Critical Path Disease Modeling Coalition

Drug development decisions depend on understanding how a disease changes over time, why patients differ and how they respond to treatment. Yet relevant data are often dispersed across clinical trials, registries and routine care, and collected using different standards, making them difficult to combine and reuse across development programs. 

This fragmentation can leave avoidable uncertainty around endpoint selection, eligibility criteria, trial duration, sample size and dose selection; complicating trial design and the generation of evidence needed for regulatory decisions. 

International guidelines, including ICH E11A Pediatric Extrapolation and ICH M15 General Principles for Model-Informed Drug Development, provide harmonized frameworks for pediatric extrapolation and model-informed drug development. Translating these principles into practice requires disease-specific data, transparent methods, clearly defined contexts of use and early alignment among those who develop, evaluate and use the tools. 

 CP-DMC can combine the C-Path five core competencies: Regulatory & Development Science; Data Collaboration, Management & Standards; Modeling, Analytics & Quantitative Medicine; Translational Science; and Clinical Outcome Assessments & Patient-Centered Evidence. Together these capabilities provide a neutral, precompetitive environment where organizations bring together data, scientific expertise and patient perspectives. Projects are developed in collaboration with scientific societies and patient communities to address shared drug development challenges and create reusable quantitative models and tools. 

Each project begins with a clearly defined development need and context of use, guiding the data strategy, modeling approach, evaluation and regulatory engagement. This structured approach connects scientific innovation with the evidence needed to support its intended application. 

The resulting tools are intended to support evidence generation, trial design and regulatory decision-making; not to replace product-specific regulatory review, independent regulatory decisions or individual clinical judgment. 

Learn more: 

• Brumfield MA, Higson GC, Ollivier C, Seigneuret N. Delivering regulatory impact from consortium-based projects. Nat Rev Drug Discov. 2025;24(12):889-890. doi: 10.1038/d41573-025-00098-8. 
• Bauer AM, Huynh H, Stamm K, Sullivan B, Heavner S, Martinez T, et al. Regulatory Science Framework of Drug Development Tools. Version 2.0. Critical Path Institute; 2025. 

CP-DMC aims to transform fragmented evidence into reusable quantitative models, tools and knowledge. These resources can help sponsors and researchers test assumptions before a trial begins, compare trial-design options, make more efficient use of existing data, focus new data collection on unresolved questions, and reuse methods and insights across development programs. 

Over time, this approach has the potential to reduce avoidable trial burden, improve the predictability and quality of evidence generation, strengthen pediatric extrapolation strategies, and support more efficient drug development; ultimately contributing to faster access to better therapies, particularly for children and people living with rare or chronic diseases. 

• CP-DMC’s publicly launched proof-of-concept project focuses on pediatric Crohn’s disease and ulcerative colitis, where children have historically experienced substantial delays in accessing innovative therapies compared with adults. Growing scientific and regulatory consensus supports greater use of pediatric extrapolation and quantitative approaches to reduce unnecessary duplication of evidence generation.
• CP-DMC aims to develop disease-progression and clinical-trial simulation tools integrating longitudinal clinical trial and real-world data. These tools will be used to characterize disease trajectories and treatment response, quantify uncertainty when extrapolating evidence from adults to children, and explore more efficient pediatric trial-design options.
• The goal is to translate frameworks such as ICH E11A Pediatric Extrapolation into practical, decision-relevant tools that help determine what evidence can be extrapolated and what additional pediatric evidence is still needed across mechanisms of action.

Learn more:  

• Turner D, Assa A, Malham M, Yuval Bar-Asher S, Rayan C, Hyams JS, et al. Reshaping study design for faster extrapolation-based drug approval in pediatric inflammatory bowel diseases: an ESPGHAN-NASPGHAN position paper. J Pediatr Gastroenterol Nutr. 2026;82(3):867-894. doi: 10.1002/jpn3.70275. 

• European Medicines Agency. Concept paper on a paediatric update on the Guideline on the development of new medicinal products for the treatment of Ulcerative Colitis. European Medicines Agency; 2025. EMA/CHMP/312843/2025. 

• U.S. Food and Drug Administration. Pediatric Inflammatory Bowel Disease: Developing Drugs for Treatment. Guidance for Industry. Draft Guidance. U.S. Food and Drug Administration, Center for Drug Evaluation and Research; 2024. 

• Croft NM, de Ridder L, Griffiths AM, Hyams JS, Ruemmele FM, Turner D, et al. Paediatric inflammatory bowel disease: a multi-stakeholder perspective to improve development of drugs for children and adolescents. J Crohns Colitis. 2023;17(2):249-258. doi: 10.1093/ecco-jcc/jjac135. 

Pediatric CKD presents particular drug development challenges because patient populations are small and heterogeneous, disease progression can be slow and variable, and clinically meaningful outcomes may take years to occur. 

CP-DMC will explore how pediatric and relevant adult evidence can be combined to better characterize disease progression, identify patients at greater risk of progression, and evaluate meaningful outcomes and biomarkers. Quantitative approaches may support pediatric extrapolation, population enrichment, endpoint evaluation and clinical trial simulation, depending on the available data and intended context of use. 

This priority area is being developed in collaboration with C-Path’s Polycystic Kidney Disease Outcomes Consortium (PKDOC), allowing the project to build on an established kidney-disease community, existing regulatory-science expertise, longitudinal data resources, biomarker experience and past clinical trial simulation activities. PKDOC has previously supported the qualification of Total Kidney Volume as a prognostic enrichment biomarker and continues to advance biomarker, modeling, simulation and patient-centered outcome work in PKD. 

By connecting this existing foundation with CP-DMC’s broader pediatric and model-informed development framework, the pilot can benefit from accumulated knowledge, established stakeholder relationships and ongoing scientific work, while extending these capabilities toward broader pediatric CKD questions. 

The goal is to develop reusable tools that help sponsors and researchers determine which patients to study, which outcomes are most informative and how trials can be designed more efficiently, while making the best possible use of existing evidence. 

Learn more: 

• Oni L, Smoyer WE, Denburg M, Bjornstad P, Tarnoff J, Lim MD, et al. The use of extrapolation to promote clinical trials in pediatric nephrology. J Am Soc Nephrol. 2026;37(3):616-618. doi: 10.1681/ASN.0000000888. 

• Oni L, McKenzie J, Seide S, Smoyer WE, Trachtman H. Clinical trial end points for childhood CKD. J Am Soc Nephrol. 2025;36(6):1204-1207. doi: 10.1681/ASN.0000000701. 

• Greenberg JH, Abraham AG, Xu Y, Schelling JR, Coca SG, Schrauben SJ, et al. Biomarker panels for discriminating risk of CKD progression in children. J Am Soc Nephrol. 2025;36(6):1105-1115. doi: 10.1681/ASN.0000000602. 

• Khawandi J, Rao V, Rayner DG, Girimaji N, Azzam M, Hamarsha Q, et al. Serum and urine prognostic biomarkers for autosomal dominant polycystic kidney disease: a systematic review and meta-analysis. BMC Nephrol. 2026;27:459. doi: 10.1186/s12882-026-05056-z. 

• Park PG, Kim J, Choi N, Kim JH, Lim SH, Lee JH, et al. Cross-population validation of the pediatric CKD risk-prediction tool. Kidney Int Rep. 2026;11(5):106373. doi: 10.1016/j.ekir.2026.106373. 

CP-DMC will continue to expand its pediatric portfolio to disease areas where quantitative approaches could address important evidence-generation challenges. Rare epilepsies are one such priority area, where the coalition plans to explore approaches to patient stratification, characterization of disease variability and prediction of treatment response, drawing on fit-for-purpose registry, clinical trial and real-world data.

At the same time, CP-DMC is being designed as a scalable disease-modeling platform rather than a pediatric-only initiative. Opportunities beyond pediatrics are currently being explored in areas such as oncology and brain health, where disease heterogeneity, fragmented evidence and complex development pathways may similarly benefit from shared quantitative frameworks and reusable modeling tools.

Future projects, whether pediatric or adult, will be prioritized based on the importance of the drug development need, scientific and clinical relevance, availability and fitness of data, potential regulatory value, patient relevance, technical feasibility, opportunities for collaboration and long-term sustainability.

A quantitative disease model is a numerical representation of how a disease, relevant outcomes and sources of variability change over time. Depending on its context of use, it can help explore treatment effects, trial designs, endpoints or evidence from different populations.

“Regulatory-grade” describes an intended development standard: a defined context of use, traceable data and assumptions, evaluation commensurate with model risk, stated uncertainty and limitations, and reproducible methods. It is not a formal evidence of qualification, endorsement or acceptance unless a specific authority and milestone are named and cited.

Data use is governed through project-specific agreements and applicable privacy, security and legal requirements. C-Path’s Data Collaboration supports secure data curation, standardization, sharing and analysis. Patient-level data access is governed by the applicable Data Contribution Agreement (DCA); project participation alone does not grant access. Access to data is driven by the governance outlined within the relevant DCA(s) and subject to the specific analysis use-case requirements.

No. CP-DMC’s initial tools focus on drug development, trial design and evidence generation. Any future clinical use would require a separate evaluation and validation of that specific context of use.

• Quinten Health
• European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN),
• Crohn’s & Colitis Foundation
• ImproveCareNow
• European Rare Kidney Disease Reference Network (ERKNet)