Leading India's charge in AI-driven drug discovery – the Peptris story

Drug discovery is among the areas that scientists and global pharmaceutical companies alike are excited about, when it comes to the hope that artificial intelligence is going to be transformative.

AI holds out the promise of not only slashing the costs of seeing a new molecule from lab to pharmacy to patients, but also helping innovators advance new, safer and sustainable processes and make the dream of personalised medicine a reality.

For India, a country with deep expertise in generic drug manufacturing but limited presence in drug innovation, the opportunity is considerable. In our own portfolio, Peptris Technologies, a Bengaluru-based startup founded in 2019, is at the frontier of this transformation. Our investment in them in 2023 recognised India’s potential as a centre for computational approaches to drug development.

Generative AI is expected to create $60 billion to $110 billion in annual value in the pharmaceutical value chain. The global market for AI in pharmaceutical applications is projected to grow from about $2 billion in 2025 to $16.5 billion by 2034, expanding at a compound annual growth rate of 27 per cent. Within drug discovery specifically, the market was valued at nearly $7 billion in 2025 and expected to reach $16.5 billion by 2034, advancing at a CAGR of 10.1 per cent.

Traditionally, the median cost of R&D for a new drug was close to a $1 billion, America’s National Institutes of Health found in one study. And a new drug can take 10-15 years from initial discovery to final approved medicine. And often companies focus on diseases that offer the most potential for recovering their costs and making substantial profits, and not necessarily on those that are most in need of innovative solutions.

Peptris has developed pepAI, a computational platform designed to accelerate compound screening and molecular design. The system predicts how molecules will behave, identify potential drug targets, and simulate late-stage clinical failures before they occur — processes that traditionally require years of wet-lab work.

The platform operates across multiple disease areas. Peptris is currently advancing projects in oncology and inflammation, focusing on testing novel compounds for drug development. Separately, it is pursuing drug repurposing initiatives to identify existing approved medications that could treat rare diseases. One such project targets Duchenne muscular dystrophy (DMD), a severe genetic condition affecting approximately one in 3,500 male births.

In March last year, Peptris became the first company in India to license out a molecule discovered via an AI-led platform. Peptris’ preclinical-stage asset, PEPR124 (RT001), has been licensed to Revio Therapeutics for further development, which could eventually lead to a drug to treat DMD.

The founders bring substantial credibility to the venture. Shridhar Narayanan, the company's chief scientific advisor, has contributed to eighteen clinical drug candidates across various therapeutic areas and is a co-inventor of Enmetazobactam, a novel antibiotic in clinical development. Narayanan Venkatasubramanian, Amit Mahajan and Anand Budni, bring deep expertise in computer science and engineering.

This background anchors the startup's work in the realities of pharmaceutical development rather than theoretical applications.

Peptris exemplifies a broader trend. India possesses several structural advantages for AI-driven drug discovery: a large talent pool versed in computational science, long-standing expertise in chemistry and pharmaceuticals, and lower operating costs than Western counterparts. Yet until recently, Indian pharmaceutical expertise has been confined largely to generic manufacture and contract research.

The AI opportunity changes this equation. Asia-Pacific is projected to become the fastest-growing region for AI in drug discovery, expanding at a CAGR of 21.1 per cent from 2025 to 2034, compared with 10.26 per cent growth in the United States. India, with its technical workforce and regulatory framework, sits at the centre of this regional growth.

Several factors drive this shift. First, computational drug discovery requires neither large capital equipment nor physical manufacturing — only data scientists, software engineers, and computational resources. Second, Indian pharmaceutical companies have begun investing in these capabilities, recognising that innovation, not volume production, increasingly determines market value.

Third, global pharmaceutical companies are seeking external innovation partners, creating demand for platforms like pepAI that can reduce time-to-candidate identification from months to weeks.

While Peptris operates in a competitive landscape, its focus on rare diseases and drug repurposing addresses genuine market gaps. Of the more than 7,000 known rare diseases, most have no approved treatments, and existing drugs often contain latent therapeutic potential that remains unexploited. These areas receive less venture attention than oncology or inflammatory diseases, allowing smaller startups to operate without overwhelming competition.

If Peptris’ platform can accelerate the discovery of therapeutics for diseases where progress has stalled, it will position India as not just a research vendor to Western companies but as a promising new source of intellectual property and innovation. It will demonstrate that India can compete in the higher-value segments of the pharmaceutical value chain.