India’s RWE Landscape — PvPI, DPDP Act, and the Data Gap

This module has covered global RWE infrastructure throughout, and it’s worth closing with a dedicated look at India specifically, given both this course’s audience and the genuinely distinctive challenges and opportunities India presents. The Indian patient population is large, ethnically and genetically diverse, carries a high combined burden of infectious and non-communicable disease comorbidity, uses both conventional and traditional medicine widely and often simultaneously, and has been substantially underrepresented in the global RWD infrastructure this module has otherwise described.

The current Indian RWE landscape has several concrete components worth knowing specifically. PvPI’s ADR database — the same national spontaneous reporting system Module 1 introduced — held over 1.5 million ICSRs as of 2025, linked directly to VigiBase, with an AI signal dashboard pilot now operational; it’s growing steadily but remains smaller than major Western spontaneous reporting databases. National Health Insurance Scheme (NHIS) and Central Government Health Scheme (CGHS) data provide exposure and claims data for covered populations, though genuine coverage gaps remain for India’s substantial informal-sector workforce. Major tertiary care hospitals — AIIMS, PGI, KEM among them — maintain electronic health record systems of variable data quality, with CDSCO’s National RWE Hub (Lesson 15.8) piloting a connection between selected hospital EHR systems and PvPI directly.

Two challenges deserve specific attention because they’re genuinely distinctive to the Indian context rather than universal RWE limitations. Traditional medicine use — ayurvedic, homeopathic, and herbal medicines used widely alongside prescription drugs — is rarely captured in structured electronic records at all, which means drug-herb interaction signals represent a genuinely important, under-addressed gap in Indian pharmacovigilance specifically, invisible to standard RWD infrastructure unless deliberate effort is made to capture it. And genetic diversity matters concretely, not just demographically: Indian populations carry distinct HLA profiles and CYP enzyme variants compared to the European populations that have historically dominated pharmacogenomic research, which means AI models trained predominantly on Western datasets — exactly the concern Lesson 15.10 flagged — can genuinely miss pharmacogenomic risk signals that are specifically relevant to Indian patients.

India’s Digital Personal Data Protection Act 2023 (DPDP Act) governs all processing of personal data, including patient health data, and any RWE research using Indian healthcare data has to establish a valid legal basis under it. The Act provides a public interest exception specifically for health research, but that exception requires real safeguards — institutional ethics committee approval, defined de-identification standards, data minimisation, and formal protocols for data access requests. For a marketing authorisation holder running a federated multi-database study that includes an Indian data source alongside European or US databases — an increasingly common scenario given Lesson 15.8’s federated network content — DPDP Act compliance has to be satisfied alongside GDPR and HIPAA simultaneously, not as an alternative to either.