Sanofi Genzyme sponsors and operates four rare disease registries, including a global 20-year study of patients with Gaucher disease, the largest data set ever collected on this disease.
Sanofi Genzyme’s registries are industry models in both design and execution of long-term observational studies. They play a critical role in advancing the global understanding of disease, analyzing treatment outcomes over time, and fulfilling regulatory requirements related to life-threatening genetic diseases.
Serving as the primary partner for Sanofi Genzyme, DIFZ took a leadership role in the end-to-end design and construction of the RegistryNXT! Platform.
In replacing its aging data collection system, the Sanofi Genzyme/DIFZ team needed to address a complex set of challenges, specifically:
- Provide a single data collection system to capture data for all four registries to improve cross-registry analysis.
- Ensure accurate migration of all legacy data.
- Improve the registry value and reporting capabilities for participating physicians and nurses.
- Adopt the use of standards defined by the Clinical Data Interchange Standards Consortium (CDISC) to allow advanced electronic interchange of clinical data.
RegistryNXT!, implemented using the N of 1 Health Research Platform, is an innovative solution that includes:
- Fully integrated portal providing single sign-on access to data collection tools and analytical graphs and reports.
- Integration with Medidata’s RAVE, the leading clinical trial data collection application.
- Real-time data interchange using CDISC standards.
- Role-based disease management for patients, physicians, and nurses.
- Reporting functionalities for sites, registry staff, and Sanofi Genzyme regulatory reports.
- A production system based on the CDISC BRIDG model for health care and clinical trial data.
The platform of registries gives physicians the ability to share and retrieve data in a quick, secure, and seamless manner. These capabilities result in better decisions for patient treatment and better quality long-term research data.