As AI Collapses Drug Discovery Timelines, Will India Follow …

India’s bioeconomy has expanded at breakneck speed over the past decade, rising from $10 billion in 2014 to $165.7 billion in 2024. The scale of manufacturing, the depth of clinical research talent, and the global reputation of Indian pharma have placed the country among the world’s top biotech hubs.

To replicate such success in biotechnology over the next decades, countries would require manufacturing muscle and speed at R&D to discover and develop new therapies. One source critical to this speed is Artificial Intelligence (AI). 

Nowhere is that more evident than in China.

Its strategic use of AI to automate labs, model biological interactions, design molecules and optimise clinical trials has transformed it into one of the world’s fastest-rising biopharma powers. They say China has begun compressing drug discovery timelines at a pace India has not yet matched. 

China in 2022 unveiled its first five-year bioeconomy plan that projected a target of a $3.28-trillion bioeconomy to be achieved by the end of 2025. 

Western pharmaceutical giants are striking multibillion-dollar deals with Chinese biotech firms that use AI, signalling growing confidence in China’s ability to deliver faster and cheaper innovative drugs. 

AstraZeneca, Pfizer, and Sanofi among the Big Pharma have struck major deals with Chinese AI-driven biotech firms, drawn by the country’s rapid development timelines, lower research costs, and a state-supported startup ecosystem. 

While US companies continue to dominate the sector, China’s growing talent pipeline and strong government backing are beginning to shift global perceptions around where the next wave of biotech innovation may emerge.

At the Bengaluru Tech Summit in November this year, Kiran Mazumdar-Shaw, executive chairperson of Biocon, pointed out the rapid surge in China’s clinical R&D activity. “China has validated its use of AI to bring down pipeline time and costs, becoming one of the most efficient drug discovery ecosystems,” she said. 

China’s share of global clinical trial starts has jumped from 3% in 2013 to 28% in 2023, a shift so dramatic that it is now considered the only country capable of challenging the US biotech machine across the full research-to-commercialisation pipeline.

Debjani Ghosh, president of NASSCOM, described this convergence as the defining feature of the new technological age. “The disruption is not in individual sciences. The disruption is at the convergence,” she said during her keynote at the Bengaluru Tech Summit. 

For her, AI is no longer merely a powerful tool; it has become the centre of gravity in a planetary system of emerging technologies, with biology, physics, materials science and energy orbiting around it. “Everything else is anchored around intelligence,” she said. “This is where you get to see the maximum disruption and impact.”

Ghosh argued that India has spent too long in a “perpetual catch-up phase” in AI, in silicon, in quantum and the biotech race must not fall into the same pattern. “How do we move India out of this perpetual catch-up phase and leapfrog to a leadership position, where we are defining the evolution, the standards, and the alliances?” she asked. 

As AI becomes woven into biology, computing and automation, it will reshape not just industries but national security, governance and global power. China has understood this, she said, and acted decisively to translate that understanding into policy and investment.

According to Stanford University’s AI Index Report 2024, China accounted for 61.1% of global AI patent filings in 2022, far ahead of the United States at 20.9%. Analysts point to a decade of investment in AI talent, biomedical research, and supportive policy as the foundation for this new phase of growth.

Mazumdar-Shaw expanded on why China’s momentum is particularly significant for India. China’s application of AI goes beyond prediction models or molecule screening. It has built automated laboratories capable of running experiments around the clock at speeds that would require dozens of human scientists to match. 

These labs are beginning to merge with AI systems trained on enormous volumes of biological and chemical data, creating feedback loops that accelerate discovery with each cycle. “Biology is becoming programmable,” she said. 

India may be the world’s largest supplier of generics and vaccines, but a future led by AI-driven biology will depend on rapid prototyping, automated validation, massive compute and the ability to shift from molecule development to clinical testing in record time. If China continues to compress its development cycles, it could redefine global supply chains and intellectual property flows in ways that blunt India’s current advantages.

However, Ghosh warned that this technological shift will not only shape industrial competitiveness but also global power structures. She pointed to DeepSeek, a Chinese AI breakthrough that triggered an immediate geopolitical recalibration. 

“When DeepSeek came up, all of a sudden everybody was saying we have a new leader in AI,” she said. “What happens when you lead in some of these technologies? You’re not just a technology leader; you become an economic rule-maker.” AI, quantum computing and programmable biology, she said, have become core instruments of tech diplomacy—a domain India can no longer afford to treat as peripheral.

The panel stressed that India holds enormous untapped potential. Its talent base, cost advantages, biodiversity, clinical research capacity and growing entrepreneurial ecosystem create fertile ground for a leap in AI-led biotech innovation. But, such a leap requires India to embrace convergence, not just incremental improvement. It demands that biology be treated not as a lab science but as a computational discipline, one that requires high-performance computing, data interoperability, cross-sector collaboration and policy frameworks that enable bold experimentation.

Mazumdar-Shaw said she believes the answer lies in recognising that the next breakthroughs in healthcare, agriculture, materials, energy and climate will come from programmable systems. 

Ghosh emphasised that the window for action is narrower than most policymakers realise. “It will happen sooner than we realise,” she said.

The post As AI Collapses Drug Discovery Timelines, Will India Follow China’s Lead? appeared first on Analytics India Magazine.

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