Disease Progression Models of Six Endpoints and the Development of a Regulatory -Ready Clinical Trial Simulation Tool for Duchenne Muscular Dystrophy.


Real World Data - Disease registries, natural history, post marketing surveillance

Poster Number: 158


Jane Larkindale, Dphil, Sarah Kim, PhD, Karthik Lingineni, Stephan Schmidt, PhD, F.C.P., Diane Corey, Abby Bronson, MBA, Klaus Romero


2. University of Florida, 3. University of Florida, 4. University of Florida, 5. Critical Path Institute, 6. PPMD, 7. Critical Path Institute

The Duchenne Regulatory Science Consortium (D-RSC) was formed in 2016 to address these issues. Working with clinicians, companies, patients and patient advocates and the regulators, D-RSC has aggregated the largest available database of Duchenne clinical data (a total of 1,137 patients and 23,305 observations in the analysis dataset, nearly 5,000 patients in total) and is using those data to build a series of mathematical models of disease.

D-RSC has modeled the dynamics of change and sources of variability of six endpoints (velocities of time to stand from supine, time to climb 4 stairs, 10 m walk/run time, Northstar Ambulatory Assessment, Forced Vital Capacity and Brooke score). The models will be used to build a clinical trial simulation platform that will describe the trajectory of disease in patients from age 4 to end stage disease. The patient level data were divided randomly into training and test datasets in the ratio of 4:1, maintaining the consistency of balance in covariates. A non-linear mixed effects modeling approach was used to develop base and covariate models of each endpoint.

The final models capture the longitudinal changes in the endpoints adequately, including both the increase and decline phases. The models will be joined and used in clinical trial simulations to optimize selection of inclusion/exclusion criteria, endpoints and other trial parameters. The planned datasets, models and simulation tool have all been reviewed by both the US Food and Drug Administration and the European Medicines Authority and have been accepted into the Fit-for-Purpose and Qualification for Novel Methodologies pathways respectively. The platform will be submitted for potential endorsement by both agencies by mid-2020. The tools will be made publicly available through C-Path’s website.