Sun Pharma, Glenmark Deploy AI to Accelerate Drug Development and Cut Costs
Indian pharmaceutical companies Sun Pharma and Glenmark are integrating AI into drug discovery to reduce development timelines and costs. Global pharma AI investment reached $6.93 billion last year and is projected to hit $16.5 billion by 2034.
Sun Pharma and Glenmark Pharma are exploring how artificial intelligence can reduce the time and cost of developing new drugs, reflecting a broader global trend in pharmaceutical research. Drug makers worldwide invested nearly $6.93 billion in AI-driven drug discovery last year, a figure projected to more than double to $16.5 billion by 2034.
The chairman of Sun Pharma indicated that the company is seriously evaluating how AI can strengthen its research capabilities and accelerate drug development. Artificial intelligence could help compress timelines within a roughly 18-month window for late-stage patient recruitment and regulatory filings. At Sun Pharma, which reported revenues of ₹52,041 crore last year, innovative and specialty products already contribute about 20% of total revenue.
Glenmark is taking a similar approach, though with a sharper near-term focus on small-molecule, chemistry-based drug discovery. The chairman noted that AI in drug discovery is likely to have its immediate impact in analyzing complex clinical trial data and refining molecular modeling and drug design. He noted that biologics may take longer to see comparable benefits, but AI is expected to play an expanding role across the research cycle.
Both companies are exploring AI for things like finding the right patients for trials, analyzing results, and speeding up paperwork. AI helps scientists quickly sort through molecules, predict side effects, and even understand how proteins interact in the body.
Last year, Glenmark's subsidiary entered into a landmark $1.9 billion out-licensing agreement with US-based AbbVie for a multiple myeloma treatment candidate ISB2001. The deal included a $700 million upfront payment, highlighting the growing global expectations for innovative assets emerging from Indian labs.
For pharmaceutical companies, bringing a drug to market even a year earlier can extend its effective patent life and significantly boost revenues. AI in drug discovery promises to reduce trial-and-error processes, speed up patient recruitment, and streamline data analysis, rather than replacing scientists altogether.