Why India Needs Indigenous AI Models for Its Genomic Future

AI in healthcare is only as good as the data it learns from. But here’s the catch: most global AI models in genomics are trained on Western datasets that barely represent 1% of India’s genetic diversity. For a country as diverse as ours, that’s a problem with serious consequences.

Imported Models ≠ Indian Reality

Using Western-trained AI models in India often leads to:

• Misdiagnosis
• Wrong risk predictions
• Ineffective drug response
• Wider health disparities

India is not one uniform population—it’s a mosaic of thousands of genetically distinct groups, shaped by history, culture, and geography. Healthcare AI must reflect this richness.

Why Genomic Variation Matters

• Indians develop diabetes, cardiovascular disease, and cancers earlier and at lower BMIs than Western populations.
• Drug response is also different—for instance, clopidogrel resistance and altered statin metabolism are common here.
• Without Indian genomic data, AI models can’t account for these unique patterns.

India’s Efforts: Building the Right Foundation

Several initiatives are already paving the way for India-specific genomic intelligence:

• Indian Genome Variation Consortium (IGVC) → Population-specific variants mapped.
• CSIR-IndiGen → Sequenced Indian genomes for drug response insights.
• GenomeIndia Project → 10,000 genomes planned for sequencing.
• RICH Biobank (Telangana) → AI-ready datasets combining clinical + lifestyle data.
• Phenome India National Biobank (2025) → Collecting genomic + lifestyle + clinical data from 10,000 Indians across all regions and communities.



Together, these are creating the training datasets AI needs to be accurate for Indian patients.

What Indigenous AI Models Can Deliver

With India-specific genomic intelligence, AI can:

• Predict risk of diseases like diabetes, breast cancer, thalassemia more accurately.
• Personalize drug dosing through pharmacogenomics.
• Diagnose rare diseases unique to Indian subpopulations.
• Enable public health tools that target local communities.

Beyond Science: It’s About Health Sovereignty

If India depends only on Western AI models, we risk importing irrelevant or harmful healthcare solutions. Building our own genomic intelligence ensures:

• Better accuracy for Indian patients
• Global competitiveness in healthcare AI
• Health sovereignty for the world’s most diverse population



The Bottom Line

If AI is the engine of personalized medicine, then genomics is its fuel. For India, that fuel must come from our own people—not borrowed datasets from the West.

Building indigenous AI models isn’t a luxury. It’s the only way to deliver trustworthy, inclusive, and effective healthcare for 1.4 billion Indians.