The Critical Path for Sickle Cell Disease (CP-SCD) is a collaboration set up to develop community consensus on how to optimize and accelerate drug development for this rare disease. Sickle cell disease affects between 90,000 and 100,000 people in the U.S., and millions more around the world. The disease is caused by genetic mutations that cause red blood cells to become deformed, or sickled, which results in anemia, recurrent pain, organ damage and early death. Limited treatments are available at this time, but the first sickle cell therapies were recently approved by the U.S. Food and Drug Administration.

The mission of the CP-SCD is to support collaborative development and regulatory endorsement of new medical product development tools. These tools will help to optimize and de-risk clinical trials to increase the efficiency in developing and delivering safe, effective treatments for people living with sickle cell disease. Sickle cell disease research has been limited for some time, but recent interest in the disease and novel technologies has resulted in many potential therapeutics in development, as well as the first drug approvals. However, the path to regulatory approval of these new therapeutics is challenged by limited understanding of the natural history of the disease and how to measure therapeutic effects. CP-SCD has been set up to drive community understanding of these issues, and to develop tools to overcome them. The goals of the consortium are to:

1. Establish an international forum that engages regulatory agencies around the globe to identify and address regulatory issues that impact the development and approval of new therapies for sickle cell disease.
2. Identify potential drug development tools, such as clinical trial simulators, patient-reported outcome measures and other clinical outcome assessments (“COAs”), safety and efficacy biomarkers for use in clinical trials, and seek to obtain regulatory endorsement for the use of these solutions based on a specific context of use.
3. Develop new trial designs with optimal features (e.g., entry criteria, enrichment strategies, endpoint selection, sample size and power estimations, adaptation features, optimized control arms, etc.), based on model-informed drug development (“MIDD”) platforms.
4. Standardize data collection, including developing CDISC data standards as needed and designing master protocols.