Taking a leaf out of Amul’s textbook to help rare-disease patients

Rare disease patients can benefit from a data-driven approach, similar to how Amul has succeeded in the dairy industry, according to a new report. Patient data is crucial for developing new treatments for rare diseases, as it helps identify biomarkers, predict disease progression, and design effective clinical trials. However, conventional trials are impractical for rare diseases due to the limited number of eligible participants.

Patient registries and natural-history studies offer alternative data sources that can serve as external controls. By aggregating patient data, researchers can design better trials, identify suitable participants, and determine meaningful clinical endpoints, ultimately accelerating the development of treatments for rare diseases.

In India, a proposed "Patient Data Collective" (PDC) could serve as a cooperative framework to collect and manage patient data. Inspired by Amul's success, the PDC would operate as a central repository for patient information, with the option to share revenue with participating patients. The PDC would collaborate with patient advocacy groups, hospital records, Centres of Excellence for Rare Diseases, and other data repositories.

AI-based data analytics would ensure data protection and privacy, with patient consent being a prerequisite for data collection and analysis.

The Indian Council of Medical Research (ICMR) has already established a rare disease registry, collecting data from 19 specialized hospitals over the past five years. However, this resource is insufficient to represent the entire Indian population. Therefore, the PDC should adopt a flexible and inclusive approach to data collection, maintaining high ethical and legal standards. Leveraging existing public registries and engaging non-governmental organizations is essential for the success of this initiative.

Implementing the PDC will require the development of a secure digital health platform, which can be facilitated by India's Ayushman Bharat Digital Health Mission. This mission provides a foundation for a secure digital health locker, enabling the aggregation of scattered medical histories, genetic reports, and clinical notes. To further enhance the platform, generative AI can be employed to synthesize medical records and suggest possible diagnoses and treatment options.

By encouraging natural-history registries led by patient advocacy groups and funding longitudinal studies, the PDC can generate valuable real-world evidence datasets. Ultimately, the success of the PDC depends on government and philanthropic support for developing a robust platform with AI capabilities, ensuring strict governance and oversight.