Duchenne Regulatory Science Consortium (DRSC)

The Duchenne Regulatory Science Consortium (D-RSC), created by the Critical Path Institute (C-Path) was started in late 2015 as regulators, academics, and sponsors came together and realized that the process of drug development in Duchenne needed a new model. An analogy is the aerospace industry, where millions and millions of data points from previous successful and failed rocket launches are used to design rockets and launches. Nowadays, a computer designs the entire process before a rocket is built and a launch is attempted in reality. This is what D-RSC was setting off to do – using data points from natural history and placebo arm data, design disease progression models that could describe how defined groups of patients with Duchenne would progress over time, and how a treatment might impact that trajectory. In its first couple of years, it gathered industry and academic partners, as well as acquired data sets.


The goal of D-RSC is to develop regulatory ready tools to accelerate clinical trials for new drugs to treat Duchenne. Specifically, D-RSC will develop:

  • A Duchenne Therapeutic Area User Guide, which describes how Duchenne data should be entered into databases in the CDISC structure (see “First Steps” below) which is required for FDA submissions. This was completed in September of 2017.
  • An integrated database of clinical data describing progression of Duchenne. This consists of data shared with the consortium from natural history studies, clinical trials (placebo arms) clinical data collections, and registries. A portion of this data has been shared with D-RSC in such a way that this data may be made available to others.  The total database now contains nine datasets.
  • A clinical trial simulation platform, created from a series of disease progression models. These models are derived from the data in the database. This platform will allow clinical trial sponsors to forecast changes in clinically-meaningful endpoints, which would inform clinical trial protocol development with respect to inclusion criteria, endpoints, as well as the size and length and statistical analysis of clinical trials
  • D-RSC is working with another C-Path Consortium (the Predictive Safety Testing Consortium, PSTC) to qualify glutamate dehydrogenase as a liver safety biomarker in patients with underlying muscle disease, to be used in conjunction with existing liver safety biomarkers. D-RSC and PSTC received a formal Letter of Support from EMA for this biomarker in 2017.

C-Path will seek regulatory endorsement for tools developed by the consortium from both the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA).

First Steps

As D-RSC gathered data sets to use in its analysis, we didn’t want to evaluate data set by data set, but wanted to aggregate the data into a large dataset with as much data as possible. But, how is this done? Each dataset acquired seemed to record endpoint measures in a different way, and have different definitions. CDISC is a “universal language” if you will, that allows communication between datasets. Much like you insert your ATM card into a bank that is not your own, technical standards have been decided on and used to allow communication between banks. This is what CDISC does for datasets. So D-RSCs first step with any dataset that it brings in house is to translate it into the CDISC language so that it can talk to the other datasets and be included in the large overall aggregate dataset.

Progress to Date

D-RSC just had its third Annual Meeting in Washington, D.C. in March 2018 where all stakeholders (companies, academics, clinicians, patient groups, and government advisors) came together to discuss progress and plans. A context of use statement, a guiding framework that will drive the clinical trial simulation platform was presented and discussed. The group determined the various models that would be built to form the overall clinical trial simulation platform, and details of how the data need to be analyzed. D-RSC laid out a timeline to develop the various models and to seek endorsement from FDA and EMA. If successful in getting endorsement, the platform will be able to be used by drug sponsors for developing clinical trial protocols without need to justify the model to the authorities and will help sponsors to develop effective clinical trials that will give definitive answers on whether a drug works or not in less time and/or with fewer patients than previously needed.

D-RSC has also: