AI-Driven Genomics to Power India’s Shift to Predictive, Personalised Medicine: Jitendra Singh

The Minister said India’s next priority is to transition AI in biotechnology from proof-of-concept research into scalable, industry-ready solutions through partnerships supported by BIRAC.

Artificial Intelligence-enabled gene sequencing is rapidly emerging as one of India’s most transformative scientific applications, with the potential to reshape healthcare through personalised prescriptions and predictive medicine, Union Minister for Science and Technology Dr. Jitendra Singh said.

Speaking on the sidelines of the ongoing AI Impact Summit, the Minister noted that some of the country’s most substantive and high-impact AI deployments are currently unfolding in genomics, supported by large-scale sequencing initiatives under the Department of Biotechnology (DBT).

“Our gene sequencing work is AI-driven. Tomorrow, when we move toward personalised prescriptions, they will be based on our gene studies facilitated by Artificial Intelligence,” Dr. Singh said, underscoring India’s transition from conventional treatment models toward precision healthcare.

From Standard Treatment to Precision Prescriptions

Dr. Singh said AI-facilitated genomics platforms will increasingly enable doctors to tailor treatments based on an individual’s genetic profile, moving India toward a future where medicine is predictive rather than reactive.

The Minister emphasised that DBT’s genomics ecosystem is positioning India to harness computational biology and big data to deliver targeted interventions, improve disease prevention and strengthen clinical decision-making.

Bio-AI Mulankur Hubs to Launch in 2026

In a major announcement, Dr. Singh said DBT, together with the Biotechnology Industry Research Assistance Council (BIRAC), will establish “Bio-AI Mulankur” hubs in 2026.

These hubs will function as integrated, closed-loop research platforms where:

• AI-based predictions• Laboratory validation• Genomics data analytics

operate within a unified framework.

The hubs will focus on frontier domains including:

• Genomics diagnostics• Biomolecular and therapeutic design• Synthetic biology• Ayurveda-based evidence research

The objective, he said, is to institutionalise AI as a core scientific engine within biotechnology rather than as a peripheral analytical tool.

The initiative aligns with the BioE3 Policy, aimed at strengthening high-performance biomanufacturing to drive economic growth, environmental sustainability and employment generation.

Accelerating TB Drug Resistance Detection

Highlighting real-world applications, Dr. Singh cited the Indian Tuberculosis Genomic Surveillance Consortium (InTGS), supported by DBT, where AI is being deployed to catalogue drug-resistance mutations in Mycobacterium tuberculosis.

AI-enabled whole-genome sequencing analysis has reduced confirmation timelines for drug resistance from weeks to days, enabling faster clinical response and strengthening public health surveillance.

Maternal Health Breakthroughs Under GARBH-Ini

In maternal and child health research, the GARBH-Ini programme has applied AI-driven ultrasound imaging and genomics tools to identify 66 genetic markers associated with preterm birth risk.

Dr. Singh said such initiatives demonstrate how AI-supported genomics can enable:

• Early risk prediction• Targeted interventions• Improved outcomes in maternal healthcare

The Minister added that similar AI-based risk models are being developed for cancer, diabetes and cardiovascular diseases.

National Genomics Infrastructure Strengthening Research Capacity

Dr. Singh highlighted the role of the National Genomics Core, established at:

• National Institute of Biomedical Genomics (NIBMG), Kalyani• Centre for DNA Fingerprinting and Diagnostics (CDFD), Hyderabad

These facilities provide high-throughput sequencing and big data analytics infrastructure essential for AI-led genomics research.

GenomeIndia Project Unlocking Disease-Linked Variants

Data generated under the GenomeIndia project, which maps India’s genetic diversity, is being analysed using AI and machine learning techniques to identify disease-associated variants and advance translational medicine.

The project is expected to play a foundational role in building population-scale predictive healthcare systems tailored to India’s diverse genetic landscape.

AI Expanding into Drug Target Discovery and Tumour Profiling

Referring to work under the Centre of Excellence in Genome Sciences and Predictive Medicine, Dr. Singh said researchers are applying computational prediction and AI-based structural analysis to identify potential drug targets for rheumatoid arthritis.

AI applications are also expanding into:

• Single-cell and spatial genomics for tumour microenvironment profiling

• Protein engineering

• Therapeutic molecule design

• Synthetic biology innovations

From Proof-of-Concept to Industry-Ready Biotech Solutions

The Minister said India’s next priority is to transition AI in biotechnology from proof-of-concept research into scalable, industry-ready solutions through partnerships supported by BIRAC.

Embedding AI across DBT’s genomics platforms, he said, will strengthen:

• Predictive healthcare

• Disease surveillance

• Advanced biomanufacturing

• India’s global biotechnology competitiveness

With AI-driven genomics at the centre of this transformation, India is positioning itself at the forefront of precision medicine and next-generation healthcare innovation.