment across >1M compound records",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":788},[789],{"text":790,"type":109,"format":100,"version":4},"Molecular Docking: Simulate ligand-target interactions to assess binding affinity",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":792},[793],{"text":794,"type":109,"format":100,"version":4},"Epitope Identification: Deep learning models for protein-protein interactions",{"type":103,"format":9,"indent":100,"version":4,"children":796},[797],{"text":798,"type":109,"format":100,"version":4}," Furthermore, by partnering with InSilicoTrials, pharmaceutical companies can immediately access FDA-aligned computational solutions to accelerate development timelines, reduce costs, and strategically position them for the FDA's new regulatory incentives, all while delivering safer, more effective therapies to patients with unprecedented speed.",{"type":103,"format":9,"indent":100,"version":4,"children":800},[801],{"text":802,"type":109,"format":4,"version":4},"Next Steps and Key Takeaways",{"type":103,"format":9,"indent":100,"version":4,"children":804},[805],{"text":806,"type":109,"format":100,"version":4}," The FDA's strategic roadmap marks a pivotal shift away from animal testing toward scientifically validated NAMs. This transition promises multiple benefits: patients will receive safer therapies faster, unnecessary animal testing will be eliminated, and drug development will align with 21st-century technology. ",{"type":103,"format":9,"indent":100,"version":4,"children":808},[809],{"text":810,"type":109,"format":100,"version":4},"The future of drug development is computational, ethical, and human-relevant, and the time to embrace this transformation is now.",{"type":103,"format":9,"indent":100,"version":4,"children":812},[813],{"text":646,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":815},[816,818],{"text":817,"type":109,"format":100,"version":4},"¹ NIH Advisory Committee to the Director, \"NAMs Working Group Report,\" December 2023. ",{"url":819,"type":411,"fields":820,"version":4,"children":821},"https:\u002F\u002Fwww.acd.od.nih.gov\u002Fdocuments\u002Fpresentations\u002F12142023_NAMs_Working_Group_Report.pdf",{"url":819,"newTab":413,"linkType":414},[822],{"text":823,"type":109,"format":100,"version":4},"[Link]",{"type":103,"format":9,"indent":100,"version":4,"children":825},[826,828],{"text":827,"type":109,"format":100,"version":4},"² FDA, \"FDA Announces Plan to Phase Out Animal Testing Requirement for Monoclonal Antibodies and Other Drugs,\" April 2024. ",{"url":696,"type":411,"fields":829,"version":4,"children":830},{"url":696,"newTab":413,"linkType":414},[831],{"text":823,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":833},[834,836],{"text":835,"type":109,"format":100,"version":4},"³ Bailey J. \"Does the stress of laboratory life and experimentation on animals adversely affect research data?\" Altern Lab Anim. 2018;46(5):291-305. ",{"url":837,"type":411,"fields":838,"version":4,"children":839},"https:\u002F\u002Fpubmed.ncbi.nlm.nih.gov\u002F30488713\u002F",{"url":837,"newTab":413,"linkType":414},[840],{"text":823,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":842},[843,845],{"text":844,"type":109,"format":100,"version":4},"⁴ Labmate Online, \"Market Report: Therapeutic Monoclonal Antibodies in Europe\" ",{"url":846,"type":411,"fields":847,"version":4,"children":848},"https:\u002F\u002Fwww.labmate-online.com\u002Fnews\u002Fnews-and-views\u002F5\u002Ffrost-sullivan\u002Fmarket-report-therapeutic-monoclonal-antibodies-in-europe\u002F22346",{"url":846,"newTab":413,"linkType":414},[849],{"text":823,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":851},[852,854],{"text":853,"type":109,"format":100,"version":4},"⁵ NC3Rs, \"Reducing animal use in monoclonal antibody development\" ",{"url":855,"type":411,"fields":856,"version":4,"children":857},"https:\u002F\u002Fnc3rs.org.uk\u002Four-portfolio\u002Freducing-animal-use-monoclonal-antibody-development",{"url":855,"newTab":413,"linkType":414},[858],{"text":823,"type":109,"format":100,"version":4},"2026-05-25T09:46:48.506Z","2026-05-25T07:52:17.700Z",{"id":862,"title":863,"slug":864,"excerpt":865,"authors":866,"reviewedBy":74,"publishedAt":868,"tags":869,"gated":78,"businessEmailRequired":78,"legacyUrl":871,"template":352,"heroImage":872,"intro":74,"lede":74,"citationId":74,"body":882,"updatedAt":931,"createdAt":932,"_status":335},40,"InSilicoTrials Highlighted in HSBC Venture Healthcare Report for 1H 2024","hsbc_report","The HSBC Healthcare Annual Report for the first half of 2024 provides an extensive analysis of the healthcare sector, focusing on trends in venture capital investments, biopharma, medical devices, and health tech. This report, authored by HSBC Innovation Banking,…",[867],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-07-24T13:28:52.000Z",[870],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fhsbc_report\u002F",{"id":873,"alt":874,"updatedAt":875,"createdAt":875,"url":876,"thumbnailURL":74,"filename":877,"mimeType":359,"filesize":878,"width":679,"height":680,"focalX":92,"focalY":92,"sizes":879},1334,"InSilicoTrials_HSBC","2026-05-25T08:05:38.351Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F36656.jpg","36656.jpg",73743,{"thumbnail":880,"card":881},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":883},{"type":99,"format":9,"indent":100,"version":4,"children":884},[885,889,896,900,904,908,912,916,920],{"type":103,"format":9,"indent":100,"version":4,"children":886},[887],{"text":888,"type":109,"format":100,"version":4},"The HSBC Healthcare Annual Report for the first half of 2024 provides an extensive analysis of the healthcare sector, focusing on trends in venture capital investments, biopharma, medical devices, and health tech. This report, authored by HSBC Innovation Banking, serves as a valuable resource for stakeholders aiming to understand the current and future directions of the healthcare industry.",{"type":103,"format":9,"indent":100,"version":4,"children":890},[891,893,894],{"text":892,"type":109,"format":100,"version":4},"In this extensive landscape, ",{"text":72,"type":109,"format":4,"version":4},{"text":895,"type":109,"format":100,"version":4}," is included between the most prominent companies within the Insight Platform and Infrastructure (IPI) sub-sector, on slide 34. In such slide, we can see the most important companies in the computational biology landscape in 1H 2024 for USA and Europe categorized into four sectors: AI Discovery (AID), Diagnostics (Dx), Clinical Response Prediction (CRP), and Insight Platform & Infrastructure (IPI).",{"type":103,"format":9,"indent":100,"version":4,"children":897},[898],{"text":899,"type":109,"format":100,"version":4},"We are honored by this mention, as it highlights our work in democratizing modeling and simulation, making these advanced tools more accessible to researchers and organizations worldwide.",{"type":103,"format":9,"indent":100,"version":4,"children":901},[902],{"text":903,"type":109,"format":100,"version":4},"The report outlines significant investment activities in Q1 2024, with $1.9 billion invested across 31 deals. This continued the momentum from Q2 2023, reflecting a sustained interest in healthcare innovations. Quarterly investment activities varied, with notable spikes and declines, indicating dynamic market conditions.",{"type":103,"format":9,"indent":100,"version":4,"children":905},[906],{"text":907,"type":109,"format":100,"version":4},"In the biopharma sector, the report covers first-financing deals by indication, the largest financings, the most active investors, and new investor step-up analyses. It also provides insights into private VC-backed M&A activities and IPO trends, offering a comprehensive view of the biopharma investment landscape.",{"type":103,"format":9,"indent":100,"version":4,"children":909},[910],{"text":911,"type":109,"format":100,"version":4},"Investments in diagnostics and tools are broken down by subsector, with a focus on first-financing deals, the most active investors, and post-money valuations. The sector shows a strong interest in innovation, particularly in areas such as AI-driven diagnostics and advanced medical tools.",{"type":103,"format":9,"indent":100,"version":4,"children":913},[914],{"text":915,"type":109,"format":100,"version":4},"The medical devices sector is covered in detail, with information on first-financing deals, investments by indication, and the largest investments in the first half of 2024. The report highlights the most active investors and provides an analysis of new investor step-ups, reflecting the evolving investment strategies in the medical device sector.",{"type":103,"format":9,"indent":100,"version":4,"children":917},[918],{"text":919,"type":109,"format":100,"version":4},"Healthtech investments are analyzed by subsector, with data on the largest financings and the most active investors. The report underscores the growing significance of healthtech in the broader healthcare investment landscape, driven by advancements in digital health and telemedicine.",{"type":103,"format":9,"indent":100,"version":4,"children":921},[922,924,930],{"text":923,"type":109,"format":100,"version":4},"The complete document is available for download ",{"url":925,"type":411,"fields":926,"version":4,"children":927},"https:\u002F\u002Fwww.business.us.hsbc.com\u002Fen\u002Fcampaigns\u002Finnovation-banking\u002Fventure-healthcare-report",{"url":925,"newTab":413,"linkType":414},[928],{"text":929,"type":109,"format":100,"version":4},"here",{"text":451,"type":109,"format":100,"version":4},"2026-05-25T08:07:08.454Z","2026-05-25T07:42:52.683Z",{"id":934,"title":935,"slug":936,"excerpt":937,"authors":938,"reviewedBy":74,"publishedAt":940,"tags":941,"gated":78,"businessEmailRequired":78,"legacyUrl":943,"template":352,"heroImage":944,"intro":74,"lede":74,"citationId":74,"body":956,"updatedAt":1012,"createdAt":1013,"_status":335},60,"FDA DRAFT GUIDANCE: Diversity Action Plans to Improve Enrollment of Participants from Underrepresented Populations in Clinical Studies Guidance for Industry","fda_draft_guidance","In recent years, the US Congress and the US Food and Drug Administration (FDA) have emphasized the importance of including underrepresented populations in clinical trials. This push for diversity is not just a regulatory requirement but a critical step towards ensuring…",[939],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-07-09T10:45:52.000Z",[942],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Ffda_draft_guidance\u002F",{"id":945,"alt":946,"updatedAt":947,"createdAt":947,"url":948,"thumbnailURL":74,"filename":949,"mimeType":359,"filesize":950,"width":951,"height":952,"focalX":92,"focalY":92,"sizes":953},1321,"IST_FDAGuidance","2026-05-25T08:05:36.486Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F36549.jpg","36549.jpg",373720,1140,755,{"thumbnail":954,"card":955},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":957},{"type":99,"format":9,"indent":100,"version":4,"children":958},[959,963,967,971,975,979,983,987,991,995,999,1003],{"type":103,"format":9,"indent":100,"version":4,"children":960},[961],{"text":962,"type":109,"format":100,"version":4},"In recent years, the US Congress and the US Food and Drug Administration (FDA) have emphasized the importance of including underrepresented populations in clinical trials. This push for diversity is not just a regulatory requirement but a critical step towards ensuring that medical treatments and devices are safe, effective, and accessible for everyone. The FDA has published draft guidance recommending that sponsors develop comprehensive diversity strategies for their clinical development programs.",{"type":103,"format":9,"indent":100,"version":4,"children":964},[965],{"text":966,"type":109,"format":4,"version":4},"But why is this so important?",{"type":103,"format":9,"indent":100,"version":4,"children":968},[969],{"text":970,"type":109,"format":100,"version":4},"Wider Representation",{"type":103,"format":9,"indent":100,"version":4,"children":972},[973],{"text":974,"type":109,"format":100,"version":4},"Including individuals of different ages, sexes, races, ethnicities, and backgrounds in clinical trials provides a more accurate picture of how treatments work across diverse populations. Genetic, environmental, and lifestyle factors can significantly influence how different groups respond to the same treatment. For instance, some populations may have genetic variations that affect drug metabolism, while others may have different susceptibilities to certain diseases. Comprehensive representation helps to identify these differences and ensures that the treatments developed are effective for everyone.",{"type":103,"format":9,"indent":100,"version":4,"children":976},[977],{"text":978,"type":109,"format":100,"version":4},"Health Equity",{"type":103,"format":9,"indent":100,"version":4,"children":980},[981],{"text":982,"type":109,"format":100,"version":4},"Diverse clinical trials are a cornerstone of health equity. By ensuring that all communities are represented in medical research, we can help close the gaps in health disparities and ensure that advancements in medicine benefit everyone. Historically, certain groups have been underrepresented in clinical trials, resulting in a limited understanding of how these groups respond to various treatments. Improving diversity in clinical trials helps address these gaps and promotes fair and equitable healthcare for all populations.",{"type":103,"format":9,"indent":100,"version":4,"children":984},[985],{"text":986,"type":109,"format":4,"version":4},"FDA's Draft Guidance",{"type":103,"format":9,"indent":100,"version":4,"children":988},[989],{"text":990,"type":109,"format":100,"version":4},"The FDA's draft guidance on diversity action plans outlines specific requirements for sponsors. These plans must detail enrollment goals disaggregated by race, ethnicity, sex, and age group of clinically relevant study populations. Additionally, sponsors must provide a rationale for these goals and explain how they intend to meet them. The guidance emphasizes the need for community engagement, cultural competency training for clinical staff, and strategies to reduce participant burden, such as providing transportation and flexible study hours.",{"type":103,"format":9,"indent":100,"version":4,"children":992},[993],{"text":994,"type":109,"format":4,"version":4},"InSilicoTrials' Commitment",{"type":103,"format":9,"indent":100,"version":4,"children":996},[997],{"text":998,"type":109,"format":100,"version":4},"At IST, we recognize the importance of this initiative and are committed to supporting sponsors in designing clinical studies that reflect true diversity. Our expertise in in silico methods enables us to provide detailed justifications for the number of patients needed to achieve meaningful results for each subpopulation. These advanced techniques allow the simulations of various scenarios, helping to determine the optimal sample size and ensure robust and reliable outcomes.",{"type":103,"format":9,"indent":100,"version":4,"children":1000},[1001],{"text":1002,"type":109,"format":100,"version":4},"By leveraging these methods, sponsors can design trials that meet regulatory requirements while fostering inclusivity and equity in healthcare. This approach ensures that medical advancements are accessible and effective across diverse populations, ultimately contributing to a more inclusive and equitable healthcare landscape.",{"type":103,"format":9,"indent":100,"version":4,"children":1004},[1005,1007],{"text":1006,"type":109,"format":100,"version":4},"Read the full guidance: ",{"url":1008,"type":411,"fields":1009,"version":4,"children":1010},"https:\u002F\u002Fwww.fda.gov\u002Fmedia\u002F179593\u002Fdownload",{"url":1008,"newTab":413,"linkType":414},[1011],{"text":1008,"type":109,"format":100,"version":4},"2026-05-25T08:07:08.280Z","2026-05-25T07:52:17.654Z",{"id":1015,"title":1016,"slug":1017,"excerpt":1018,"authors":1019,"reviewedBy":74,"publishedAt":1021,"tags":1022,"gated":78,"businessEmailRequired":78,"legacyUrl":1024,"template":352,"heroImage":1025,"intro":74,"lede":74,"citationId":74,"body":1035,"updatedAt":1166,"createdAt":1167,"_status":335},39,"Charting New Horizons for Clinical Trials: InSilicoTrials at DIA 2024","insilicotrials_dia_2024","InSilicoTrials recently participated in the DIA 2024 Global Annual Meeting, ( 16-20 June, San Diego), sharing valuable insights on the use of in silico trials, digital twins, and AI-powered predictive intelligence in drug development and patient care. This event…",[1020],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-06-25T14:43:57.000Z",[1023],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Finsilicotrials_dia_2024\u002F",{"id":1026,"alt":1027,"updatedAt":1028,"createdAt":1028,"url":1029,"thumbnailURL":74,"filename":1030,"mimeType":359,"filesize":1031,"width":679,"height":680,"focalX":92,"focalY":92,"sizes":1032},1319,"InSilicoTrials_DIA2024","2026-05-25T08:05:36.088Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F36406.jpg","36406.jpg",295029,{"thumbnail":1033,"card":1034},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":1036},{"type":99,"format":9,"indent":100,"version":4,"children":1037},[1038,1046,1050,1066,1070,1100,1104,1111,1115,1135,1139,1154],{"type":103,"format":9,"indent":100,"version":4,"children":1039},[1040,1042,1044],{"text":1041,"type":109,"format":100,"version":4},"InSilicoTrials recently participated in the ",{"text":1043,"type":109,"format":4,"version":4},"DIA 2024 Global Annual Meeting, (",{"text":1045,"type":109,"format":100,"version":4},"16-20 June, San Diego), sharing valuable insights on the use of in silico trials, digital twins, and AI-powered predictive intelligence in drug development and patient care. This event provided a platform for discussing the transformative potential of these technologies and their applications in clinical trials.",{"type":103,"format":9,"indent":100,"version":4,"children":1047},[1048],{"text":1049,"type":109,"format":4,"version":4},"Innovation Theater Presentation Highlights",{"type":103,"format":9,"indent":100,"version":4,"children":1051},[1052,1054,1056,1058,1060,1062,1064],{"text":1053,"type":109,"format":100,"version":4},"During our Innovation Theater presentation titled \"",{"text":1055,"type":109,"format":145,"version":4},"Are Human Patients Needed for Clinical Trials, Tomorrow?",{"text":1057,"type":109,"format":100,"version":4},"\", we brought together experts from various fields to discuss the advancements in",{"text":1059,"type":109,"format":140,"version":4}," in silico",{"text":1061,"type":109,"format":100,"version":4}," methods. The panel included Jonathan Helfgott, PhD (Senior Lecturer, Johns Hopkins University and Former FDA), Adam Kaplin, MD, PhD (Chief Scientific and Clinical Innovation Officer, Miralogx) and our CEO Luca Emili. Moderated by MaryAnne Rizk, PhD (CEO Rizk Management Advisor, Former Oracle, Medidata, IQVIA), the session focused on how ",{"text":1063,"type":109,"format":4,"version":4},"digital simulations can enhance drug development processes",{"text":1065,"type":109,"format":100,"version":4}," and improve patient safety.",{"type":103,"format":9,"indent":100,"version":4,"children":1067},[1068],{"text":1069,"type":109,"format":4,"version":4},"Key Points Discussed:",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":1071,"listType":159},[1072,1082,1092],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1073},[1074,1076,1078,1080],{"text":1075,"type":109,"format":4,"version":4},"Definition and Scope",{"text":1077,"type":109,"format":100,"version":4},": ",{"text":1079,"type":109,"format":140,"version":4},"In silico",{"text":1081,"type":109,"format":100,"version":4}," trials involve the use of computer simulations in the design, development, and regulatory evaluation of new drugs, devices, or interventions. These simulations provide a virtual representation of patient scenarios, allowing for extensive testing without the need for physical trials.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1083},[1084,1086,1088,1090],{"text":1085,"type":109,"format":4,"version":4},"Regulatory Acceptance",{"text":1087,"type":109,"format":100,"version":4},": The panel discussed the growing acceptance of ",{"text":1089,"type":109,"format":140,"version":4},"in silico",{"text":1091,"type":109,"format":100,"version":4}," methods by regulatory bodies like the FDA. This includes recent FDA Modernization Acts that promote the use of computer models as alternatives to animal testing, highlighting a shift towards more ethical and efficient testing methods.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1093},[1094,1096,1097,1098],{"text":1095,"type":109,"format":4,"version":4},"Efficiency and Accuracy",{"text":1077,"type":109,"format":100,"version":4},{"text":1079,"type":109,"format":140,"version":4},{"text":1099,"type":109,"format":100,"version":4}," trials offer significant reductions in time and costs associated with drug development. By identifying and discarding non-viable drug candidates early in the process, companies can save substantial amounts in synthesis costs. Additionally, these methods provide precise and accurate data on drug interactions and mechanisms of action.",{"type":103,"format":9,"indent":100,"version":4,"children":1101},[1102],{"text":1103,"type":109,"format":4,"version":4},"Real-World Applications and Case Studies",{"type":103,"format":9,"indent":100,"version":4,"children":1105},[1106,1108,1109],{"text":1107,"type":109,"format":100,"version":4},"The use of ",{"text":1089,"type":109,"format":140,"version":4},{"text":1110,"type":109,"format":100,"version":4}," models spans across various industries, including pharmaceuticals, cosmetics, and consumer electronics. For instance, pharmaceutical companies use these models for drug discovery and personalized medicine, while cosmetic companies leverage them to predict product safety and efficacy. These applications underscore the versatility and effectiveness of in silico methods.",{"type":103,"format":9,"indent":100,"version":4,"children":1112},[1113],{"text":1114,"type":109,"format":4,"version":4},"Specific Benefits Highlighted:",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":1116,"listType":159},[1117,1123,1129],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1118},[1119,1121],{"text":1120,"type":109,"format":4,"version":4},"Cost and Time Savings",{"text":1122,"type":109,"format":100,"version":4},": Achieving up to a 90% efficiency in specific R&D activities, in silico trials significantly cut down on development time and costs.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1124},[1125,1127],{"text":1126,"type":109,"format":4,"version":4},"Comprehensive Data Generation",{"text":1128,"type":109,"format":100,"version":4},": These methods generate extensive datasets on drug interactions, disease progression, and patient profiles, enhancing the decision-making process.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1130},[1131,1133],{"text":1132,"type":109,"format":4,"version":4},"Risk Mitigation",{"text":1134,"type":109,"format":100,"version":4},": Early identification of potential safety and efficacy issues helps reduce the risk of late-stage failures, ensuring better patient outcomes.",{"type":103,"format":9,"indent":100,"version":4,"children":1136},[1137],{"text":1138,"type":109,"format":4,"version":4},"Engaging with InSilicoTrials",{"type":103,"format":9,"indent":100,"version":4,"children":1140},[1141,1143,1145,1147,1149,1151,1152],{"text":1142,"type":109,"format":100,"version":4},"During the event, attendees were invited to visit Booth #1006 to connect with the InSilicoTrials team and also get autographed copies of \"",{"text":1144,"type":109,"format":145,"version":4},"Towards Good Simulation Practice",{"text":1146,"type":109,"format":100,"version":4},"\". 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Morrison on a significant initiative supported by the FDA and the U.S. Department of Health and Human Services. The project, titled \"A Strategic Imperative for Accelerating Breakthroughs and Market Leadership for FDA-Regulated Products,\" highlights the transformative potential of",{"text":1059,"type":109,"format":140,"version":4},{"text":1198,"type":109,"format":100,"version":4}," methods in medical product R&D.",{"type":103,"format":9,"indent":100,"version":4,"children":1200},[1201,1203,1204],{"text":1202,"type":109,"format":100,"version":4},"This collaborative effort aimed to raise awareness among stakeholders in the medical product development space about the revolutionary opportunities presented by ",{"text":1089,"type":109,"format":140,"version":4},{"text":1205,"type":109,"format":100,"version":4}," trials. The 21st-century technology revolution has paved the way for organizations to manage, process, and harness data more efficiently. Innovations such as artificial intelligence (AI), machine learning (ML), and advanced cybersecurity solutions are now integral to data analysis, automation, and connectivity. Among these innovations, In Silico Technologies (ISTs) stand out for their ability to model, analyze, and predict complex processes, offering significant advantages for the development and evaluation of medical products, food safety measures, and digital health technologies.",{"type":103,"format":9,"indent":100,"version":4,"children":1207},[1208,1210,1212],{"text":1209,"type":109,"format":4,"version":4},"Value Proposition of ",{"text":1211,"type":109,"format":145,"version":4},"In Silico",{"text":1213,"type":109,"format":4,"version":4}," Technologies",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":1215,"listType":159},[1216,1222,1228,1233],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1217},[1218,1220],{"text":1219,"type":109,"format":4,"version":4},"Accelerate Innovation",{"text":1221,"type":109,"format":100,"version":4},": By enabling rapid exploration of promising ideas, ISTs significantly reduce the time required for product development.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1223},[1224,1226],{"text":1225,"type":109,"format":4,"version":4},"Cost-Effective",{"text":1227,"type":109,"format":100,"version":4},": Streamlined knowledge capture and transfer lead to overall reduced development costs.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1229},[1230,1231],{"text":1085,"type":109,"format":4,"version":4},{"text":1232,"type":109,"format":100,"version":4},": With increasing acceptance by the FDA and global regulatory bodies, IST-generated evidence facilitates smoother regulatory submissions.",{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":1234},[1235,1237],{"text":1236,"type":109,"format":4,"version":4},"Enhanced Product Safety",{"text":1238,"type":109,"format":100,"version":4},": ISTs improve the safety profile of devices and drugs, offering a competitive edge over traditional methods.",{"type":103,"format":9,"indent":100,"version":4,"children":1240},[1241],{"text":1242,"type":109,"format":4,"version":4},"Key Drivers for Adoption",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":1244,"listType":159},[1245,1251,1257],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1246},[1247,1249],{"text":1248,"type":109,"format":4,"version":4},"Improved Predictive Capabilities",{"text":1250,"type":109,"format":100,"version":4},": ISTs enhance the ability to predict outcomes, making them invaluable for developing more effective products.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1252},[1253,1255],{"text":1254,"type":109,"format":4,"version":4},"Handling Complexity",{"text":1256,"type":109,"format":100,"version":4},": These technologies can manage increased product complexity, ensuring more reliable and accurate results.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1258},[1259,1261],{"text":1260,"type":109,"format":4,"version":4},"Data Generation for AI",{"text":1262,"type":109,"format":100,"version":4},": ISTs generate comprehensive data sets necessary for training and testing AI models, further enhancing product development processes.",{"type":103,"format":9,"indent":100,"version":4,"children":1264},[1265],{"text":1266,"type":109,"format":4,"version":4},"Dispelling Myths Preventing Adoption",{"type":103,"format":9,"indent":100,"version":4,"children":1268},[1269],{"text":1270,"type":109,"format":100,"version":4},"Several myths hinder the widespread adoption of ISTs. It's crucial to address and dispel these misconceptions: ",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":1272,"listType":159},[1273,1279,1285],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1274},[1275,1277],{"text":1276,"type":109,"format":4,"version":4},"Myth: ISTs are unreliable",{"text":1278,"type":109,"format":100,"version":4},": ISTs have proven reliable across various stages of product development, offering robust and repeatable results.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1280},[1281,1283],{"text":1282,"type":109,"format":4,"version":4},"Myth: High costs with unclear Return on Investment (ROI)",{"text":1284,"type":109,"format":100,"version":4},": While the initial investment can be significant, ISTs lead to long-term cost savings, faster time-to-market, and improved product safety, resulting in a higher return on investment.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1286},[1287,1289],{"text":1288,"type":109,"format":4,"version":4},"Myth: Limited applicability",{"text":1290,"type":109,"format":100,"version":4},": ISTs are applicable across the entire product lifecycle, from early development to post-market evaluation, providing valuable insights and efficiencies at each stage.",{"type":103,"format":9,"indent":100,"version":4,"children":1292},[1293,1295,1296,1298,1299],{"text":1294,"type":109,"format":100,"version":4},"Luca Emili, our CEO, contributed to this important paper, demonstrating InSilicoTrials' dedication to advancing the integration of ",{"text":1089,"type":109,"format":140,"version":4},{"text":1297,"type":109,"format":100,"version":4}," methodologies in medical product development. The initiative shows that delaying the adoption of ",{"text":1089,"type":109,"format":140,"version":4},{"text":1300,"type":109,"format":100,"version":4}," trials could result in missed opportunities and strategic disadvantages, as early integration of these methodologies is crucial for staying competitive and leading in innovation.",{"type":103,"format":9,"indent":100,"version":4,"children":1302},[1303],{"text":1304,"type":109,"format":4,"version":4},"Conclusion",{"type":103,"format":9,"indent":100,"version":4,"children":1306},[1307,1308,1310,1311],{"text":1079,"type":109,"format":140,"version":4},{"text":1309,"type":109,"format":100,"version":4}," technologies are transforming the healthcare industry by providing efficient, cost-effective, and highly predictive tools for innovation and safety assessment. InSilicoTrials can help healthcare organizations accelerate product development, enhance safety, and achieve market leadership through our extensive expertise in ",{"text":1089,"type":109,"format":140,"version":4},{"text":1312,"type":109,"format":100,"version":4}," methodologies. Get in contact now to leverage these technologies and unlock their full potential.",{"type":103,"format":9,"indent":100,"version":4,"children":1314},[1315,1317],{"text":1316,"type":109,"format":100,"version":4},"Read full report: ",{"url":1318,"type":411,"fields":1319,"version":4,"children":1320},"https:\u002F\u002Freaganudall.org\u002Fsites\u002Fdefault\u002Ffiles\u002F2024-06\u002FIn%20Silico%20Technologies_final_0.pdf",{"url":1318,"newTab":413,"linkType":414},[1321],{"text":1318,"type":109,"format":100,"version":4},"2026-05-25T08:07:08.173Z","2026-05-25T07:52:17.606Z",{"id":1325,"title":1326,"slug":1327,"excerpt":1328,"authors":1329,"reviewedBy":74,"publishedAt":1331,"tags":1332,"gated":78,"businessEmailRequired":78,"legacyUrl":1334,"template":352,"heroImage":1335,"intro":74,"lede":74,"citationId":74,"body":1345,"updatedAt":1412,"createdAt":1413,"_status":335},38,"Living with Amyotrophic Lateral Sclerosis","amyotrophic_lateral_sclerosis_webinar","The BRAINTEASER Community of Practice Second webinar Advances in digital technology are helping us to predict the onset of a disease, how it will progress, or which is the best treatment option for a particular person. 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In other words, technology allows us to shift to person-centred healthcare, and what’s more, digital tools can help us from the comfort of our homes. Want to know more?",{"type":103,"format":9,"indent":100,"version":4,"children":1362},[1363,1369],{"url":1364,"type":411,"fields":1365,"version":4,"children":1366},"https:\u002F\u002Fbrainteaser.health\u002Fwp-login.php?action=register",{"url":1364,"newTab":78,"linkType":414},[1367],{"text":1368,"type":109,"format":4,"version":4},"Join",{"text":1370,"type":109,"format":4,"version":4}," BRAINTEASER Community of Practice! 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",{"text":1386,"type":109,"format":140,"version":4},"This disease not only profoundly impacts individuals diagnosed with it but also reverberates throughout their families, friends, and caregivers",{"text":1388,"type":109,"format":100,"version":4},". As the disease progresses, individuals with ALS often require increasing levels of support and care to maintain their quality of life. Moreover, the emotional and psychological toll on both patients and their loved ones cannot be overstated, as they navigate the challenges and uncertainties associated with living with a condition for which there is currently no cure. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1391},"quote",[1392],{"text":1393,"type":109,"format":100,"version":4},"Despite the immense hardships, the ALS community remains resilient, advocating for greater awareness, improved treatments, and enhanced support systems to empower those affected by this relentless disease.",{"type":103,"format":9,"indent":100,"version":4,"children":1395},[1396,1398,1400],{"text":1397,"type":109,"format":100,"version":4}," Scheduled for ",{"text":1399,"type":109,"format":4,"version":4},"14th May 2024 at 12.00 CET",{"text":1401,"type":109,"format":100,"version":4},", the BRAINTEASER CoP webinar will feature distinguished experts and representatives of patients. It aims to delve into ALS diagnosis, personalised medicine, symptomatic treatments, non-pharmacological interventions, psychosocial support for patients and caregivers, and a firsthand account of living with ALS. Each speaker will bring expertise from different fields to provide a comprehensive understanding of managing and supporting individuals affected by ALS.",{"type":103,"format":9,"indent":100,"version":4,"children":1403},[1404,1410],{"url":1405,"type":411,"fields":1406,"version":4,"children":1407},"https:\u002F\u002Fus02web.zoom.us\u002Fwebinar\u002Fregister\u002FWN_bVVmwX_pRPOiUeVyaqf91g#\u002Fregistration",{"url":1405,"newTab":78,"linkType":414},[1408],{"text":1409,"type":109,"format":100,"version":4},"Register here",{"text":1411,"type":109,"format":100,"version":4}," and join us for a stimulating discussion aimed at raising awareness, providing valuable insights, and enhancing understanding!","2026-05-25T08:07:08.128Z","2026-05-25T07:42:52.612Z",{"id":1415,"title":1416,"slug":1417,"excerpt":1418,"authors":1419,"reviewedBy":74,"publishedAt":1421,"tags":1422,"gated":78,"businessEmailRequired":78,"legacyUrl":1424,"template":352,"heroImage":1425,"intro":74,"lede":74,"citationId":74,"body":1436,"updatedAt":1480,"createdAt":1481,"_status":335},37,"Axoltis Pharma receives authorization to launch SEALS - phase II clinical trial for ALS patients with drug candidate NX210c","axoltis-pharma-authorization_seals","InSilicoTrials partners with Axoltis Pharma to leverage advanced modeling technology, generating predictive analyses of disease progression in virtual subjects based on the baseline characteristics of actual enrolled patients. This collaboration will enhance the…",[1420],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-04-18T14:12:00.000Z",[1423],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Faxoltis-pharma-authorization_seals\u002F",{"id":1426,"alt":1416,"updatedAt":1427,"createdAt":1427,"url":1428,"thumbnailURL":74,"filename":1429,"mimeType":359,"filesize":1430,"width":1431,"height":1432,"focalX":92,"focalY":92,"sizes":1433},1295,"2026-05-25T08:05:31.790Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F35580.jpg","35580.jpg",104603,1000,627,{"thumbnail":1434,"card":1435},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":1437},{"type":99,"format":9,"indent":100,"version":4,"children":1438},[1439,1443,1447,1451,1455,1459,1463,1467,1471],{"type":103,"format":9,"indent":100,"version":4,"children":1440},[1441],{"text":1442,"type":109,"format":100,"version":4},"InSilicoTrials partners with Axoltis Pharma to leverage advanced modeling technology, generating predictive analyses of disease progression in virtual subjects based on the baseline characteristics of actual enrolled patients. This collaboration will enhance the development of Axoltis’s NX210c by accelerating the treatment process, improving safety, and reducing development costs.",{"type":103,"format":9,"indent":100,"version":4,"children":1444},[1445],{"text":1446,"type":109,"format":100,"version":4}," Clermont-Ferrand and Lyon, France, April 10, 2024 - Axoltis Pharma, a French biopharmaceutical company dedicated to developing therapeutic solutions for neurodegenerative diseases, today announces the authorization from ANSM, the French agency for the safety of health products, to launch the SEALS study. This phase II clinical trial of drug candidate NX210c in patients with Amyotrophic Lateral Sclerosis (ALS) is the first to target the integrity of the Blood Brain Barrier (BBB).",{"type":103,"format":9,"indent":100,"version":4,"children":1448},[1449],{"text":1450,"type":109,"format":100,"version":4},"ALS is a fatal neurodegenerative disease affecting 50,000 individuals in Europe at any time, resulting in 10,000 deaths each year. It predominantly affects motor neurons in both the brain and spinal cord. This leads to muscular weakness and paralysis, with most patients succumbing to respiratory failure within, on average, two to five years.",{"type":103,"format":9,"indent":100,"version":4,"children":1452},[1453],{"text":1454,"type":109,"format":100,"version":4},"Today, there is no cure for ALS and the only approved drug in the EU for the disease is Riluzole, prolonging survival for a median of just two months. Therefore, ALS remains a progressive and fatal neurologic disease of high unmet need.",{"type":103,"format":9,"indent":100,"version":4,"children":1456},[1457],{"text":1458,"type":109,"format":100,"version":4},"“The therapeutic approach of recovering BBB integrity in ALS patients is very",{"type":103,"format":9,"indent":100,"version":4,"children":1460},[1461],{"text":1462,"type":109,"format":100,"version":4},"promising; here at Axoltis we are proud to have a marked head start in the clinic with NX210c,” said Dr. Annette Janus, neurologist and chief medical officer at Axoltis. “The use of advanced analytical methods will offer a fresh approach to tackling ALS and contribute to the understanding of neurodegenerative diseases overall.”",{"type":103,"format":9,"indent":100,"version":4,"children":1464},[1465],{"text":1466,"type":109,"format":100,"version":4},"SEALS is a double-blind, randomized, placebo-controlled, multicentric phase II study that will assess the efficacy, safety, tolerability and pharmacokinetics of NX210c treatment in ALS patients. Its primary objective is to assess the effect of NX210c via two markers: Neurofilament Light chain (NfL) concentration in the blood, as a diagnostic and prognostic of axonal damage relevant to ALS, as well as the ratio of albumin concentration between CerebroSpinal Fluid (CSF) and blood, which has long been a reliable biomarker of BBB integrity. The study will also evaluate the effect of NX210c on functional outcomes and select secondary biomarkers. The first results are expected by early 2026.",{"type":103,"format":9,"indent":100,"version":4,"children":1468},[1469],{"text":1470,"type":109,"format":100,"version":4},"In another pioneering step, the clinical trial will also incorporate statistical enrichment of the placebo group by adding virtual, in silico patients, based on computational methods of historical control data. This modelling, performed in collaboration with InSilicoTrials (Italy) will create predictions of disease progression in virtual subjects based on actual enrolled patients’ baseline characteristics.",{"type":103,"format":9,"indent":100,"version":4,"children":1472},[1473,1475],{"text":1474,"type":109,"format":100,"version":4},"Read the full press release here: ",{"url":1476,"type":411,"fields":1477,"version":4,"children":1478},"https:\u002F\u002Fwww.axoltis.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002F240410-Axoltis-phase-II-trial-ALS-EN.pdf",{"url":1476,"newTab":78,"linkType":414},[1479],{"text":1476,"type":109,"format":100,"version":4},"2026-05-25T08:07:08.085Z","2026-05-25T07:42:52.579Z",{"id":1483,"title":1484,"slug":1485,"excerpt":1486,"authors":1487,"reviewedBy":74,"publishedAt":1489,"tags":1490,"gated":78,"businessEmailRequired":78,"legacyUrl":1492,"template":352,"heroImage":1493,"intro":74,"lede":74,"citationId":74,"body":1505,"updatedAt":1551,"createdAt":1552,"_status":335},58,"Telomir Pharmaceuticals Presents Promising Pre-Clinical Data For Its Lead Development Product at Singapore Conference","telomir-pharmaceuticals-presents-promising-pre-clinical-data-for-its-lead-development-product-at-singapore-conference","InSilicoTrials collaborates with Telomir Pharmaceuticals, applying cutting-edge AI and simulation technologies to optimize the development of Telomir-1, a promising agent in the battle against age-related conditions, by improving its safety profile and reducing…",[1488],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2024-03-11T14:58:42.000Z",[1491],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Ftelomir-pharmaceuticals-presents-promising-pre-clinical-data-for-its-lead-development-product-at-singapore-conference\u002F",{"id":1494,"alt":1495,"updatedAt":1496,"createdAt":1496,"url":1497,"thumbnailURL":74,"filename":1498,"mimeType":359,"filesize":1499,"width":1500,"height":1501,"focalX":92,"focalY":92,"sizes":1502},1279,"pic for blogpost","2026-05-25T08:05:27.627Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F34830.jpg","34830.jpg",1933991,5760,3240,{"thumbnail":1503,"card":1504},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":1506},{"type":99,"format":9,"indent":100,"version":4,"children":1507},[1508,1513,1523,1535,1539,1543,1547],{"tag":1509,"type":544,"format":9,"indent":100,"version":4,"children":1510},"h5",[1511],{"text":1512,"type":109,"format":100,"version":4},"InSilicoTrials collaborates with Telomir Pharmaceuticals, applying cutting-edge AI and simulation technologies to optimize the development of Telomir-1, a promising agent in the battle against age-related conditions, by improving its safety profile and reducing development costs.",{"type":103,"format":9,"indent":100,"version":4,"children":1514},[1515,1517,1519,1521],{"text":1516,"type":109,"format":100,"version":4},"BALTIMORE, March 07, 2024 (GLOBE NEWSWIRE) -- ",{"text":1518,"type":109,"format":4,"version":4},"Telomir Pharmaceuticals, Inc.",{"text":1520,"type":109,"format":4,"version":4},"(Nasdaq:TELO)",{"text":1522,"type":109,"format":100,"version":4}," (“Telomir” or the “Company”), a pre-clinical-stage pharmaceutical company focused on the development and commercialization of Telomir-1 as the first novel small molecule to lengthen the DNA’s protective telomere caps in order to potentially reverse age-related conditions, today announced that Telomir, alongside its partner Frontage Laboratories, presented a scientific poster at the National University Health System of Singapore (NUHS) Centre for Healthy Longevity Conference 2024 with data showing the effect of Telomir-1 on telomere length in three human cell lines: MRC-5 fetal lung fibroblasts, human umbilical endothelial cells (HUVEC), and mesenchymal stem cells (MSC). The data presented was garnered from pre-clinical studies that Telomir previously disclosed it was undertaking.",{"type":103,"format":9,"indent":100,"version":4,"children":1524},[1525,1527,1529,1531,1533],{"text":1526,"type":109,"format":100,"version":4},"Danielle R. Baker, Ph.D., of Frontage Laboratories, presented the poster, titled “Telomir-1 Induces Telomere Extensions in Primary Human Cell Strains,” at the conference, which took place in Singapore, on February 29",{"text":1528,"type":109,"format":100,"version":4},"th",{"text":1530,"type":109,"format":100,"version":4}," and March 1",{"text":1532,"type":109,"format":100,"version":4},"st",{"text":1534,"type":109,"format":100,"version":4},". The data presented further demonstrated how Telomir-1 increases telomere length and its potential to successfully affect age-related inflammatory conditions.",{"type":103,"format":9,"indent":100,"version":4,"children":1536},[1537],{"text":1538,"type":109,"format":100,"version":4},"“We are honored that this poster was accepted for presentation at the NUHS Conference. Moreover, the promising data we presented at the NUHS Conference showed the advances we are making at potentially treating age-related conditions and prolonging human life,” stated Chris Chapman, MD, co-founder, chairman, chief executive officer and president of Telomir. “If Telomir-1 can safely extend telomeres in people, it could vastly alter the aging process and redefine our potential for living longer, healthier lives. We are excited at what the future holds and we look forward to presenting additional data to the longevity community in the coming months.”",{"type":103,"format":9,"indent":100,"version":4,"children":1540},[1541],{"text":1542,"type":109,"format":100,"version":4},"Dr. Michael Roizen, special advisor to Telomir, added, “While more research is needed, these preliminary findings open up the possibility that many diseases long considered inevitable consequences of aging could become avoidable. This study further demonstrates our belief that Telomir-1 may have the effect of reversing age through telomere regeneration, enabling the production of more stem cells, essentially allowing an individual to repair oneself.”",{"type":103,"format":9,"indent":100,"version":4,"children":1544},[1545],{"text":1546,"type":109,"format":100,"version":4},"The conference was orchestrated by the NUHS Centre for Healthy Longevity, a distinguished entity devoted to extending healthy life by delaying aging, prolonging disease-free life, and maintaining high functionality. Through rigorous research and strategic implementations, the NUHS Centre strives to unveil and promote innovative geroprotective interventions. The CHL Conference 2024 serves as a hallmark event, reflecting the NUHS Centre's steadfast commitment to fostering a collaborative environment, facilitating discourse, and propelling the field of healthy longevity forward.",{"type":103,"format":9,"indent":100,"version":4,"children":1548},[1549],{"text":1550,"type":109,"format":100,"version":4},"As part of its ongoing work on Telomir-1, the Company collaborated with InSilicoTrials, an innovator in leveraging AI and simulations to enhance drug development, to perform advanced AI modeling on Telomir-1. Early research has confirmed the mechanism of action of Telomir-1 and suggests that it may be a potent metal inhibitor, potentially leading to a reversal of aging through telomere regeneration. The collaboration is expected to help accelerate the development of Telomir-1, improve its safety profile, and significantly reduce the research and development costs of Telomir’s drug development program.","2026-05-25T08:07:08.038Z","2026-05-25T07:52:17.546Z",{"id":1554,"title":1555,"slug":1556,"excerpt":1557,"authors":1558,"reviewedBy":74,"publishedAt":1560,"tags":1561,"gated":78,"businessEmailRequired":78,"legacyUrl":1563,"template":352,"heroImage":1564,"intro":74,"lede":74,"citationId":74,"body":1576,"updatedAt":1734,"createdAt":1735,"_status":335},57,"Revolutionizing Healthcare: The Emergence and Impact of Synthetic Data in Life Sciences","revolutionizing-healthcare-the-emergence-and-impact-of-synthetic-data-in-life-sciences","The realm of healthcare and life sciences is undergoing a transformative shift, fueled by the advent and integration of data-driven technologies. At the forefront of this revolution is the burgeoning use of synthetic data, a groundbreaking development poised to…",[1559],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2024-03-07T11:51:48.000Z",[1562],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Frevolutionizing-healthcare-the-emergence-and-impact-of-synthetic-data-in-life-sciences\u002F",{"id":1565,"alt":1566,"updatedAt":1567,"createdAt":1567,"url":1568,"thumbnailURL":74,"filename":1569,"mimeType":88,"filesize":1570,"width":1571,"height":1572,"focalX":92,"focalY":92,"sizes":1573},1273,"synthetic-data","2026-05-25T08:05:25.998Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F34654.png","34654.png",393876,1020,600,{"thumbnail":1574,"card":1575},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":1577},{"type":99,"format":9,"indent":100,"version":4,"children":1578},[1579,1583,1587,1591,1595,1599,1603,1607,1611,1615,1619,1623,1627,1631,1635,1639,1643,1647,1650,1654,1658,1668,1672,1682,1686,1690,1694,1698,1702,1706],{"type":103,"format":9,"indent":100,"version":4,"children":1580},[1581],{"text":1582,"type":109,"format":100,"version":4},"The realm of healthcare and life sciences is undergoing a transformative shift, fueled by the advent and integration of data-driven technologies. At the forefront of this revolution is the burgeoning use of synthetic data, a groundbreaking development poised to redefine the landscape of medical research, AI development, and patient privacy.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1584},[1585],{"text":1586,"type":109,"format":4,"version":4},"The Emergence of Synthetic Data",{"type":103,"format":9,"indent":100,"version":4,"children":1588},[1589],{"text":1590,"type":109,"format":100,"version":4},"Synthetic data is to real-world data as synthetic fiber (like nylon) is to real fiber (like hemp). Humans have created synthetic products throughout our evolution to achieve goals and develop new products that improve our lives. Synthetic fibers are used in clothing, rope, industrial equipment, automobiles, and more. The ability to create synthetic fiber expanded the opportunity to create numerous products that today we find essential.",{"type":103,"format":9,"indent":100,"version":4,"children":1592},[1593],{"text":1594,"type":109,"format":100,"version":4},"Synthetic data has the opportunity to have a similar impact in healthcare. Synthetic data is created based on real-world data using a data synthesizer. These synthesizers may leverage different methods to create synthetic data that have the same statistical and correlative properties as the original data; however, they are completely independent from the real-world data (1, 2).",{"type":103,"format":9,"indent":100,"version":4,"children":1596},[1597],{"text":1598,"type":109,"format":100,"version":4},"Notably, synthetic data do not contain any personal identifying information which ensures personal privacy and full compliance with privacy regulations such as EU's General Data Protection Regulation (GDPR). The use of high-fidelity synthetic data for data augmentation is an area of growing interest in data science, generating virtual patient cohorts, such as digital twins, to estimate counterfactuals in silico trials, allowing for better prediction of treatment outcomes and personalised medicine (3).",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1600},[1601],{"text":1602,"type":109,"format":4,"version":4},"Synthetic Data in Clinical Trials and Healthcare",{"type":103,"format":9,"indent":100,"version":4,"children":1604},[1605],{"text":1606,"type":109,"format":100,"version":4},"In clinical trials and healthcare, synthetic data offer a unique balance of data quality, accuracy, in conjunction with privacy protection. By enabling meaningful analysis without the need to expose sensitive details, they preserve individual privacy while advancing medical research. Furthermore, synthetic data from clinical trials could become a commodity exchanged between researchers without cumbersome legal agreements to ensure personal privacy.",{"type":103,"format":9,"indent":100,"version":4,"children":1608},[1609],{"text":1610,"type":109,"format":100,"version":4},"One use of synthetic data in clinical trials is the inclusion of synthetic control arms created using real-world data to estimate the comparative effectiveness of lurbinectedin versus the historical standard of care for relapsed small cell lung cancer in the post-platinum setting (4). The study was able to evaluate the efficacy of the treatment without the ethical and logistical constraints of enrolling a comparable control group of patients undertaking the historical standard of care. A synthetic control arm was also used for the evaluation of lisocabtagene maraleucel for the treatment of hematological cancer (5). These examples demonstrate that synthetic data can be used to accelerate clinical development.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1612},[1613],{"text":1614,"type":109,"format":4,"version":4},"Market Growth and Privacy Enhancement",{"type":103,"format":9,"indent":100,"version":4,"children":1616},[1617],{"text":1618,"type":109,"format":100,"version":4},"The synthetic data generation market has seen significant growth, reaching USD 163.8 million in 2022 with a projected CAGR of 35.0% from 2023 to 2030, driven by AI integration (6). This market expansion is attributed to synthetic data's capability to mimic real datasets' statistical properties without compromising personal privacy. This technology, akin to creating a completely anonymized version of a detailed photograph, ensures compliance with privacy laws and protects participant anonymity in clinical research.",{"type":103,"format":9,"indent":100,"version":4,"children":1620},[1621],{"text":1622,"type":109,"format":100,"version":4},"Highlighting synthetic data as a pivotal privacy-enhancing tool, Simmons & Simmons note its capacity to foster innovation while adhering to strict privacy regulations. This positions synthetic data as crucial for businesses aiming to utilize large data volumes securely, aligning market growth with the increasing demand for robust data protection in the face of tightening privacy laws.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1624},[1625],{"text":1626,"type":109,"format":100,"version":4},"Challenges and Regulatory Considerations",{"type":103,"format":9,"indent":100,"version":4,"children":1628},[1629],{"text":1630,"type":109,"format":100,"version":4},"The emergence of synthetic data will present new challenges for regulatory bodies like the European Medicines Agency and US Food and Drug Administration as they start to receive requests for marketing authorization that include synthetic data. The European Data Supervisory Board advocates for privacy assurance assessments to guarantee the non-personal nature of synthetic data (7).",{"type":103,"format":9,"indent":100,"version":4,"children":1632},[1633],{"text":1634,"type":109,"format":100,"version":4},"EMA and FDA's recognition of in silico methodologies, including synthetic data, underscores their significance in complementing traditional research methods (8,9,10). Yet concerns remain around the ability of synthetic data to capture small subgroups, outlier profiles, and other aspects of real world data (11). Efforts to compare synthetic data to real-world data must continue to support continued use of synthetic data in clinical development activities.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1636},[1637],{"text":1638,"type":109,"format":100,"version":4},"InSilicoTrials and Synthetic Data",{"type":103,"format":9,"indent":100,"version":4,"children":1640},[1641],{"text":1642,"type":109,"format":100,"version":4}," InSilicoTrials is helping sponsors integrate synthetic data in drug development programs. We help companies leverage synthetic data to support clinical trials in rare diseases, develop synthetic control arms, discuss use cases with regulatory agencies, and more. At InSilicoTrials, our vision is to incorporate synthetic data to accelerate drug development, reduce, refine, and replace clinical trials where possible, and improve the safety of medical products. ",{"type":103,"format":9,"indent":100,"version":4,"children":1644},[1645],{"text":1646,"type":109,"format":100,"version":4},"In conclusion, synthetic data may play a key role in the digital transformation in the healthcare and life sciences sector. Apart from offering a pragmatic solution to privacy concerns, they also open new avenues for market opportunities, research endeavors, and addressing biases which allow for a safe and ethical framework for medical research, where privacy and technological progress coexist harmoniously.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1648},[1649],{"text":646,"type":109,"format":100,"version":4},{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1651},[1652],{"text":1653,"type":109,"format":100,"version":4},"Bange, V., Nwosu, C. and Griffiths, H. (2023) ‘How synthetic data can increase privacy-prioritised data sharing among businesses’, Connect on Tech [Preprint]. Available at: https:\u002F\u002Fconnectontech.com\u002Fhow-synthetic-data-can-increase-privacy-prioritised-data-sharing-among-businesses\u002F.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1655},[1656],{"text":1657,"type":109,"format":100,"version":4},"Bordukova, M. et al. (2024) ‘Generative artificial intelligence empowers digital twins in drug discovery and clinical trials’, Expert Opinion on Drug Discovery, 19(1), pp. 33–42. Available at: https:\u002F\u002Fdoi.org\u002F10.1080\u002F17460441.2023.2273839.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1659},[1660,1662,1667],{"text":1661,"type":109,"format":100,"version":4},"Chen, R.J. et al. (2021) ‘Synthetic data in machine learning for medicine and healthcare’, Nature Biomedical Engineering, 5(6), pp. 493–497. Available at: ",{"url":1663,"type":411,"fields":1664,"version":4,"children":1665},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41551-021-00751-8",{"url":1663,"newTab":78,"linkType":414},[1666],{"text":1663,"type":109,"format":100,"version":4},{"text":451,"type":109,"format":100,"version":4},{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1669},[1670],{"text":1671,"type":109,"format":100,"version":4},"Boyne, D.J. et al. (2023) ‘Comparative Effectiveness of Lurbinectedin for the Treatment of Relapsed Small Cell Lung Cancer in the Post-Platinum Setting: A Real-World Canadian Synthetic Control Arm Analysis’, Targeted Oncology, 18(5), pp. 697–705. Available at: https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11523-023-00995-1.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1673},[1674,1676,1681],{"text":1675,"type":109,"format":100,"version":4},"Van Le, H. et al. (2023) ‘Use of a real-world synthetic control arm for direct comparison of lisocabtagene maraleucel and conventional therapy in relapsed\u002Frefractory large B-cell lymphoma’, Leukemia & Lymphoma, 64(3), pp. 573–585. Available at: ",{"url":1677,"type":411,"fields":1678,"version":4,"children":1679},"https:\u002F\u002Fdoi.org\u002F10.1080\u002F10428194.2022.2160200",{"url":1677,"newTab":78,"linkType":414},[1680],{"text":1677,"type":109,"format":100,"version":4},{"text":451,"type":109,"format":100,"version":4},{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1683},[1684],{"text":1685,"type":109,"format":100,"version":4},"Simmons & Simmons (2023) ‘The Revolution in the Data-Driven Healthcare and Life Sciences Market’.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1687},[1688],{"text":1689,"type":109,"format":100,"version":4},"European Council and European Parliament (2023) ‘Provisional agreement on AI Act’.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1691},[1692],{"text":1693,"type":109,"format":100,"version":4},"EMA (2023) Reflection paper on the use of Artificial Intelligence (AI) in the medicinal product lifecycle. EMA\u002FCHMP\u002FCVMP\u002F83833\u002F2023. European Union: Committee for Medicinal Products for Veterinary Use (CVMP). European Medicines Agency.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1695},[1696],{"text":1697,"type":109,"format":100,"version":4},"European Commission (2023) ‘European Health Data Space’. Available at: https:\u002F\u002Fhealth.ec.europa.eu\u002Fehealth-digital-health-and-care\u002Feuropean-health-data-space_en.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1699},[1700],{"text":1701,"type":109,"format":100,"version":4},"FDA (2023) Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products. Docket No. FDA-2023-N-0743; Document Number: 2023-09985. United States: U.S. Department of Health and Human Services, Food and Drug Administration, pp. 30313–30314.",{"tag":643,"type":544,"format":9,"indent":100,"version":4,"children":1703},[1704],{"text":1705,"type":109,"format":100,"version":4},"Jordon, J. et al. (2022) Synthetic Data - what, why and how? Technical Report. The Alan Turing Institute and The Royal Society. Available at: https:\u002F\u002Fwww.turing.ac.uk.",{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":1707,"listType":613},[1708,1710,1712,1714,1716,1718,1720,1723,1725,1728,1731],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1709},[],{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1711},[],{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1713},[],{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":1715},[],{"type":135,"value":155,"indent":100,"checked":74,"version":4,"children":1717},[],{"type":135,"value":308,"indent":100,"checked":74,"version":4,"children":1719},[],{"type":135,"value":1721,"indent":100,"checked":74,"version":4,"children":1722},7,[],{"type":135,"value":449,"indent":100,"checked":74,"version":4,"children":1724},[],{"type":135,"value":1726,"indent":100,"checked":74,"version":4,"children":1727},9,[],{"type":135,"value":1729,"indent":100,"checked":74,"version":4,"children":1730},10,[],{"type":135,"value":1732,"indent":100,"checked":74,"version":4,"children":1733},11,[],"2026-05-25T08:07:07.966Z","2026-05-25T07:52:17.514Z",{"id":1737,"title":1738,"slug":1739,"excerpt":1740,"authors":1741,"reviewedBy":74,"publishedAt":1743,"tags":1744,"gated":78,"businessEmailRequired":78,"legacyUrl":1746,"template":352,"heroImage":1747,"intro":74,"lede":74,"citationId":74,"body":1759,"updatedAt":1878,"createdAt":1879,"_status":335},36,"Women in Multiple Sclerosis webinar: take-home messages","women-in-multiple-sclerosis-webinar","In the Webinar: Women in Multiple Sclerosis, hosted by the Community of Practice of the BRAINTEASER project, we focused on the role of hormones on the onset and progression of the disease and delved deeply into several aspects of pregnancy. But first, we addressed the…",[1742],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-03-06T13:48:25.000Z",[1745],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fwomen-in-multiple-sclerosis-webinar\u002F",{"id":1748,"alt":1749,"updatedAt":1750,"createdAt":1750,"url":1751,"thumbnailURL":74,"filename":1752,"mimeType":359,"filesize":1753,"width":1754,"height":1755,"focalX":92,"focalY":92,"sizes":1756},1293,"Women in Multiple Sclerosis webinar","2026-05-25T08:05:31.501Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F35578.jpg","35578.jpg",184891,2121,1414,{"thumbnail":1757,"card":1758},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":1760},{"type":99,"format":9,"indent":100,"version":4,"children":1761},[1762,1774,1778,1786,1790,1794,1798,1802,1806,1810,1814,1822,1826,1830,1834,1838,1842,1846,1850,1854,1858,1862,1866,1870,1874],{"type":103,"format":9,"indent":100,"version":4,"children":1763},[1764,1766,1772],{"text":1765,"type":109,"format":100,"version":4},"In the Webinar: Women in Multiple Sclerosis, hosted by the Community of Practice of the ",{"url":1767,"type":411,"fields":1768,"version":4,"children":1769},"https:\u002F\u002Fbrainteaser.health\u002F",{"url":1767,"newTab":413,"linkType":414},[1770],{"text":1771,"type":109,"format":100,"version":4},"BRAINTEASER",{"text":1773,"type":109,"format":100,"version":4}," project, we focused on the role of hormones on the onset and progression of the disease and delved deeply into several aspects of pregnancy. But first, we addressed the need for novel technological solutions to support patients, especially women, on their journey and help clinicians by providing more personalized monitoring.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1775},[1776],{"text":1777,"type":109,"format":100,"version":4},"Amandeep Donna about the BRAINTEASER app: “It’s what people with MS have been waiting for”",{"type":103,"format":9,"indent":100,"version":4,"children":1779},[1780,1782,1784],{"text":1781,"type":109,"format":100,"version":4},"Ms. Amandeep Donna Nahal was diagnosed with multiple sclerosis when she was 17. As a member of the UK MS Society, she shared her personal experience and insights about living as a woman with MS during these 20 years. She explained how patients get all the information during a medical appointment where the clinician provides the diagnosis, which may be overwhelming sometimes. “Once you’ve left that room, you think ",{"text":1783,"type":109,"format":140,"version":4},"that’s it",{"text":1785,"type":109,"format":100,"version":4},", that was your opportunity (to ask questions) and it’s gone.” She then expresses how people with MS have been waiting for a tool like BRAINTEASER, a mobile app that provides support and follow-up. “It’s almost like there’s someone with you,” she says. The need for portable and user-centred technologies comes from the idea that patients do not talk to their neurologist every day, but every day they may be feeling different or having different symptoms. Clinically-validated solutions aim to provide another trustable source of information between clinical visits, both for patients and for physicians. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1787},[1788],{"text":1789,"type":109,"format":4,"version":4},"“I feel like a life touched by MS should not be lost to MS, and I hope that projects like BRAINTEASER can go towards helping that happen.”",{"type":103,"format":9,"indent":100,"version":4,"children":1791},[1792],{"text":1793,"type":109,"format":100,"version":4}," Given the nature of Multiple Sclerosis, a long-lasting disease of the central nervous system that is addressed as an autoimmune disorder, women have a higher prevalence than men. There are some specific tools for women in the market, such as apps to follow the menstrual cycle, but they are not specific for women with MS and their particular needs. Ms. Donna reflects on how patients report during clinical visits what they remember that happened during the last months and their subjective symptoms, but for healthcare professionals to further investigate, technology can help to monitor and show exactly what has happened during that period.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1795},[1796],{"text":1797,"type":109,"format":100,"version":4},"There are sex-related differences in immune response, and the shifting in MS incidence starts in puberty",{"type":103,"format":9,"indent":100,"version":4,"children":1799},[1800],{"text":1801,"type":109,"format":100,"version":4},"Dr. Eleonora Tavazzi, from the Fondazione Istituto Neurologico Nazionale Casimiro Mondino -Pavia (Italy), presented her work about the influence of hormones in different stages of women’s life and how it affects Multiple Sclerosis. There are sex-related differences based on clinical and epidemiological observations. In pre-pubertal phases, girls and boys are affected in a similar 1 to 1 ratio, but in puberty, the statistics shift towards more incidence in women with a ratio of 3 to 1. Sex differences influence the risk of getting the disease but also how it evolves. In general, women are more prone to develop a more inflammatory disease with more relapses, whereas men have a higher risk of developing a more progressive disease course. “These clinical observations are supported by the different composition of the immune system between women and men” states Dr. Tavazzi. As men and women have different immune system compositions, men are at greater risk of infections of any nature (either viral or bacterial) and at higher risk of developing more severe complications. This is because women have an immune system richer in macrophages, B lymphocytes, and CD4+ T lymphocytes. In contrast, women are more susceptible to autoimmune diseases and inflammatory responses.",{"type":1390,"format":9,"indent":100,"version":4,"children":1803},[1804],{"text":1805,"type":109,"format":4,"version":4},"“Sex hormones as oestrogen and progesterone are not only in the structures responsible for the menstrual cycle, they are widespread throughout the central nervous system.”",{"type":103,"format":9,"indent":100,"version":4,"children":1807},[1808],{"text":1809,"type":109,"format":100,"version":4}," For women, the clinical status and the Magnetic Functional Imaging activity related to the disease, fluctuate during the whole woman’s lifespan. One of the reasons is the fluctuation of hormones. The levels of estrogens and progesterone increase during pregnancy and then rapidly decrease after delivery, possibly mediating an immune-stabilizing process. These hormones are present also in the central nervous system, the frontal cortex, and the sensory-motor cortex of our brains, as these are responsible for the sexual behaviour that leads to reproduction. An early puberty is associated with a higher risk of developing MS and, conversely, each year of delayed menarche is associated with a 10% lesser risk of developing MS. There are several possible explanations for this phenomenon that have been widely observed in the scientific literature, including the changes in hormonal patterns or the increase of adiposity in the tissue and its relation to inflammatory molecules. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1811},[1812],{"text":1813,"type":109,"format":4,"version":4},"MS can affect the menstrual cycle, and the menstrual cycle can affect MS-related symptoms",{"type":103,"format":9,"indent":100,"version":4,"children":1815},[1816,1818,1820],{"text":1817,"type":109,"format":100,"version":4}," “Women that were completely irregular with the menstrual cycle before the onset of the disease declared, in a significant proportion, that their menstrual irregularities appeared ",{"text":1819,"type":109,"format":140,"version":4},"after",{"text":1821,"type":109,"format":100,"version":4}," the onset of the disease” states Dr. Tavazzi, highlighting the relation between hormones, the menstrual cycle, and MS. Sex hormones can modulate the release of anti-inflammatory cytokines, important proteins for cell signaling, depending on the phase of the menstrual cycle. In particular, in the first half of the menstrual cycle, there is an increase in perimenstrual symptoms and a transient worsening of MS-related symptoms. Some studies have observed an increase in relapses for 42% of the women with MS during this period. On the contrary, the use of oral contraceptives seems to be associated with a 40% lower risk of developing MS and less contrast-enhancing lesions. Notice that lesions found in the brain through magnetic resonance imaging are a biomarker of the disease. Recent studies have compared different contraceptives, being continuous oral contraceptives associated with less inflammatory activity than cyclic oral contraceptives. The widespread knowledge that mood disorders are related to the menstrual cycle phases is backed by solid scientific literature. As MS can cause damage to the brain’s white matter, it can affect brain structures such as the hypothalamus and the pituitary gland, which are responsible for the regulation of the menstrual cycle. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1823},[1824],{"text":1825,"type":109,"format":4,"version":4},"Women with MS report a lack of communication between patients and healthcare professionals about sexuality issues. “Sexual dysfunctions are definitely common and have a relevant impact on quality of life, but are frequently under-investigated.”",{"type":103,"format":9,"indent":100,"version":4,"children":1827},[1828],{"text":1829,"type":109,"format":100,"version":4}," Although there is evidence that sexual function can be impaired in MS, it is a topic that has been under-investigated. Most of the studies published on this topic report that sexual dysfunctions are very frequent, up to 80% of women with MS usually declare some level of reduced sexual desire or an unsatisfying sexual life. Patients also complain about the lack of communication with their health professionals on the topic. These issues can be related to common MS symptoms that are fatigue, sensory disturbances, and mood disorders. Healthcare professionals can aid women in understanding the possible reasons for their sexuality issues when dealing with MS and provide them with additional resources and information toward a better quality of life. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1831},[1832],{"text":1833,"type":109,"format":4,"version":4},"“There is no proven effect of menopause on the evolution of the disease.”",{"type":103,"format":9,"indent":100,"version":4,"children":1835},[1836],{"text":1837,"type":109,"format":100,"version":4}," When talking about menopause, we find overlapping symptoms: affective disorders, urinary and sexual dysfunction, and cognitive impairment. However, there is no proven effect of menopause on disease evolution and, therefore, no contraindications for menopause-related hormonal therapies. More research is needed to truly assess the potential role of menopause on MS.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":1839},[1840],{"text":1841,"type":109,"format":100,"version":4},"MS is the first degenerative disease affecting women of childbearing age",{"type":103,"format":9,"indent":100,"version":4,"children":1843},[1844],{"text":1845,"type":109,"format":100,"version":4},"Dr. Carlos de Miguel, a physician at the Hospital Gregorio Marañón in Madrid shared his knowledge about pregnancy and answered frequently asked questions from women with MS. MS is the first degenerative disease affecting women of childbearing age, and 20% of women with MS have their first pregnancy after debuting the disease. We know that the child is an organism that is genetically different from the mother, as 50% of the DNA comes from the father and, therefore, it can be considered by the woman’s body as a foreign organism. In other words, it behaves like an allogeneic transplant. However, during pregnancy, there is a mechanism so the immune system of the mother does not attack or reject the child. The complex fetus-placenta interaction secretes soluble factors that produce a reduction in pro-inflammatory cytokines, that is, starts a local immunosuppressive state, an environment where the immune system is more tolerant to foreign organisms. After birth, when the immune system returns to its prior environment, up to 30% can have a relapse. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1847},[1848],{"text":1849,"type":109,"format":4,"version":4},"“MS is not related to a higher number of miscarriage or preterm births, but women with a high disability may require more special treatment.”",{"type":103,"format":9,"indent":100,"version":4,"children":1851},[1852],{"text":1853,"type":109,"format":100,"version":4}," Some of the most frequently asked questions are the following: Can I get pregnant if I am diagnosed with MS? Is there more risk of miscarriage or birth defects? Can I get epidural anaesthesia? MS has not been related to a higher number of miscarriages or preterm births, and women with a higher disability due to MS can require more special treatment. These patients may depend more on assisted fertilization methods to achieve pregnancy and have a higher risk of instrumental labor (forceps) or a C-section.",{"type":103,"format":9,"indent":100,"version":4,"children":1855},[1856],{"text":1857,"type":109,"format":100,"version":4},"The shift in healthcare towards more personalized care, the collection of digital data, and the availability of disease-modifying therapies (DMT) such as immunotherapies for MS patients, has provided novel insights. New data shows that more relapses during the first and second trimesters of pregnancy are expected because of the DMT discontinuation, and a decrease in relapses during the third trimester with an increase after birth is expected. However, disease activity during pregnancy highly depends on previous control, and long-term outcomes are not influenced by pregnancy. If the disease is controlled, physicians recommend breastfeeding, but if it is not controlled DMT should be started acutely. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1859},[1860],{"text":1861,"type":109,"format":4,"version":4},"Multiple Sclerosis is not hereditary.",{"type":103,"format":9,"indent":100,"version":4,"children":1863},[1864],{"text":1865,"type":109,"format":100,"version":4}," Multiple Sclerosis is not hereditary. A predisposition to have MS is what is inherited. The risk for the general population is 0.01%, while for first-grade relatives the risk is 3%, and single twins (who share 100% of their DNA) have only a 38% of probability. Genetics is one of the risk factors but is not a determinant. Additionally, there are no differences in general in children from the general population regarding birth weight, deficits, or gestational age. ",{"type":1390,"format":9,"indent":100,"version":4,"children":1867},[1868],{"text":1869,"type":109,"format":4,"version":4},"“Overall, pregnancy is not contraindicated in women with MS, but better disease control is expected.”",{"type":103,"format":9,"indent":100,"version":4,"children":1871},[1872],{"text":1873,"type":109,"format":100,"version":4}," Treatments of MS are often of category C, meaning that they are more based on animal studies than on humans, where adverse events for the fetus are not clearly assessed. Because of this, young women on DMTs should use proper contraceptive methods and, if they wish to become pregnant in the future, they need to consult their neurologic for DMT discontinuation if necessary. For young women with an active disease, physicians will often prioritize disease control. For women over 35, physicians will mostly prioritize pregnancy safety. There are several options available that the patient needs to discuss with the neurologist and gynecologist: To completely stop the treatment, to maintain injectable treatment during pregnancy, to use natalizumab that can be maintained until the 34th week, induction treatment through Cladribine or Alemtuzumab, or the use of immune depletors such as Ocrelizumab or Ofatumumab. Each case should be considered and evaluated individually, making a priority for disease control and fetal health. In multiple cases, DMTs are maintained during pregnancy. during pregnancy.",{"type":103,"format":9,"indent":100,"version":4,"children":1875},[1876],{"text":1877,"type":109,"format":100,"version":4},"In conclusion, our enlightening webinar on women with multiple sclerosis united 25 participants in a meaningful dialogue driven by the invaluable insights of the expert by experience Amandeep Donna Nahal and two esteemed clinicians, Dr. Eleonora Tavazzi and Dr. Carlos de Miguel. Their comprehensive presentations addressed the significant role of hormones in multiple sclerosis throughout a woman’s life and offered current perspectives on pregnancy-related concerns, addressing frequently asked questions and sharing the latest research findings. This session not only deepened our understanding but also fostered a sense of community and support among those affected by multiple sclerosis. We extend our heartfelt thanks to our speakers and attendees for their engaging participation and look forward to continuing these important conversations in our future events.","2026-05-25T08:07:07.919Z","2026-05-25T07:42:52.531Z",{"id":1881,"title":1882,"slug":1883,"excerpt":1884,"authors":1885,"reviewedBy":74,"publishedAt":1887,"tags":1888,"gated":78,"businessEmailRequired":78,"legacyUrl":1890,"template":352,"heroImage":1891,"intro":74,"lede":74,"citationId":74,"body":1901,"updatedAt":2013,"createdAt":2014,"_status":335},56,"The book ?????? ???? ?????????? ???????? Published Open Access on Springer Nature","towards-good-simulation-practice","InSilicoTrials is thrilled to announce the publication of \" ?????? ??? d ?????????? ???????? - Best practices for the use of computational modelling & simulation in the regulatory process of biomedical products \" a crucial document guiding the use of simulation data &…",[1886],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2024-02-29T10:50:02.000Z",[1889],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Ftowards-good-simulation-practice\u002F",{"id":1892,"alt":1893,"updatedAt":1894,"createdAt":1894,"url":1895,"thumbnailURL":74,"filename":1896,"mimeType":359,"filesize":1897,"width":362,"height":1572,"focalX":92,"focalY":92,"sizes":1898},1263,"HeaderGSP","2026-05-25T08:05:22.889Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F34354.jpg","34354.jpg",284733,{"thumbnail":1899,"card":1900},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":1902},{"type":99,"format":9,"indent":100,"version":4,"children":1903},[1904,1912,1916,1936,1940,1944,1948,1952,1956,1960,1964,1968,1972,1976,1980,2000,2009],{"type":103,"format":9,"indent":100,"version":4,"children":1905},[1906,1908,1910],{"text":1907,"type":109,"format":100,"version":4},"InSilicoTrials is thrilled to announce the publication of \"?????? ???d ?????????? ???????? - ",{"text":1909,"type":109,"format":145,"version":4},"Best practices for the use of computational modelling & simulation in the regulatory process of biomedical products ",{"text":1911,"type":109,"format":100,"version":4},"\" a crucial document guiding the use of simulation data & evidence in the regulatory process of biomedical products.",{"type":103,"format":9,"indent":100,"version":4,"children":1913},[1914],{"text":1915,"type":109,"format":100,"version":4},"This work is the culmination of a global collaboration among in silico experts, coordinated by the In Silico World consortium, with significant contributions from the Avicenna Alliance, VPH Institute, and FDA professionals.",{"type":103,"format":9,"indent":100,"version":4,"children":1917},[1918,1920,1926,1928,1934],{"text":1919,"type":109,"format":100,"version":4},"Published in open access by Springer Nature Group, the book is edited by Prof. ",{"url":1921,"type":411,"fields":1922,"version":4,"children":1923},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002FACoAAAbrrGYBtO2ai0_qLPFYzMMfxc3kvkJU2pY",{"url":1921,"newTab":78,"linkType":414},[1924],{"text":1925,"type":109,"format":100,"version":4},"Marco Viceconti",{"text":1927,"type":109,"format":100,"version":4}," and InSilicoTrials' CEO ",{"url":1929,"type":411,"fields":1930,"version":4,"children":1931},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002FACoAAAAc1uAByuSigA2RgDwc1gAzOJL_vuhQWI0",{"url":1929,"newTab":78,"linkType":414},[1932],{"text":1933,"type":109,"format":100,"version":4},"Luca Emili",{"text":1935,"type":109,"format":100,"version":4},", addressing the need for standardized practices within the in silico field.",{"type":103,"format":9,"indent":100,"version":4,"children":1937},[1938],{"text":1939,"type":109,"format":100,"version":4},"Our strong belief is anchored in the insightful foreword by Pras Pathmanathan from the Office of Science and Engineering Laboratories, Center for Devices and Radiological Health at the FDA, suggesting a future where these words manifest into reality \"… ?? ?? ????? ???? ???? ???? ???? ????????? ??????? ????????????? ??????? ??? ???????????? ??? ?????????? ?????????? ?? ??? ??????????? ?? ?????????-???????? ???? ?????????? ????????, ???????? ?&? ??? ??????? ???????? ?? ????????.\"",{"type":103,"format":9,"indent":100,"version":4,"children":1941},[1942],{"text":1943,"type":109,"format":100,"version":4},"Please find below the book's index and an overview of the chapters' content:",{"type":103,"format":9,"indent":100,"version":4,"children":1945},[1946],{"text":1947,"type":109,"format":100,"version":4},"Introduction",{"type":103,"format":9,"indent":100,"version":4,"children":1949},[1950],{"text":1951,"type":109,"format":100,"version":4},"Theoretical Foundations of GSP",{"type":103,"format":9,"indent":100,"version":4,"children":1953},[1954],{"text":1955,"type":109,"format":100,"version":4},"Model Development",{"type":103,"format":9,"indent":100,"version":4,"children":1957},[1958],{"text":1959,"type":109,"format":100,"version":4},"Model Credibility",{"type":103,"format":9,"indent":100,"version":4,"children":1961},[1962],{"text":1963,"type":109,"format":100,"version":4},"Possible Qualification Pathways for In Silico Methodologies",{"type":103,"format":9,"indent":100,"version":4,"children":1965},[1966],{"text":1967,"type":109,"format":100,"version":4},"Possible Health Technology Assessment Pathways",{"type":103,"format":9,"indent":100,"version":4,"children":1969},[1970],{"text":1971,"type":109,"format":100,"version":4},"Ethical Review of In Silico Methodologies",{"type":103,"format":9,"indent":100,"version":4,"children":1973},[1974],{"text":1975,"type":109,"format":100,"version":4},"The Sponsor",{"type":103,"format":9,"indent":100,"version":4,"children":1977},[1978],{"text":1979,"type":109,"format":100,"version":4},"The Investigator: modellers and analysts ",{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":1981,"listType":613},[1982,1984,1986,1988,1990,1992,1994,1996,1998],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":1983},[],{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":1985},[],{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":1987},[],{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":1989},[],{"type":135,"value":155,"indent":100,"checked":74,"version":4,"children":1991},[],{"type":135,"value":308,"indent":100,"checked":74,"version":4,"children":1993},[],{"type":135,"value":1721,"indent":100,"checked":74,"version":4,"children":1995},[],{"type":135,"value":449,"indent":100,"checked":74,"version":4,"children":1997},[],{"type":135,"value":1726,"indent":100,"checked":74,"version":4,"children":1999},[],{"type":103,"format":9,"indent":100,"version":4,"children":2001},[2002,2004],{"text":2003,"type":109,"format":4,"version":4},"Link to freely download the book: ",{"url":2005,"type":411,"fields":2006,"version":4,"children":2007},"https:\u002F\u002Flink.springer.com\u002Fbook\u002F10.1007\u002F978-3-031-48284-7",{"url":2005,"newTab":78,"linkType":414},[2008],{"text":2005,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2010},[2011],{"text":2012,"type":109,"format":100,"version":4},"If you're seeking more details or interested in exploring how this groundbreaking publication can enhance your biosimulation strategies, don't hesitate to get in touch. Our InSilicoTrials experts are ready to assist you in understanding the implications of Good Simulation Practice (GSP) for your projects, illustrating best practices, and demonstrating use cases to maximize GSP's benefits for your drug development endeavors. ","2026-05-25T08:07:07.882Z","2026-05-25T07:52:17.441Z",{"id":2016,"title":2017,"slug":2018,"excerpt":2019,"authors":2020,"reviewedBy":74,"publishedAt":2022,"tags":2023,"gated":78,"businessEmailRequired":78,"legacyUrl":2025,"template":352,"heroImage":2026,"intro":74,"lede":74,"citationId":74,"body":2037,"updatedAt":2131,"createdAt":2132,"_status":335},35,"Harnessing AI, Big Data, and the European Health Data Space for Revolutionary Advances in Research and Clinical Practice","harnessingai-big-data-and-european-health-data-space","At the Brain Innovation Days held in Brussels on October 26-27, 2023, organised by the European Brain Council, representatives from the BRAINTEASER project and from other pertinent initiatives gathered for a roundtable discussion. The focus was on promoting…",[2021],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-02-28T10:36:06.000Z",[2024],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fharnessingai-big-data-and-european-health-data-space\u002F",{"id":2027,"alt":2017,"updatedAt":2028,"createdAt":2028,"url":2029,"thumbnailURL":74,"filename":2030,"mimeType":359,"filesize":2031,"width":2032,"height":2033,"focalX":92,"focalY":92,"sizes":2034},1289,"2026-05-25T08:05:30.055Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F35568.jpeg","35568.jpeg",108848,788,443,{"thumbnail":2035,"card":2036},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":2038},{"type":99,"format":9,"indent":100,"version":4,"children":2039},[2040,2052,2056,2060,2064,2068,2078,2080,2084,2088,2092,2096,2105,2106,2110,2114,2118,2122],{"type":103,"format":9,"indent":100,"version":4,"children":2041},[2042,2044,2050],{"text":2043,"type":109,"format":100,"version":4},"At the ",{"url":2045,"type":411,"fields":2046,"version":4,"children":2047},"https:\u002F\u002Fwww.braininnovationdays.eu\u002F",{"url":2045,"newTab":413,"linkType":414},[2048],{"text":2049,"type":109,"format":100,"version":4},"Brain Innovation Days",{"text":2051,"type":109,"format":100,"version":4}," held in Brussels on October 26-27, 2023, organised by the European Brain Council, representatives from the BRAINTEASER project and from other pertinent initiatives gathered for a roundtable discussion. The focus was on promoting collaboration among various EU projects and catalysing the translation of research breakthroughs into innovation and policy changes.",{"type":103,"format":9,"indent":100,"version":4,"children":2053},[2054],{"text":2055,"type":109,"format":100,"version":4},"We seised the opportunity to gain insight into their views on AI and Big Data technologies, their impact on the healthcare sector, and to delve into discussions regarding the transformative effects the European Health Data Space will have on research and clinical practices across Europe. ",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":2057},[2058],{"text":2059,"type":109,"format":100,"version":4},"AI and Big Data reshaping development and fostering access to treatment – Florence Butlen-Ducuing",{"type":103,"format":9,"indent":100,"version":4,"children":2061},[2062],{"text":2063,"type":109,"format":100,"version":4}," The field of AI and Big Data is fast evolving, with all stakeholders trying to learn and adjust to these developments. Time is needed to make sure that we set up the right environment to facilitate and enable the use of these new tools for better healthcare. There are a number of options and possibilities using these new tools: from selecting the right populations to improving patient outcome, diagnosis and treatment. The purpose is to create an environment that is really safe, and everybody is willing to trust, and that will ultimately help the patients.",{"type":1390,"format":9,"indent":100,"version":4,"children":2065},[2066],{"text":2067,"type":109,"format":140,"version":4},"“I think the patient centric approach is really what should drive the progress in this field.”",{"type":103,"format":9,"indent":100,"version":4,"children":2069},[2070,2072,2077],{"text":2071,"type":109,"format":100,"version":4}," Watch the interview ",{"url":2073,"type":411,"fields":2074,"version":4,"children":2075},"https:\u002F\u002Fyoutu.be\u002FwCEdk5c76eA",{"url":2073,"newTab":413,"linkType":414},[2076],{"text":929,"type":109,"format":100,"version":4},{"text":451,"type":109,"format":100,"version":4},{"type":2079,"version":4},"horizontalrule",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":2081},[2082],{"text":2083,"type":109,"format":100,"version":4},"Patient engagement in research is a win-win partnership – Paola Zaratin",{"type":103,"format":9,"indent":100,"version":4,"children":2085},[2086],{"text":2087,"type":109,"format":100,"version":4}," There is a growing demand for preventive, predictive, and personalised medicine, as well as an increasing emphasis on prioritising the individual perspectives of patients and citizens in decision-making processes.",{"type":103,"format":9,"indent":100,"version":4,"children":2089},[2090],{"text":2091,"type":109,"format":100,"version":4},"Digital transformation and AI are the catalysers of this shift, allowing clinicians to be closer to patients and researchers to collect huge amounts of data, improving the decision-making process for patients’ health and quality of life. This cannot succeed if we are not able to apply innovative frameworks and innovative participatory research governance to enable stakeholder engagement and patient engagement. We cannot address these two aspects separately; patients’ engagement is a common goal and a common challenge for all stakeholders, since it is vital for the scientific transformation mission. This is evolving as a win-win partnership, a new discipline called “science with and of patient input”.",{"type":1390,"format":9,"indent":100,"version":4,"children":2093},[2094],{"text":2095,"type":109,"format":140,"version":4},"“I am sure that if we are able to engage stakeholders, citizens and patients in this process, we will succeed. Patients know that the free circulation of data, like the European Health Data Space, is a way to bridge research with health care. And they are willing to share their data. When speaking about ownership, patients just want to be engaged. It is not a matter of privacy. It is a matter of knowing what we are going to do with their data, to make decisions for their treatment and quality of life”. ",{"type":103,"format":9,"indent":100,"version":4,"children":2097},[2098,2099,2104],{"text":2071,"type":109,"format":100,"version":4},{"url":2100,"type":411,"fields":2101,"version":4,"children":2102},"https:\u002F\u002Fyoutu.be\u002FKFje-c0qHuw",{"url":2100,"newTab":413,"linkType":414},[2103],{"text":929,"type":109,"format":100,"version":4},{"text":451,"type":109,"format":100,"version":4},{"type":2079,"version":4},{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":2107},[2108],{"text":2109,"type":109,"format":100,"version":4},"The EHDS enabling better use of knowledge and data to boost research, innovation and policy making – Elina Drakvik",{"type":103,"format":9,"indent":100,"version":4,"children":2111},[2112],{"text":2113,"type":109,"format":100,"version":4}," The EHDS is a legislative proposal and the negotiations are still ongoing, so it is a moving target. It is also an emerging practice, so we do not know yet how it will turn out at the end. The main aim though is to create common rules for enabling better use of knowledge and data to boost research, innovation and policy making, but also for education and statistical purposes.",{"type":103,"format":9,"indent":100,"version":4,"children":2115},[2116],{"text":2117,"type":109,"format":100,"version":4},"EHDS will enable faster access to data and therefore will simplify the process for researchers to get the data they need. This will also bring societal benefits, since faster access to data can also then promote discovering novel treatments, access to medicines and also better interventions and prevention measures.",{"type":1390,"format":9,"indent":100,"version":4,"children":2119},[2120],{"text":2121,"type":109,"format":140,"version":4},"“EHDS through this harnessing of the power of data can enable promoting faster and novel access to discovering new drugs, but also personalised treatments, improved healthcare interventions, as well as more targeted prevention measures”. ",{"type":103,"format":9,"indent":100,"version":4,"children":2123},[2124,2125,2130],{"text":2071,"type":109,"format":100,"version":4},{"url":2126,"type":411,"fields":2127,"version":4,"children":2128},"https:\u002F\u002Fyoutu.be\u002FsHcWUKoWnAE",{"url":2126,"newTab":413,"linkType":414},[2129],{"text":929,"type":109,"format":100,"version":4},{"text":451,"type":109,"format":100,"version":4},"2026-05-25T08:07:07.841Z","2026-05-25T07:42:52.498Z",{"id":2134,"title":2135,"slug":2136,"excerpt":2137,"authors":2138,"reviewedBy":74,"publishedAt":2140,"tags":2141,"gated":78,"businessEmailRequired":78,"legacyUrl":2143,"template":352,"heroImage":2144,"intro":74,"lede":74,"citationId":74,"body":2156,"updatedAt":2345,"createdAt":2346,"_status":335},34,"The iDPP@CLEF Challenge as a Way to Open Science","intelligent-disease-progression-prediction-at-clef","iDPP@CLEF [1] is an open evaluation challenge to assess the performance of Artificial Intelligence (AI) algorithms to predict the progression of Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS). iDPP stands for Intelligent Disease Progression Prediction…",[2139],{"id":140,"name":343,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":344,"createdAt":344},"2024-02-14T13:24:17.000Z",[2142],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fintelligent-disease-progression-prediction-at-clef\u002F",{"id":2145,"alt":2146,"updatedAt":2147,"createdAt":2147,"url":2148,"thumbnailURL":74,"filename":2149,"mimeType":88,"filesize":2150,"width":2151,"height":2152,"focalX":92,"focalY":92,"sizes":2153},1287,"Intelligent Disease Progression Prediction at CLEF","2026-05-25T08:05:29.715Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F35561.png","35561.png",295339,980,417,{"thumbnail":2154,"card":2155},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":2157},{"type":99,"format":9,"indent":100,"version":4,"children":2158},[2159,2189,2197,2201,2205,2217,2233,2237,2245,2249,2252],{"type":103,"format":9,"indent":100,"version":4,"children":2160},[2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2183,2185,2187],{"text":2162,"type":109,"format":100,"version":4},"iDPP@CLEF [1] is an open evaluation challenge to assess the performance of ",{"text":2164,"type":109,"format":140,"version":4},"Artificial Intelligence",{"text":2166,"type":109,"format":100,"version":4}," (AI) algorithms to predict the progression of ",{"text":2168,"type":109,"format":140,"version":4},"Amyotrophic Lateral Sclerosis",{"text":2170,"type":109,"format":100,"version":4}," (ALS) and ",{"text":2172,"type":109,"format":140,"version":4},"Multiple Sclerosis",{"text":2174,"type":109,"format":100,"version":4}," (MS). iDPP stands for ",{"text":2176,"type":109,"format":140,"version":4},"Intelligent Disease Progression Prediction",{"text":2178,"type":109,"format":100,"version":4}," and it is a series of events, organised by the ",{"url":1767,"type":411,"fields":2180,"version":4,"children":2181},{"url":1767,"newTab":78,"linkType":414},[2182],{"text":1771,"type":109,"format":100,"version":4},{"text":2184,"type":109,"format":100,"version":4}," project, co-located with the ",{"text":2186,"type":109,"format":140,"version":4},"Conference and Labs of the Evaluation Forum",{"text":2188,"type":109,"format":100,"version":4}," (CLEF) [2] since 2022 [1; 3–6]. This year edition [3] is co-located with CLEF 2024 [4], whose final event will be held in Grenoble, France, from 9 to 12 September 2024.",{"type":103,"format":9,"indent":100,"version":4,"children":2190},[2191,2193,2195],{"text":2192,"type":109,"format":100,"version":4},"ALS and MS are two severe neurodegenerative diseases that affect the ",{"text":2194,"type":109,"format":140,"version":4},"Central Nervous System",{"text":2196,"type":109,"format":100,"version":4}," (CNS). They are chronic diseases characterized by progressive or alternate impairment of neurological functions (motor, sensory, visual, cognitive). Patients undergo alternated periods in hospital with care at home, experiencing a constant uncertainty regarding the timing of the disease acute phases and facing a considerable psychological and economic burden that also involves their caregivers. Clinicians, on the other hand, need tools able to support them in all the phases of the patient treatment, suggest personalized therapeutic decisions, indicate urgently needed interventions.",{"type":103,"format":9,"indent":100,"version":4,"children":2198},[2199],{"text":2200,"type":109,"format":100,"version":4},"Therefore, AI algorithms, trained on both retrospective and prospective patient data, can be of great help to both clinicians and patients in providing indications about the estimated progression of such diseases to support therapeutic decisions, to contribute to better caregiving, and to reduce psychological burden and uncertainty.",{"type":103,"format":9,"indent":100,"version":4,"children":2202},[2203],{"text":2204,"type":109,"format":100,"version":4},"To be effective and accurate such AI algorithms need, at the same time, to be trained on real patient data and to be tested on previously unseen patient data, in order to evaluate and ensure their capacity of reliably operate in real conditions.",{"type":103,"format":9,"indent":100,"version":4,"children":2206},[2207,2209,2211,2213,2215],{"text":2208,"type":109,"format":100,"version":4},"Data is clearly an extremely valuable asset in this context, as in many others, since it comes from real patients and requires years to be collected in sufficient amount for AI algorithms training and testing. In the case of the iDPP challenges we gathered ALS and MS patients’ data from medical institutions in Turin, Pavia, Lisbon, and Madrid and we carefully curated them in order to ensure their quality, correctness, and coherence. This means not only pre-processing, cleaning, and validating the raw patient data but also semantically modelling such data by means of an ontology – the BRAINTEASER Ontology [5] – and representing them in a knowledge base. In other terms, we applied the ",{"text":2210,"type":109,"format":140,"version":4},"FAIR principles",{"text":2212,"type":109,"format":100,"version":4}," (",{"text":2214,"type":109,"format":140,"version":4},"Findability, Accessibility, Interoperability, and Reusability",{"text":2216,"type":109,"format":100,"version":4},") [8] to the preparation and sharing of the datasets for the iDPP challenges in order to maximize their availability, interpretability, and impact, making them a first-class citizen in the exploitation strategy of the BRAINTEASER project.",{"type":103,"format":9,"indent":100,"version":4,"children":2218},[2219,2221,2223,2225,2227,2229,2231],{"text":2220,"type":109,"format":100,"version":4},"However, the FAIR principles are just one of the building blocks of the much broader vision embraced by the ",{"text":2222,"type":109,"format":140,"version":4},"Open Science",{"text":2224,"type":109,"format":100,"version":4}," paradigm [2] which according to the UNESCO recommendation about it: “",{"text":2226,"type":109,"format":140,"version":4},"sets a new paradigm that integrates into the scientific enterprise practices for reproducibility, transparency, sharing and collaboration resulting from the increased opening of scientific contents, tools and processes",{"text":2228,"type":109,"format":100,"version":4},"” [7, p. 7] where ",{"text":2230,"type":109,"format":140,"version":4},"“increased openness leads to increased transparency and trust in scientific information and reinforces the fundamental feature of science as a distinct form of knowledge based on evidence and tested against reality, logic and the scrutiny of scientific peers",{"text":2232,"type":109,"format":100,"version":4},"” [7, p. 18].",{"type":103,"format":9,"indent":100,"version":4,"children":2234},[2235],{"text":2236,"type":109,"format":100,"version":4},"Open Science is clearly crucial for such a sensitive domain as AI for predicting the progression of ALS and MS where not only transparency, trust and reproducibility play a pivotal role but also sharing and collaboration are indispensable to let computer scientists, medical doctors and patients cooperate together and to transfer knowledge.",{"type":103,"format":9,"indent":100,"version":4,"children":2238},[2239,2241,2243],{"text":2240,"type":109,"format":100,"version":4},"In this respect, the iDPP@CLEF challenges are a quite effective way to embody the Open Science and FAIR visions since they create and curate datasets which are then distributed to other researchers participating in the challenges and are available also beyond the challenges themselves under open source licenses; they bring together researchers working on such AI prediction algorithms and let them directly compare their approaches on the same datasets in order to understand what works better and why; they steer the development of such AI algorithms by setting increasingly complex tasks iteration after iteration; they accelerate knowledge transfer by organizing an annual event where participants discuss their approaches, by publishing the technical description and analysis of the participant approaches in open access outlets [7], and by sharing the results of participants’ approaches under open source licenses [8]. Moreover, iDPP@CLEF 2024 relies on prospective patient data of patients currently enrolled in clinical trials promoted by the BRAINTEASER project and this represents a form ",{"text":2242,"type":109,"format":140,"version":4},"of citizens science",{"text":2244,"type":109,"format":100,"version":4},", another pillar of the open science vision. In this context, the annual event in September 2024 will offer the opportunity to involve not only the computer scientists participating in the challenge but also patient associations and medical doctors in order to provide them with feedback on how their data have been used and which results and advancement they produced in the prediction of progression of ALS and MS.",{"type":103,"format":9,"indent":100,"version":4,"children":2246},[2247],{"text":2248,"type":109,"format":100,"version":4},"In summary, the iDPP@CLEF challenges offer to the BRAINTEASER project the possibility of giving added value to its dataset and AI prediction algorithms as well as maximising their impact and exploitation. But, especially, the iDPP@CLEF challenges fully embrace the Open Science parading and contribute to building transparency, trust, reproducibility, and collaboration around such AI prediction algorithms, involving both the research community and the society.",{"tag":543,"type":544,"format":9,"indent":100,"version":4,"children":2250},[2251],{"text":646,"type":109,"format":100,"version":4},{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":2253,"listType":613},[2254,2262,2275,2288,2301,2314,2327,2336],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2255},[2256,2258,2260],{"text":2257,"type":109,"format":100,"version":4},"Aidos, H., Bergamaschi, S., Cavalla, P., Chiò, A., Dagliati, A., Di Camillo, B., de Carvalho, M., Ferro, N., Fariselli, P., Garcia Dominguez, J. M., Madeira, S. C., and Tavazzi, E. (2024). iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. In Nazli, G., Tonellotto, N., He, Y., Lipani, A., McDonald, G., Macdonald, C., and Ounis, I., editors, ",{"text":2259,"type":109,"format":140,"version":4},"Advances in Information Retrieval. Proc. 46th European Confer- ence on IR Research (ECIR 2024) – Part II",{"text":2261,"type":109,"format":100,"version":4},". Lecture Notes in Computer Science (LNCS) 14609, Springer, Heidelberg, Germany.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":2263},[2264,2266,2268,2270],{"text":2265,"type":109,"format":100,"version":4},"Chubin, D. E. (1985). Open Science and Closed Science: Tradeoffs in a Democracy. Science, ",{"text":2267,"type":109,"format":140,"version":4},"Technology, & Human Values",{"text":2269,"type":109,"format":100,"version":4},", 10(2):73–81. ",{"url":2271,"type":411,"fields":2272,"version":4,"children":2273},"https:\u002F\u002Fdoi.org\u002F10.1177\u002F016224398501000211",{"url":2271,"newTab":78,"linkType":414},[2274],{"text":2271,"type":109,"format":100,"version":4},{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":2276},[2277,2279,2281,2283],{"text":2278,"type":109,"format":100,"version":4},"Faggioli, G., Guazzo, A., Marchesin, S., Menotti, L., Trescato, I., Aidos, H., Bergamaschi, R., Birolo, G., Cavalla, P., Chiò, A., Dagliati, A., de Carvalho, M., Di Nunzio, G. M., Fariselli, P., Garc ia Dominguez, J. M., Gromicho, M., Longato, E., Madeira, S. C., Manera, U., Silvello, G., Tavazzi, E., Tavazzi, E., Vettoretti, M., Di Camillo, B., and Ferro, N. (2023). Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2023. In Arampatzis, A., Kanoulas, E., Tsikrika, T., Vrochidis, S., Giachanou, A., Li, D., Aliannejadi, M., Vlachos, M., Fag gioli, G., and Ferro, N., editors, ",{"text":2280,"type":109,"format":140,"version":4},"Experimental IR Meets Multilinguality, Multimodality, and Interaction. Proceedings of the Fourteenth International Conference of the CLEF Association (CLEF 2023",{"text":2282,"type":109,"format":100,"version":4},"), pages 343–369. Lecture Notes in Computer Science (LNCS) 14163, Springer, Heidelberg, Germany. ",{"url":2284,"type":411,"fields":2285,"version":4,"children":2286},"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-031-42448-9_24",{"url":2284,"newTab":78,"linkType":414},[2287],{"text":2284,"type":109,"format":100,"version":4},{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":2289},[2290,2292,2294,2296],{"text":2291,"type":109,"format":100,"version":4},"Faggioli, G., Guazzo, A., Marchesin, S., Menotti, L., Trescato, I., Aidos, H., Bergamaschi, R., Birolo, G., Cavalla, P., Chiò, A., Dagliati, A., de Carvalho, M., Di Nunzio, G. M., Fariselli, P., Garcia Dominguez, J. M., Gromicho, M., Longato, E., Madeira, S. C., Manera, U., Silvello, G., Tavazzi, E., Tavazzi, E., Vettoretti, M., Di Camillo, B., and Ferro, N. (2023). Overview of iDPP@CLEF 2023: The Intelligent Disease Pro- gression Prediction Challenge. In Aliannejadi, M., Faggioli, G., Ferro, N., and Vlachos, M., editors, ",{"text":2293,"type":109,"format":140,"version":4},"CLEF 2023 Working Notes",{"text":2295,"type":109,"format":100,"version":4},", pages 1123– 1164. CEUR Workshop Proceedings (CEUR-WS.org), ISSN 1613-0073. ",{"url":2297,"type":411,"fields":2298,"version":4,"children":2299},"https:\u002F\u002Fceur-ws.org\u002FVol-3497\u002Fpaper-095.pdf",{"url":2297,"newTab":78,"linkType":414},[2300],{"text":2297,"type":109,"format":100,"version":4},{"type":135,"value":155,"indent":100,"checked":74,"version":4,"children":2302},[2303,2305,2307,2309],{"text":2304,"type":109,"format":100,"version":4},"Guazzo, A., Trescato, I., Longato, E., Hazizaj, E., Dosso, D., Faggioli, G., Di Nunzio, G. M., Silvello, G., Vettoretti, M., Tavazzi, E., Roversi,C., Fariselli, P., Madeira, S. C., de Carvalho, M., Gromicho, M., Chiò, A., Manera, U., Dagliati, A., Birolo, G., Aidos, H., Di Camillo, B., and Ferro, N. (2022). Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2022. In Barron-Cedenno, A., Da San Martino, G., Degli Es- posti, M., Sebastiani, F., Macdonald, C., Pasi, G., Hanbury, A., Potthast, M., Faggioli, G., and Ferro, N., editors, ",{"text":2306,"type":109,"format":140,"version":4},"Experimental IR Meets Multilinguality, Multimodality, and Interaction. Proceedings of the Thirteenth International Conference of the CLEF Association (CLEF 2022)",{"text":2308,"type":109,"format":100,"version":4},", pages 395–422. Lecture Notes in Computer Science (LNCS) 13390, Springer, Heidelberg, Germany. ",{"url":2310,"type":411,"fields":2311,"version":4,"children":2312},"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-031-13643-6_25",{"url":2310,"newTab":78,"linkType":414},[2313],{"text":2310,"type":109,"format":100,"version":4},{"type":135,"value":308,"indent":100,"checked":74,"version":4,"children":2315},[2316,2318,2320,2322],{"text":2317,"type":109,"format":100,"version":4},"Guazzo, A., Trescato, I., Longato, E., Hazizaj, E., Dosso, D., Faggioli, G., Di Nunzio, G. M., Silvello, G., Vettoretti, M., Tavazzi, E., Roversi, C., Fariselli, P., Madeira, S. C., de Carvalho, M., Gromicho, M., Chiò, A., Manera, U., Dagliati, A., Birolo, G., Aidos, H., Di Camillo, B., and Ferro, N. (2022). Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge. In Faggioli, G., Ferro, N., Hanbury, A., and Potthast, M., editors, ",{"text":2319,"type":109,"format":140,"version":4},"CLEF 2022 Working Notes",{"text":2321,"type":109,"format":100,"version":4},", pages 1130– 1210. CEUR Workshop Proceedings (CEUR-WS.org), ISSN 1613-0073. ",{"url":2323,"type":411,"fields":2324,"version":4,"children":2325},"https:\u002F\u002Fceur-ws.org\u002FVol-3180\u002Fpaper-88.pdf",{"url":2323,"newTab":78,"linkType":414},[2326],{"text":2323,"type":109,"format":100,"version":4},{"type":135,"value":1721,"indent":100,"checked":74,"version":4,"children":2328},[2329,2331],{"text":2330,"type":109,"format":100,"version":4},"UNESCO (2021). UNESCO Recommendation on Open Science. UNESCO, Paris, France, SC-PCB-SPP\u002F2021\u002FOS\u002FUROS. ",{"url":2332,"type":411,"fields":2333,"version":4,"children":2334},"https:\u002F\u002Fdoi.org\u002F10.54677\u002FMNMH8546",{"url":2332,"newTab":78,"linkType":414},[2335],{"text":2332,"type":109,"format":100,"version":4},{"type":135,"value":449,"indent":100,"checked":74,"version":4,"children":2337},[2338,2340],{"text":2339,"type":109,"format":100,"version":4},"Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J., Groth, P., Goble, C., Grethe, J. S., Heringa, J., ’t Hoen, P., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A., Packer, A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M. A., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Nature Scientific Data, 3(160018). ",{"url":2341,"type":411,"fields":2342,"version":4,"children":2343},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fsdata.2016.18",{"url":2341,"newTab":78,"linkType":414},[2344],{"text":2341,"type":109,"format":100,"version":4},"2026-05-25T08:07:07.788Z","2026-05-25T07:42:52.465Z",{"id":2348,"title":2349,"slug":2350,"excerpt":2351,"authors":2352,"reviewedBy":74,"publishedAt":2354,"tags":2355,"gated":78,"businessEmailRequired":78,"legacyUrl":2357,"template":352,"heroImage":2358,"intro":74,"lede":74,"citationId":74,"body":2370,"updatedAt":2394,"createdAt":2395,"_status":335},55,"Axoltis Pharma's Breakthrough in Neurodegenerative Disease Research, Supported by InSilicoTrials","axoltis-pharmas-breakthrough-in-neurodegenerative-disease-research-supported-by-insilicotrials","Axoltis Pharma is at the forefront of developing treatments for neurodegenerative diseases, with their phase 1b clinical trial of NX210c marking a notable achievement in the field. 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This peptide drug candidate has shown promising results following a successful phase 1a study, demonstrating not only a good safety profile but also significant pharmacodynamic effects. These findings are crucial as they highlight the drug’s potential in improving neuroprotection, neurotransmission, and particularly in maintaining the integrity of the Blood-Brain Barrier, a key factor in neurodegenerative conditions.",{"type":103,"format":9,"indent":100,"version":4,"children":2378},[2379],{"text":2380,"type":109,"format":100,"version":4},"The company is now preparing to take significant steps forward. Plans are underway for a phase 2 trial targeting ALS patients and an extension of the phase 1b trial to include individuals with Parkinson’s Disease. These trials are vital in exploring the broader potential of NX210c and represent a major commitment from Axoltis Pharma towards addressing some of the most challenging aspects of neurodegenerative diseases.",{"type":103,"format":9,"indent":100,"version":4,"children":2382},[2383],{"text":2384,"type":109,"format":100,"version":4},"Supporting Axoltis Pharma in this endeavor is InSilicoTrials, whose expertise in computational modeling will help provide valuable insights into the drug's effectiveness and potential applications, fully exploring the potential effects of NX210c in neurodegenerative disease models.",{"type":103,"format":9,"indent":100,"version":4,"children":2386},[2387,2389],{"text":2388,"type":109,"format":100,"version":4},"Find out more: ",{"url":2390,"type":411,"fields":2391,"version":4,"children":2392},"https:\u002F\u002Fala.associates\u002Fclinical\u002Faxoltis-pharma-presents-promising-results-from-phase-1b-clinical-trial-of-innovative-drug-candidate-for-neurodegenerative-diseases\u002F",{"url":2390,"newTab":78,"linkType":414},[2393],{"text":2390,"type":109,"format":100,"version":4},"2026-05-25T08:07:07.742Z","2026-05-25T07:52:17.385Z",{"id":2397,"title":2398,"slug":2399,"excerpt":2400,"authors":2401,"reviewedBy":74,"publishedAt":2403,"tags":2404,"gated":78,"businessEmailRequired":78,"legacyUrl":2406,"template":352,"heroImage":2407,"intro":74,"lede":74,"citationId":74,"body":2419,"updatedAt":2480,"createdAt":2481,"_status":335},33,"AI state-of-play around clinical research – BRAINTEASER Community of Practice","ai-state-of-play-around-clinical-research-brainteaser-community-of-practice","The life sciences sector is beginning to experience the transformative effects of AI, with numerous applications offering clinical, operational, and medical advantages. 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Unlike other industries, life sciences face the unique challenge of safeguarding patient safety and privacy. This has led to heightened regulatory scrutiny regarding the development, validation, and implementation of AI technology in this field.",{"type":103,"format":9,"indent":100,"version":4,"children":2427},[2428,2430,2436,2438,2444],{"text":2429,"type":109,"format":100,"version":4},"In this environment, the AI Task Force, initiated by the ",{"url":2431,"type":411,"fields":2432,"version":4,"children":2433},"https:\u002F\u002Fwww.eucrof.eu\u002Fhome-new\u002Fworking-groups-eucrof",{"url":2431,"newTab":78,"linkType":414},[2434],{"text":2435,"type":109,"format":100,"version":4},"New Technologies Working Group of EUCROF",{"text":2437,"type":109,"format":100,"version":4}," and the ",{"url":2439,"type":411,"fields":2440,"version":4,"children":2441},"https:\u002F\u002Feclinicalforum.org\u002F",{"url":2439,"newTab":78,"linkType":414},[2442],{"text":2443,"type":109,"format":100,"version":4},"eClinical Forum",{"text":2445,"type":109,"format":100,"version":4},", aims to monitor the evolution of AI technologies and development of related regulations in life sciences and address relevant topics that are of major interest for clinical research.",{"type":103,"format":9,"indent":100,"version":4,"children":2447},[2448,2450,2456],{"text":2449,"type":109,"format":100,"version":4},"The white paper “",{"url":2451,"type":411,"fields":2452,"version":4,"children":2453},"https:\u002F\u002Fwww.eucrof.eu\u002Fimages\u002F23_11_06_AI_State-of-Play_Around_Clinical_Research_15Sep23__vPR1_Approved_by_eCF_SC_for_Release.pdf",{"url":2451,"newTab":78,"linkType":414},[2454],{"text":2455,"type":109,"format":100,"version":4},"AI state-of-play around clinical research",{"text":2457,"type":109,"format":100,"version":4},"” provides information about the state-of-play of artificial intelligence (AI) and machine learning (ML) for clinical research.",{"type":103,"format":9,"indent":100,"version":4,"children":2459},[2460],{"text":2461,"type":109,"format":100,"version":4},"The state-of-the-art of AI in clinical research is presented in four sections, focused on the following topics: ",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":2463,"listType":159},[2464,2468,2472,2476],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2465},[2466],{"text":2467,"type":109,"format":100,"version":4},"An overview of the status of regulations in the United States, Europe, Asia and the rest of the world",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":2469},[2470],{"text":2471,"type":109,"format":100,"version":4},"A review of major use cases for the domain",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":2473},[2474],{"text":2475,"type":109,"format":100,"version":4},"Recommendations for best practices in development and validation of AI in clinical research",{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":2477},[2478],{"text":2479,"type":109,"format":100,"version":4},"A statement of this task force’s current positions and future work","2026-05-25T08:07:07.700Z","2026-05-25T07:42:52.431Z",{"id":2483,"title":2484,"slug":2485,"excerpt":2486,"authors":2487,"reviewedBy":74,"publishedAt":2489,"tags":2490,"gated":78,"businessEmailRequired":78,"legacyUrl":2492,"template":352,"heroImage":2493,"intro":74,"lede":74,"citationId":74,"body":2505,"updatedAt":2571,"createdAt":2572,"_status":335},32,"Cutting-edge Big Data initiative seeks to provide crucial support to people affected by Amyotrophic Lateral Sclerosis and Multiple Sclerosis","cutting-edge-big-data-initiative-seeks-to-provide-crucial-support-to-people-affected-by-amyotrophic-lateral-sclerosis-and-multiple-sclerosis-2","Mamede de Carvalho, a renowned neurologist and the head of the Amyotrophic Lateral Sclerosis (ALS) Clinic at Centro Hospitalar Universitário Lisboa Norte (CHULN), situated at the prestigious Hospital de Santa Maria, recently unveiled the exciting BRAINTEASER project…",[2488],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2023-12-07T08:19:08.000Z",[2491],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fcutting-edge-big-data-initiative-seeks-to-provide-crucial-support-to-people-affected-by-amyotrophic-lateral-sclerosis-and-multiple-sclerosis-2\u002F",{"id":2494,"alt":2495,"updatedAt":2496,"createdAt":2496,"url":2497,"thumbnailURL":74,"filename":2498,"mimeType":88,"filesize":2499,"width":2500,"height":2501,"focalX":92,"focalY":92,"sizes":2502},1182,"Cutting edge","2026-05-25T08:05:05.548Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F32719-1.png","32719-1.png",158996,409,230,{"thumbnail":2503,"card":2504},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":2506},{"type":99,"format":9,"indent":100,"version":4,"children":2507},[2508,2527,2531,2535,2539,2543,2547,2551,2555,2559,2563,2567],{"type":103,"format":9,"indent":100,"version":4,"children":2509},[2510,2512,2518,2520,2526],{"text":2511,"type":109,"format":100,"version":4},"Mamede de Carvalho, a renowned neurologist and the head of the Amyotrophic Lateral Sclerosis (ALS) Clinic at Centro Hospitalar Universitário Lisboa Norte (CHULN), situated at the prestigious Hospital de Santa Maria, recently unveiled the exciting BRAINTEASER project during an exclusive ",{"url":2513,"type":411,"fields":2514,"version":4,"children":2515},"https:\u002F\u002Fsaudeonline.pt\u002Fprojeto-de-big-data-visa-ajudar-doentes-com-esclerose-lateral-amiotrofica-e-esclerose-multipla\u002F",{"url":2513,"newTab":78,"linkType":414},[2516],{"text":2517,"type":109,"format":100,"version":4},"interview",{"text":2519,"type":109,"format":100,"version":4}," with ",{"url":2521,"type":411,"fields":2522,"version":4,"children":2523},"https:\u002F\u002Fsaudeonline.pt\u002F",{"url":2521,"newTab":78,"linkType":414},[2524],{"text":2525,"type":109,"format":100,"version":4},"SaúdeOnline",{"text":451,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2528},[2529],{"text":2530,"type":109,"format":100,"version":4},"Here are some captivating insights from Professor de Carvalho’s presentation.",{"type":103,"format":9,"indent":100,"version":4,"children":2532},[2533],{"text":2534,"type":109,"format":4,"version":4},"What is the current status of the BRAINTEASER project?",{"type":103,"format":9,"indent":100,"version":4,"children":2536},[2537],{"text":2538,"type":109,"format":100,"version":4},"BRAINTEASER commenced in January 2021 and is slated for completion at the close of 2024. At present, the project is actively enrolling patients and gathering their data, all while continually enhancing the technical aspects of analysis tools and algorithms. It’s worth noting that some project data is already available to the worldwide scientific community.",{"type":103,"format":9,"indent":100,"version":4,"children":2540},[2541],{"text":2542,"type":109,"format":4,"version":4},"What is the added value for patients?",{"type":103,"format":9,"indent":100,"version":4,"children":2544},[2545],{"text":2546,"type":109,"format":100,"version":4},"The added value is (1) closer and more continuous monitoring of patients and their caregivers, avoiding the necessary periodicity of hospital visits; (2) faster perception of more complex clinical events and situations that may require more timely intervention by the medical team; (3) greater opportunities for inclusion in clinical trials of new drugs, with a greater likelihood of finding a positive effect; (4) and satisfaction in participating in a scientific study that will potentially condition the advantages listed above.",{"type":103,"format":9,"indent":100,"version":4,"children":2548},[2549],{"text":2550,"type":109,"format":4,"version":4},"What significant stride can this project represent for clinicians?",{"type":103,"format":9,"indent":100,"version":4,"children":2552},[2553],{"text":2554,"type":109,"format":100,"version":4},"It paves the way for the creation of artificial intelligence algorithms, underpinned by extensive data, which can identify previously undiscovered clinical insights. This breakthrough holds the promise of delivering more efficient and individualized treatment and care to each patient.",{"type":103,"format":9,"indent":100,"version":4,"children":2556},[2557],{"text":2558,"type":109,"format":4,"version":4},"One of the factors BRAINTEASER investigates is the correlation between the two diseases and air pollution. Can it be stated that this research, by exploiting cutting-edge technologies, will broaden the scope of the investigation, making it more complete?",{"type":103,"format":9,"indent":100,"version":4,"children":2560},[2561],{"text":2562,"type":109,"format":100,"version":4},"Environmental factors are regarded as pertinent to the onset and advancement of both diseases under examination. Therefore, conducting a systematic and quantitative investigation into these factors could yield highly significant insights.",{"type":103,"format":9,"indent":100,"version":4,"children":2564},[2565],{"text":2566,"type":109,"format":4,"version":4},"Regarding big data and AI, some fears arise, particularly about security. Are there any risks associated with this project?",{"type":103,"format":9,"indent":100,"version":4,"children":2568},[2569],{"text":2570,"type":109,"format":100,"version":4},"The project complies with European and national data protection regulations. A computer system assigns random codes to patients, effectively replacing identifiable details such as names, addresses, full zip codes and dates of birth. The only individual who knows the patient’s identity, in this case, myself in Portugal, retains this information. The data is amalgamated with a large dataset of other patient information and subjected to analysis through mathematical algorithms using computer techniques. It’s like finding the specific hen that contributed an egg to our omelette, a complex but safe process.","2026-05-25T08:07:07.556Z","2026-05-25T07:42:52.385Z",{"id":2574,"title":2575,"slug":2576,"excerpt":2577,"authors":2578,"reviewedBy":74,"publishedAt":2580,"tags":2581,"gated":78,"businessEmailRequired":78,"legacyUrl":2586,"template":352,"heroImage":2587,"intro":74,"lede":74,"citationId":74,"body":2599,"updatedAt":2742,"createdAt":2743,"_status":335},54,"InSilicoTrials’ Talks Series Listen our IST Customer Testimonial - Yann Godfrin, CEO of Axoltis Pharma","insilicotrials-talks-series-listen-our-ist-customer-testimonial-yann-godfrin-ceo-of-axoltis-pharma","Welcome back to InSilicoTrials’ Talks! We're excited to launch our IST Customer Testimonials’ initiative, a series dedicated to hearing directly from our clients. Today, we feature Yann Godfrin , CEO of Axoltis Pharma, who joined us for an insightful in silico chat.…",[2579],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2023-11-13T13:21:39.000Z",[2582],{"id":140,"name":2583,"slug":2584,"updatedAt":2585,"createdAt":2585},"In Silico Talks","in-silico-talks","2026-05-25T07:42:25.373Z","\u002Finsilicotrials-talks-series-listen-our-ist-customer-testimonial-yann-godfrin-ceo-of-axoltis-pharma\u002F",{"id":2588,"alt":2589,"updatedAt":2590,"createdAt":2590,"url":2591,"thumbnailURL":74,"filename":2592,"mimeType":88,"filesize":2593,"width":2594,"height":2595,"focalX":92,"focalY":92,"sizes":2596},1118,"in-silico-talkk-new-banner","2026-05-25T08:04:50.145Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F32020.png","32020.png",235087,8000,4500,{"thumbnail":2597,"card":2598},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":2600},{"type":99,"format":9,"indent":100,"version":4,"children":2601},[2602,2625,2631,2651,2662,2670,2696,2700,2706,2738],{"type":103,"format":9,"indent":100,"version":4,"children":2603},[2604,2606,2612,2614,2620,2622,2623],{"text":2605,"type":109,"format":100,"version":4},"Welcome back to InSilicoTrials’ Talks! We're excited to launch our IST Customer Testimonials’ initiative, a series dedicated to hearing directly from our clients. Today, we feature ",{"url":2607,"type":411,"fields":2608,"version":4,"children":2609},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fyann-godfrin-ph-d-110a621\u002F",{"url":2607,"newTab":78,"linkType":414},[2610],{"text":2611,"type":109,"format":100,"version":4},"Yann Godfrin",{"text":2613,"type":109,"format":100,"version":4},", CEO of ",{"url":2615,"type":411,"fields":2616,"version":4,"children":2617},"https:\u002F\u002Fwww.axoltis.com",{"url":2615,"newTab":78,"linkType":414},[2618],{"text":2619,"type":109,"format":100,"version":4},"Axoltis Pharma,",{"text":2621,"type":109,"format":100,"version":4}," who joined us for an insightful ",{"text":1089,"type":109,"format":140,"version":4},{"text":2624,"type":109,"format":100,"version":4}," chat. Discover why InSilicoTrials was their choice for advancing CNS disorder treatments and the benefits they've experienced from in silico technologies.",{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":2626,"listType":613},[2627],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2628},[2629],{"text":2630,"type":109,"format":140,"version":4},"Why did you choose InSilicoTrials for your project\u002Fneeds? ",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":2632,"listType":159},[2633,2639,2645],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2634},[2635,2637],{"text":2636,"type":109,"format":4,"version":4},"Specialized Project in CNS Disorders:",{"text":2638,"type":109,"format":100,"version":4}," We are working on a special project focused on CNS (Central Nervous System) disorders. which involves \"agnostic indications,\" meaning we can target many indications within CNS disorders and neurology.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":2640},[2641,2643],{"text":2642,"type":109,"format":4,"version":4},"Utilization of In Silico Technology:",{"text":2644,"type":109,"format":100,"version":4}," We have a desire to utilize in silico technology, which involves computer simulations, to help select and optimize our next steps in clinical development. This technology aids in determining the best regimen of treatment to maximize the chances of success.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":2646},[2647,2649],{"text":2648,"type":109,"format":4,"version":4},"Company Visibility and Communication:",{"text":2650,"type":109,"format":100,"version":4}," We have acknowledged the visibility of InSilicoTrials due to its social media presence and communication efforts, which helped us easily identify and choose the company. We have also identified other companies, but IST was the one with the best fit according to what we wished to explore.",{"type":103,"format":9,"indent":100,"version":4,"children":2652},[2653,2655,2660],{"text":2654,"type":109,"format":4,"version":4},"To sum up, the decision to choose ",{"url":2656,"type":411,"fields":2657,"version":4,"children":2658},"https:\u002F\u002Fumx.369.myftpupload.com",{"url":2656,"newTab":78,"linkType":414},[2659],{"text":72,"type":109,"format":4,"version":4},{"text":2661,"type":109,"format":4,"version":4}," was influenced by our company specialization in CNS and InSilicoTrials technological capabilities, as well as its visibility and communication in the field.",{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":2663,"listType":613},[2664],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2665},[2666,2668],{"text":2667,"type":109,"format":140,"version":4},"What benefits have you experienced by incorporating in silico approaches into your projects",{"text":2669,"type":109,"format":100,"version":4},"?",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":2671,"listType":159},[2672,2678,2684,2690],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2673},[2674,2676],{"text":2675,"type":109,"format":4,"version":4},"Risk Reduction:",{"text":2677,"type":109,"format":100,"version":4}," in silico approaches help in reducing the risk of development, which is particularly significant for ventures that are inherently risky, like a biotech company",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":2679},[2680,2682],{"text":2681,"type":109,"format":4,"version":4},"Increased Chance of Success:",{"text":2683,"type":109,"format":100,"version":4}," Utilizing in silico modeling to predict outcomes of clinical trials allows for better regimen choices, thereby increasing the chances of success. The practical applicability and acceptance by authorities of in silico proposed dosage signify that it could potentially streamline certain processes in clinical trials.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":2685},[2686,2688],{"text":2687,"type":109,"format":4,"version":4},"Aid in Fundraising:",{"text":2689,"type":109,"format":100,"version":4}," The use of in silico methods makes projects more appealing to venture capitalists by demonstrating a well-thought-out approach, thus aiding in fundraising.",{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":2691},[2692,2694],{"text":2693,"type":109,"format":4,"version":4},"Strategic Advantages:",{"text":2695,"type":109,"format":100,"version":4}," Companies utilizing in silico approaches are deemed to have a strategic advantage over those relying solely on traditional methods, especially when seeking investments and competing in the market.",{"type":103,"format":9,"indent":100,"version":4,"children":2697},[2698],{"text":2699,"type":109,"format":4,"version":4},"In conclusion, the integration of in silico methodologies into our operations offers multifaceted benefits ranging from risk mitigation and heightened success rates to aiding in financial backing and ensuring a strategic edge in the competitive landscape.",{"tag":579,"type":132,"start":4,"indent":100,"version":4,"children":2701,"listType":613},[2702],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2703},[2704],{"text":2705,"type":109,"format":140,"version":4},"In your opinion, what are the key advantages of using in silico methods over traditional approaches in your field? ",{"tag":131,"type":132,"start":4,"indent":100,"version":4,"children":2707,"listType":159},[2708,2714,2720,2726,2732],{"type":135,"value":4,"indent":100,"checked":74,"version":4,"children":2709},[2710,2712],{"text":2711,"type":109,"format":4,"version":4},"De-risking Developmental Process: ",{"text":2713,"type":109,"format":100,"version":4},"In silico approaches allow for the de-risking of the developmental process by providing insights and predictions that can be accounted for in the early stages.",{"type":135,"value":140,"indent":100,"checked":74,"version":4,"children":2715},[2716,2718],{"text":2717,"type":109,"format":4,"version":4},"Enhanced Valuation",{"text":2719,"type":109,"format":100,"version":4},": By reducing risk and increasing the likelihood of success, in silico methods contribute to enhancing the valuation of the projects\u002Fcompanies.",{"type":135,"value":145,"indent":100,"checked":74,"version":4,"children":2721},[2722,2724],{"text":2723,"type":109,"format":4,"version":4},"Clever Investment Opportunity",{"text":2725,"type":109,"format":100,"version":4},": The speaker suggests that incorporating in silico approaches presents a more \"clever bet\" to venture capitalists, as it demonstrates a comprehensive and strategic approach to development.",{"type":135,"value":150,"indent":100,"checked":74,"version":4,"children":2727},[2728,2730],{"text":2729,"type":109,"format":4,"version":4},"Optimized Clinical Approaches",{"text":2731,"type":109,"format":100,"version":4},": The in silico approach optimizes the selection and mobilization in clinical approaches, improving overall development strategies. The mention of “deep technology and deep mathematical approach” suggests that in silico methods might offer more detailed and comprehensive analysis compared to traditional approaches.",{"type":135,"value":155,"indent":100,"checked":74,"version":4,"children":2733},[2734,2736],{"text":2735,"type":109,"format":4,"version":4},"Time Efficiency",{"text":2737,"type":109,"format":100,"version":4},": In silico models offer time advantages by predicting possible outcomes and thereby allowing for more strategic planning and execution.",{"type":103,"format":9,"indent":100,"version":4,"children":2739},[2740],{"text":2741,"type":109,"format":4,"version":4},"To recap, in silico approaches are pivotal in modernizing drug development by significantly reducing risks, optimizing clinical approaches, and allowing for more strategic planning and execution due to their detailed and comprehensive analysis compared to traditional approaches.","2026-05-25T08:07:07.502Z","2026-05-25T07:52:17.315Z",{"id":2745,"title":2746,"slug":2747,"excerpt":2748,"authors":2749,"reviewedBy":74,"publishedAt":2751,"tags":2752,"gated":78,"businessEmailRequired":78,"legacyUrl":2754,"template":352,"heroImage":2755,"intro":74,"lede":74,"citationId":74,"body":2767,"updatedAt":2848,"createdAt":2849,"_status":335},53,"Collaboration Between InSilicoTrials and Biofarma Group Explores the Benefits of In Silico Technology in Clinical Research","collaboration-between-insilicotrials-and-biofarma-group-explores-the-benefits-of-in-silico-technology-in-clinical-research","InSilicoTrials has collaborated effectively with Biofarma Group to harness the potential of in silico technology for clinical research. In this collaboration, InSilicoTrials utilized its expertise in computational modeling to analyze and reinterpret the clinical trial…",[2750],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2023-11-13T13:14:25.000Z",[2753],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fcollaboration-between-insilicotrials-and-biofarma-group-explores-the-benefits-of-in-silico-technology-in-clinical-research\u002F",{"id":2756,"alt":2757,"updatedAt":2758,"createdAt":2758,"url":2759,"thumbnailURL":74,"filename":2760,"mimeType":88,"filesize":2761,"width":2762,"height":2763,"focalX":92,"focalY":92,"sizes":2764},1117,"for article_","2026-05-25T08:04:49.882Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F32015.png","32015.png",13991896,8500,4000,{"thumbnail":2765,"card":2766},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":2768},{"type":99,"format":9,"indent":100,"version":4,"children":2769},[2770,2786,2800,2810,2824,2831,2838],{"type":103,"format":9,"indent":100,"version":4,"children":2771},[2772,2776,2778,2784],{"url":2656,"type":411,"fields":2773,"version":4,"children":2774},{"url":2656,"newTab":78,"linkType":414},[2775],{"text":72,"type":109,"format":140,"version":4},{"text":2777,"type":109,"format":140,"version":4}," has collaborated effectively with ",{"url":2779,"type":411,"fields":2780,"version":4,"children":2781},"https:\u002F\u002Fwww.biofarmagroup.it",{"url":2779,"newTab":78,"linkType":414},[2782],{"text":2783,"type":109,"format":140,"version":4},"Biofarma Group",{"text":2785,"type":109,"format":140,"version":4}," to harness the potential of in silico technology for clinical research. In this collaboration, InSilicoTrials utilized its expertise in computational modeling to analyze and reinterpret the clinical trial data of Epatrex, Biofarma Group's dietary supplement for non-alcoholic fatty liver disease, thereby offering insights to enhance its development and efficacy evaluation.",{"type":103,"format":9,"indent":100,"version":4,"children":2787},[2788,2792,2794,2795,2797,2798],{"url":2779,"type":411,"fields":2789,"version":4,"children":2790},{"url":2779,"newTab":78,"linkType":414},[2791],{"text":2783,"type":109,"format":100,"version":4},{"text":2793,"type":109,"format":100,"version":4},", a company at the forefront of innovation, has embraced ",{"text":1089,"type":109,"format":140,"version":4},{"text":2796,"type":109,"format":100,"version":4}," technology to optimize the development of their products. ",{"text":1079,"type":109,"format":140,"version":4},{"text":2799,"type":109,"format":100,"version":4}," trials involve creating computer models using algorithms that can predict clinical outcomes without the need for traditional in vivo or in vitro experimentation. This technology is becoming increasingly vital in the pharmaceutical field for forecasting the safety, efficacy, and optimal dosing strategies of new formulations, and for guiding clinical trial designs.",{"type":103,"format":9,"indent":100,"version":4,"children":2801},[2802,2804,2805,2807,2808],{"text":2803,"type":109,"format":100,"version":4},"A distinct advantage of ",{"text":1089,"type":109,"format":140,"version":4},{"text":2806,"type":109,"format":100,"version":4}," trials over conventional studies is the insight they provide into why a product might fail during clinical testing. Traditional trials may indicate inefficacy or safety concerns without suggesting how to rectify these issues, potentially leading to the abandonment of otherwise promising products. This can hinder innovation and inflate development costs. In contrast, ",{"text":1089,"type":109,"format":140,"version":4},{"text":2809,"type":109,"format":100,"version":4}," analysis can help refine a product to meet clinical testing standards successfully.",{"type":103,"format":9,"indent":100,"version":4,"children":2811},[2812,2813,2815,2816,2818,2819,2821,2822],{"text":72,"type":109,"format":4,"version":4},{"text":2814,"type":109,"format":100,"version":4}," and ",{"text":2783,"type":109,"format":4,"version":4},{"text":2817,"type":109,"format":100,"version":4}," tested the innovative edge of ",{"text":1089,"type":109,"format":140,"version":4},{"text":2820,"type":109,"format":100,"version":4}," trials with Epatrex, a dietary supplement designed to support individuals with non-alcoholic fatty liver disease (NAFLD). The application of ",{"text":1089,"type":109,"format":140,"version":4},{"text":2823,"type":109,"format":100,"version":4}," trials to the nutraceutical field is relatively novel and has the potential to enhance the effectiveness of innovation and new product development processes.",{"type":103,"format":9,"indent":100,"version":4,"children":2825},[2826,2828,2829],{"text":2827,"type":109,"format":100,"version":4},"The clinical validation of Epatrex involved a two-phase process. The initial phase, a multicenter clinical trial, established the safety of Epatrex but did not show statistically significant effects on markers of liver inflammation when compared to a placebo. The second phase utilized ",{"text":1089,"type":109,"format":140,"version":4},{"text":2830,"type":109,"format":100,"version":4}," methodology to further analyze and reinterpret data from the first trial, which provided new insights, particularly into the Hamaguchi score, which measures the severity of fatty liver disease.",{"type":103,"format":9,"indent":100,"version":4,"children":2832},[2833,2835,2836],{"text":2834,"type":109,"format":100,"version":4},"This ",{"text":1089,"type":109,"format":140,"version":4},{"text":2837,"type":109,"format":100,"version":4}," analysis also considered patient-specific characteristics and the study design, leading to recommendations for future clinical trials. Although the placebo effect seemed to obscure the efficacy of Epatrex initially, a significant association was found between treatment duration and changes in the Hamaguchi score. Moreover, the analysis suggested a stronger effect of Epatrex in patients with higher waist circumference, indicating potential for targeted treatment strategies.",{"type":103,"format":9,"indent":100,"version":4,"children":2839},[2840,2842,2843,2845,2846],{"text":2841,"type":109,"format":100,"version":4},"In conclusion, the ",{"text":1089,"type":109,"format":140,"version":4},{"text":2844,"type":109,"format":100,"version":4}," trial with InSilicoTrials offered valuable directions for enhancing clinical study designs and marked a step towards a mechanistic understanding of Epatrex's effects on NAFLD. The insights gained from this collaborative effort demonstrate the practical applications of ",{"text":1089,"type":109,"format":140,"version":4},{"text":2847,"type":109,"format":100,"version":4}," technology in advancing nutraceutical research and development.","2026-05-25T08:07:07.466Z","2026-05-25T07:52:17.283Z",{"id":2851,"title":2484,"slug":2852,"excerpt":2486,"authors":2853,"reviewedBy":74,"publishedAt":2855,"tags":2856,"gated":78,"businessEmailRequired":78,"legacyUrl":2858,"template":352,"heroImage":74,"intro":74,"lede":74,"citationId":74,"body":2859,"updatedAt":2920,"createdAt":2920,"_status":335},31,"cutting-edge-big-data-initiative-seeks-to-provide-crucial-support-to-people-affected-by-amyotrophic-lateral-sclerosis-and-multiple-sclerosis",[2854],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2023-10-04T10:57:18.000Z",[2857],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Fcutting-edge-big-data-initiative-seeks-to-provide-crucial-support-to-people-affected-by-amyotrophic-lateral-sclerosis-and-multiple-sclerosis\u002F",{"root":2860},{"type":99,"format":9,"indent":100,"version":4,"children":2861},[2862,2875,2878,2881,2884,2887,2890,2893,2896,2899,2902,2905,2908,2912],{"type":103,"format":9,"indent":100,"version":4,"children":2863},[2864,2865,2869,2870,2874],{"text":2511,"type":109,"format":100,"version":4},{"url":2513,"type":411,"fields":2866,"version":4,"children":2867},{"url":2513,"newTab":78,"linkType":414},[2868],{"text":2517,"type":109,"format":100,"version":4},{"text":2519,"type":109,"format":100,"version":4},{"url":2521,"type":411,"fields":2871,"version":4,"children":2872},{"url":2521,"newTab":78,"linkType":414},[2873],{"text":2525,"type":109,"format":100,"version":4},{"text":451,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2876},[2877],{"text":2530,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2879},[2880],{"text":2534,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2882},[2883],{"text":2538,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2885},[2886],{"text":2542,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2888},[2889],{"text":2546,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2891},[2892],{"text":2550,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2894},[2895],{"text":2554,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2897},[2898],{"text":2558,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2900},[2901],{"text":2562,"type":109,"format":100,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2903},[2904],{"text":2566,"type":109,"format":4,"version":4},{"type":103,"format":9,"indent":100,"version":4,"children":2906},[2907],{"text":2570,"type":109,"format":100,"version":4},{"tag":1349,"type":544,"format":9,"indent":100,"version":4,"children":2909},[2910],{"text":2911,"type":109,"format":100,"version":4},"OUR NEWSLETTER",{"type":103,"format":9,"indent":100,"version":4,"children":2913},[2914],{"url":2915,"type":411,"fields":2916,"version":4,"children":2917},"https:\u002F\u002Fbrainteaser.health\u002Fnews\u002Fcutting-edge-big-data-initiative-seeks-to-provide-crucial-support-to-people-affected-by-amyotrophic-lateral-sclerosis-and-multiple-sclerosis\u002F#",{"url":2915,"newTab":78,"linkType":414},[2918],{"text":2919,"type":109,"format":100,"version":4},"SUBSCRIBE","2026-05-25T07:42:52.348Z",{"id":2922,"title":2923,"slug":2924,"excerpt":2925,"authors":2926,"reviewedBy":74,"publishedAt":2928,"tags":2929,"gated":78,"businessEmailRequired":78,"legacyUrl":2931,"template":352,"heroImage":2932,"intro":74,"lede":74,"citationId":74,"body":2944,"updatedAt":3033,"createdAt":3034,"_status":335},52,"Transforming Fracture Risk Assessment for Cancer Patients with Vertebral Metastases","transforming-fracture-risk-assessment-for-cancer-patients-with-vertebral-metastases","Cutting-edge EU-funded project METASTRA unites an interdisciplinary team of experts to spearhead a transformative approach to revolutionize fracture risk assessment and personalized treatment for cancer patients with vertebral metastases. A groundbreaking initiative,…",[2927],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2023-08-19T14:02:51.000Z",[2930],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Ftransforming-fracture-risk-assessment-for-cancer-patients-with-vertebral-metastases\u002F",{"id":2933,"alt":2934,"updatedAt":2935,"createdAt":2935,"url":2936,"thumbnailURL":74,"filename":2937,"mimeType":88,"filesize":2938,"width":2939,"height":2940,"focalX":92,"focalY":92,"sizes":2941},1103,"Metastra_logo_final","2026-05-25T08:04:45.751Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F29212.png","29212.png",81947,4001,2251,{"thumbnail":2942,"card":2943},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":2945},{"type":99,"format":9,"indent":100,"version":4,"children":2946},[2947,2955,2967,2971,2975,2979,2987,2995,3001,3005],{"type":103,"format":9,"indent":100,"version":4,"children":2948},[2949,2951,2953],{"text":2950,"type":109,"format":140,"version":4},"Cutting-edge EU-funded project ",{"text":2952,"type":109,"format":145,"version":4},"METASTRA",{"text":2954,"type":109,"format":140,"version":4}," unites an interdisciplinary team of experts to spearhead a transformative approach to revolutionize fracture risk assessment and personalized treatment for cancer patients with vertebral metastases.",{"type":103,"format":9,"indent":100,"version":4,"children":2956},[2957,2959,2961,2963,2965],{"text":2958,"type":109,"format":100,"version":4}," A groundbreaking initiative, ",{"text":2960,"type":109,"format":4,"version":4},"METASTRA is set to transform the way clinicians assess fracture risk in cancer patients with vertebral metastases",{"text":2962,"type":109,"format":100,"version":4},". The ambitious project funded by the EU’s Horizon Europe “Tools and technologies for a healthy society„ Call promises to provide personalised treatment recommendations based on robust ",{"text":2964,"type":109,"format":4,"version":4},"computational models and improved patient stratification techniques",{"text":2966,"type":109,"format":100,"version":4},". Coordinated by the University of Bologna, METASTRA brings together 15 partners from different European Member States, receiving a total funding of 6.7 Mil EUR over the next five years. With an avid and visionary work plan, the international, multidisciplinary research team is poised to make a substantial impact on the lives of cancer patients and the healthcare system as a whole.",{"type":103,"format":9,"indent":100,"version":4,"children":2968},[2969],{"text":2970,"type":109,"format":100,"version":4},"As early diagnosis and improved care are improving life expectancy of cancer patients across Europe, approximately 2.7 million individuals, face an alarmingly high incidence of secondary tumors, affecting nearly 1 million people. Among these cases, bone metastases spread to the spine in 30-70% of instances, causing a significant reduction in the vertebrae's load-bearing capacity and leading to fractures in approximately 30% of patients. Currently, clinicians are left with two subjective options: either performing surgery to stabilize the spine or leaving the patient vulnerable to a high risk of fractures. Such decisions often result in either unnecessary surgeries or fractures that severely impact both the quality of life and ongoing cancer treatment.",{"type":103,"format":9,"indent":100,"version":4,"children":2972},[2973],{"text":2974,"type":109,"format":100,"version":4},"The existing standard-of-care relies on scoring systems based solely on radiographic images, with limited consideration for local biomechanics. As a consequence, these systems fail to provide accurate indications for surgery in around 60% of cases, leaving a critical need for improved risk quantification and patient stratification methods.",{"tag":1349,"type":544,"format":9,"indent":100,"version":4,"children":2976},[2977],{"text":2978,"type":109,"format":100,"version":4},"Innovative Computational Models for Personalised Cancer Therapies",{"type":103,"format":9,"indent":100,"version":4,"children":2980},[2981,2983,2985],{"text":2982,"type":109,"format":100,"version":4},"METASTRA will address this unmet need by ",{"text":2984,"type":109,"format":4,"version":4},"developing innovative Artificial Intelligence (AI) and Physiology-based (VPH) mechanical computational models",{"text":2986,"type":109,"format":100,"version":4},". These models will accurately stratify patients with spine metastasis who are at high risk of fractures and identify personalised surgical treatments. The project will extensively train the models using a comprehensive dataset comprising clinical data from 2000 retrospective cases and biomechanical data from 120 ex vivo specimens. Subsequently, the efficacy of the new approach will be evaluated through a multicentric prospective observational study involving 200 patients.",{"type":103,"format":9,"indent":100,"version":4,"children":2988},[2989,2991,2993],{"text":2990,"type":109,"format":100,"version":4},"To facilitate clinical decision-making, the project will ",{"text":2992,"type":109,"format":4,"version":4},"integrate the computational models into a user-friendly Decision Support System (DSS)",{"text":2994,"type":109,"format":100,"version":4}," tailored to meet regulatory requirements and future commercialization opportunities. METASTRA's innovative guidelines for patient stratification and management are expected to significantly reduce uncertain diagnoses from the current 60% to a mere 20% of cases. This breakthrough will alleviate patient suffering and potentially save up to 2.4 billion euros annually in healthcare expenditures.",{"type":103,"format":9,"indent":100,"version":4,"children":2996},[2997,2999],{"text":2998,"type":109,"format":100,"version":4},"Professor Luca Cristofolini (from University of Bologna, Italy), the coordinator of the METASTRA project, expressed his enthusiasm for this groundbreaking endeavor: ",{"text":3000,"type":109,"format":140,"version":4},"“We stand on the cusp of a groundbreaking revolution in fracture risk stratification for cancer patients with vertebral metastases. METASTRA is poised to transcend the limitations of current subjective approaches by harnessing the power of advanced computational models and clinical validation. This project holds the potential to reshape the landscape of patient care, sparing individuals from unnecessary surgeries and fractures that impact their well-being and treatment outcomes. With METASTRA, we strive to empower clinicians with precise, personalized strategies, ultimately elevating the quality of life for countless patients and transforming the future of cancer management.",{"type":103,"format":9,"indent":100,"version":4,"children":3002},[3003],{"text":3004,"type":109,"format":140,"version":4},"We are thrilled to be part of this exceptional collaboration, bringing together leading institutions and experts from across Europe. Our collective efforts and expertise will drive transformative advancements in personalized medicine, revolutionizing the way we treat cancer patients with vertebral metastases. We look forward to working collaboratively to achieve our shared goals and make a significant impact on patient care.” ",{"type":103,"format":9,"indent":100,"version":4,"children":3006},[3007,3009,3015,3017,3023,3025,3031],{"text":3008,"type":109,"format":100,"version":4},"For more information about the METASTRA project, please visit ",{"url":3010,"type":411,"fields":3011,"version":4,"children":3012},"https:\u002F\u002Fwww.metastraproject.eu\u002F",{"url":3010,"newTab":78,"linkType":414},[3013],{"text":3014,"type":109,"format":100,"version":4},"metastraproject.eu",{"text":3016,"type":109,"format":100,"version":4}," or follow the project on Twitter (",{"url":3018,"type":411,"fields":3019,"version":4,"children":3020},"https:\u002F\u002Ftwitter.com\u002FMetastraProject",{"url":3018,"newTab":78,"linkType":414},[3021],{"text":3022,"type":109,"format":100,"version":4},"@MetastraProject",{"text":3024,"type":109,"format":100,"version":4},") and LinkedIn (",{"url":3026,"type":411,"fields":3027,"version":4,"children":3028},"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fmetastra-eu\u002F",{"url":3026,"newTab":78,"linkType":414},[3029],{"text":3030,"type":109,"format":100,"version":4},"Metastra-eu",{"text":3032,"type":109,"format":100,"version":4},").","2026-05-25T08:07:07.424Z","2026-05-25T07:52:17.241Z",{"id":3036,"title":3037,"slug":3038,"excerpt":3039,"authors":3040,"reviewedBy":74,"publishedAt":3042,"tags":3043,"gated":78,"businessEmailRequired":78,"legacyUrl":3045,"template":352,"heroImage":3046,"intro":74,"lede":74,"citationId":74,"body":3057,"updatedAt":3145,"createdAt":3146,"_status":335},30,"Unleashing the IDPP@CLEF Potential: Assessing Predictive Algorithms and Enabling Data Sharing for Enhanced Research","unleashing-the-idppclef-potential-assessing-predictive-algorithms-and-enabling-data-sharing-for-enhanced-research","Each year, the BRAINTEASER project organizes an open evaluation challenge, called iDPP@CLEF (Intelligent Disease Progression Prediction), to involve research groups from academia and industry in the assessment of the performance of their AI algorithms to predict the…",[3041],{"id":4,"name":72,"role":73,"bio":74,"orcid":74,"photo":74,"updatedAt":75,"createdAt":75},"2023-08-18T08:39:14.000Z",[3044],{"id":4,"name":348,"slug":349,"updatedAt":350,"createdAt":350},"\u002Funleashing-the-idppclef-potential-assessing-predictive-algorithms-and-enabling-data-sharing-for-enhanced-research\u002F",{"id":3047,"alt":3048,"updatedAt":3049,"createdAt":3049,"url":3050,"thumbnailURL":74,"filename":3051,"mimeType":359,"filesize":3052,"width":3053,"height":2365,"focalX":92,"focalY":92,"sizes":3054},1101,"Brainteaser PR","2026-05-25T08:04:45.491Z","https:\u002F\u002Fcms.insilicotrials.com\u002Fapi\u002Fmedia\u002Ffile\u002F29172.jpg","29172.jpg",698226,1280,{"thumbnail":3055,"card":3056},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"url":74,"width":74,"height":74,"mimeType":74,"filesize":74,"filename":74},{"root":3058},{"type":99,"format":9,"indent":100,"version":4,"children":3059},[3060,3079,3087,3095,3103,3107,3122,3130],{"type":103,"format":9,"indent":100,"version":4,"children":3061},[3062,3064,3069,3071,3073,3075,3077],{"text":3063,"type":109,"format":100,"version":4},"Each year, the ",{"url":3065,"type":411,"fields":3066,"version":4,"children":3067},"https:\u002F\u002Fbrainteaser.health",{"url":3065,"newTab":78,"linkType":414},[3068],{"text":1771,"type":109,"format":100,"version":4},{"text":3070,"type":109,"format":100,"version":4}," project organizes an open evaluation challenge, called ",{"text":3072,"type":109,"format":4,"version":4},"iDPP@CLEF (Intelligent Disease Progression Prediction),",{"text":3074,"type":109,"format":100,"version":4}," to involve research groups from academia and industry in the assessment of the performance of their ",{"text":3076,"type":109,"format":4,"version":4},"AI algorithms to predict the progression of ALS and MS",{"text":3078,"type":109,"format":100,"version":4},". These challenges are open to anyone wishing to participate and they are built around real clinical and sensor data (properly anonymized), provided by the clinical partners in our consortium.",{"type":103,"format":9,"indent":100,"version":4,"children":3080},[3081,3083,3085],{"text":3082,"type":109,"format":100,"version":4},"The challenges represent a unique ",{"text":3084,"type":109,"format":4,"version":4},"opportunity for researchers to access highly curated data",{"text":3086,"type":109,"format":100,"version":4}," and discuss their own approaches with other researchers interested in the same topics. Indeed, since all the groups participating in a challenge operate on the same datasets, it is possible to directly contrast the performance of all the proposed approaches and solutions, in order to comparatively understand what works best and what does not work.",{"type":103,"format":9,"indent":100,"version":4,"children":3088},[3089,3091,3093],{"text":3090,"type":109,"format":100,"version":4},"Every year we organize a workshop at the end of the challenge, where participants can meet and discuss together face-to-face what they did, what worked and why. Moreover, peer-reviewed papers by participants, describing their approaches, and overview papers by organizers, summarizing the main findings of each edition, are published online in the CEUR-WS proceedings series, which grants free and open access to all of them. In this way, we ",{"text":3092,"type":109,"format":4,"version":4},"accelerate knowledge transfer and impact both inside and outside the project",{"text":3094,"type":109,"format":100,"version":4},", because the best-of-breed approaches are quickly shared with everyone interested in the research community, but also industry, policy makers, and even general public, if concerned. Least, but not last, the challenge helps in building a cohesive research community, allowing them to network and learn from each other, and lays the foundations for a durable impact in the field, also after the end of the project.",{"type":103,"format":9,"indent":100,"version":4,"children":3096},[3097,3099,3101],{"text":3098,"type":109,"format":100,"version":4},"This year, in the ",{"text":3100,"type":109,"format":4,"version":4},"iDPP@CLEF 2023 challenge",{"text":3102,"type":109,"format":100,"version":4},", we organized three tasks: two of them were focused on the progression of MS and one of them on the progression of ALS. The first task dealt with the prediction of MS worsening, according to clinical standards formulated on the EDSS (Expanded Disability Status Scale) score.",{"type":103,"format":9,"indent":100,"version":4,"children":3104},[3105],{"text":3106,"type":109,"format":100,"version":4},"The second task built on the first one and investigated the probability of MS worsening in a time window, say 2, 4, 6 or 8 years. The third task explored the impact of pollutants on the worsening of ALS and whether they were useful to predict time to PEG (Percutaneous Endoscopic Gastrostomy), NIV (Non-Invasive Ventilation), or death.",{"type":103,"format":9,"indent":100,"version":4,"children":3108},[3109,3111,3113,3114,3116,3118,3120],{"text":3110,"type":109,"format":4,"version":4},"Data and their quality",{"text":3112,"type":109,"format":100,"version":4}," are key concerns for ",{"text":1771,"type":109,"format":4,"version":4},{"text":3115,"type":109,"format":100,"version":4},", since both the predictive AI algorithms developed by the consortium and the open evaluation challenges revolve around them. To this end, ",{"text":3117,"type":109,"format":4,"version":4},"BRAINTEASER fully embraces the Open Science and FAIR (Findable, Accessible, Interoperable, Reusable)",{"text":3119,"type":109,"format":100,"version":4}," principles and puts lots of effort in curating the developed datasets. This happens through various means: we designed an ontology to semantically model the clinical and sensor data we work with and to ensure their correctness; when ingesting clinical and sensor data into the knowledge base informed by our ontology, we adopt strict cleaning and filtering procedures to ensure the correctness of the ingested instances; the training and test data we use internally and in the challenges are then derived from such highly curated knowledge base; and, finally, the challenges themselves represent a further validation of our datasets, since external research groups access the datasets and can verify that they are appropriate for ",{"text":3121,"type":109,"format":4,"version":4},"developing AI algorithms.",{"type":103,"format":9,"indent":100,"version":4,"children":3123},[3124,3126,3128],{"text":3125,"type":109,"format":100,"version":4},"Since data are the fuel of research, after all the above quality checks and curation steps, we release our datasets for free to anyone wishing to conduct further research by ",{"text":3127,"type":109,"format":4,"version":4},"sharing and integrating them in the European Open Science Cloud (EOSC) via Zenodo.",{"text":3129,"type":109,"format":100,"version":4}," However, we do not simply put our datasets out there in the wide but we share them in a responsible way. Indeed, we ask requesters to submit a project describing which use and what kind of inferences they plan to do with our data and a committee of experts (both medical doctors and computer scientists) verifies that the intended use of the data is up to high ethical, clinical, and scientific standards.",{"type":103,"format":9,"indent":100,"version":4,"children":3131},[3132,3134,3139,3141,3143],{"text":3133,"type":109,"format":100,"version":4},"Listen ",{"url":3135,"type":411,"fields":3136,"version":4,"children":3137},"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=EZJGMWAiMSI&feature=youtu.be",{"url":3135,"newTab":78,"linkType":414},[3138],{"text":929,"type":109,"format":100,"version":4},{"text":3140,"type":109,"format":100,"version":4}," to Nicola Ferro, Challenge organiser and full-time computer science professor (University of Padua - IT) to have more precious insights about this ",{"text":3142,"type":109,"format":4,"version":4},"BRAINTEASER initiative",{"text":3144,"type":109,"format":100,"version":4},"!","2026-05-25T08:07:07.386Z","2026-05-25T07:42:52.313Z",24,{"id":4,"siteTitle":72,"siteDescription":3149,"defaultOgImage":74,"footerCopy":3150,"featuredContent":3151,"updatedAt":3160,"createdAt":3161,"globalType":3162},"The simulation layer for drug development.","2017–2026 © InSilicoTrials Technologies. All rights reserved. · Made with ❤️ by the IST Dev Team",[3152,3155,3158],{"id":3153,"contentType":3154,"article":74,"newsItem":4,"researchProject":74,"overrideImage":74},"6a2bd2c713e9177f31f09ae8","news",{"id":3156,"contentType":3157,"article":74,"newsItem":74,"researchProject":155,"overrideImage":74},"6a2bd2d113e9177f31f09aea","research-projects",{"id":3159,"contentType":3154,"article":74,"newsItem":140,"researchProject":74,"overrideImage":74},"6a2bd57e13e9177f31f09aec","2026-06-19T08:57:09.309Z","2026-06-12T09:35:23.693Z","settings"]