AI and biomanufacturing: can India’s insurance policies match its ambitions?

India stands at a pivotal juncture in its quest to harness synthetic intelligence (AI) for biotechnology innovation. On one hand, initiatives just like the BioE3 Coverage and the IndiaAI Mission mirror a daring imaginative and prescient to place the nation as a worldwide chief in AI-driven biomanufacturing and moral AI growth. On the opposite, fragmented laws and lagging safeguards threaten to undermine this progress. As India races to capitalise on AI’s transformative potential, a essential query emerges: can it stability ambition with accountability?

India’s biomanufacturing sector is abuzz with prospects. For many years, the nation has been the world’s go-to provider for generic medicines and vaccines, a popularity it has constructed on scale, value, and reliability. However now, as AI sweeps by way of the worldwide life sciences business, there’s a way that one thing a lot greater is within the works. Many fashionable biomanufacturing services have already got robots working precision duties, biosensors streaming real-time information, and AI fashions quietly optimising the whole lot from fermentation to packaging.

DNA of biomanufacturing

Biocon, considered one of India’s largest biotechnology companies, is integrating AI to enhance drug screening and its biologics manufacturing processes. By leveraging AI-based predictive analytics, Biocon will improve the effectivity of fermentation and high quality management, decreasing manufacturing prices whereas sustaining international requirements. Equally, Bengaluru-based Strand Life Sciences makes use of AI in genomics and personalised drugs, serving to speed up drug discovery and medical diagnostics. Their platforms use machine studying to analyse complicated organic information, making it simpler to determine drug targets and predict remedy responses. These efforts illustrate how AI is already reshaping biomanufacturing and healthcare supply in India.

It’s not nearly swapping out folks for machines. AI is reworking the very DNA of biomanufacturing. Think about a manufacturing line the place sensors feed hundreds of information factors each second into an AI system that may spot the faintest trace of hassle, like a temperature drift, a pH blip or a refined change in cell progress. Earlier than a human operator even notices, the AI predicts a deviation, tweaks the method, and retains the batch on monitor. Digital twins, that are digital replicas of whole manufacturing crops permit engineers to run simulations, take a look at modifications, and foresee issues with out ever touching an actual fermenter.

The consequence? Fewer failed batches, much less waste, and merchandise that persistently meet the gold customary for high quality. For a rustic like India, the place each rupee and each dose counts, these beneficial properties might be transformative.

Fascinating and complex

The Authorities of India has clearly recognised this potential. The BioE3 Coverage, rolled out in 2024, is a playbook for the long run. The coverage lays out plans for state-of-the-art biomanufacturing hubs, biofoundries, and “Bio-AI Hubs” that can convey collectively the very best minds in science, engineering, and information. There’s actual cash on the desk too, with funding and grants designed to assist startups and established gamers alike leap from the lab bench to the market shelf.

Equally essential is the IndiaAI Mission, which is working alongside BioE3 to make sure India’s AI revolution is each revolutionary and moral. The Mission is as a lot about constructing technical capability as about constructing belief. By supporting tasks that concentrate on explainable and accountable AI — resembling efforts to scale back algorithmic bias or frameworks for “machine unlearning” — the Mission helps set the requirements for a way AI needs to be developed and deployed in delicate sectors like well being and biotechnology.

However right here’s the place issues get fascinating and complex. Whereas India’s ambitions are sky-high, its regulatory framework continues to be catching its breath. The principles that govern how new medication, biologics, and manufacturing processes come to market had been written for a unique period. Immediately’s AI-driven programs don’t at all times match neatly into these containers. For instance, when an AI mannequin is used to regulate a bioreactor or predict the yield of a vaccine batch, how do we all know it’s dependable? Who checks that the information it was skilled on is consultant of India’s various circumstances, or that it received’t make a catastrophic error if one thing sudden occurs? These aren’t simply technical questions. They’re issues of public belief and security.

Danger-based, context-aware

Globally, the foundations are altering. The European Union’s AI Act, efficient since August 2024, classifies AI instruments into 4 threat tiers. Excessive-risk functions like genetic enhancing face strict audits whereas the U.S. FDA’s 2025 steerage mandates a seven-step framework for AI credibility. These fashions emphasise two issues India lacks: context-specific threat analysis and adaptive regulation. As an example, the FDA’s ‘Predetermined Change Management Plans’ permit iterative AI updates which might be essential for evolving most cancers therapies with out compromising security. India wants this sort of risk-based, context-aware oversight because it strikes from pilot tasks to full-scale, AI-powered manufacturing.

Image an Indian biotech startup that develops an AI platform to optimise enzyme manufacturing for the specialty chemical compounds business. This sector is already price $32 billion (Rs 2.74 lakh crore) and rising quick. If this AI is skilled solely on information from giant, city manufacturing websites, it’d fail to account for the quirks of smaller crops in semi-urban or rural areas, like variations in water high quality, ambient temperature and even native energy fluctuations. With out clear requirements for dataset variety and mannequin validation, the instrument might advocate course of tweaks that work superbly in Bengaluru however flop in Baddi. The consequence: misplaced income, wasted assets, and a blow to India’s popularity for high quality. This is the reason the context of use and credibility evaluation which might be core pillars within the FDA’s strategy are so essential. We have to be clear precisely what query the AI is answering, the way it’s getting used, and the way strict our oversight needs to be, relying on the dangers concerned.

After all, biomanufacturing is just one piece of the puzzle. Think about a future the place India not solely provides 60% of the world’s vaccines but in addition designs them utilizing algorithms that predict viral mutations. A future the place farmers in Bihar obtain AI-generated advisories to fight pest outbreaks and sufferers in rural Tamil Nadu are identified by instruments skilled on India’s genetic variety. This isn’t science fiction — it’s the promise of AI-driven biomanufacturing, a area the place India is making daring strides. But beneath this optimism lies a essential query: can our insurance policies sustain with science?

With nice energy comes…

The intersections are multiplying. In drug discovery, AI platforms can display thousands and thousands of compounds in silico, slashing the time and value wanted to search out new therapies. Molecular design instruments are serving to researchers fine-tune drug candidates for max efficacy and minimal negative effects. Scientific trials that had been as soon as infamous for delays and inefficiencies are being streamlined by AI programs that optimise affected person recruitment and trial design, making research sooner and extra consultant. Even the provision chain is getting an improve: AI-powered predictive upkeep retains manufacturing traces buzzing, whereas demand forecasting ensures that medicines attain the precise place on the proper time, decreasing shortages and waste.

One other distinctive software of AI is Wipro’s work in creating AI-powered options for pharmaceutical firms to streamline drug discovery. By combining machine studying algorithms with computational biology, Wipro has helped cut back the time required to determine viable drug candidates. Equally, Tata Consultancy Providers is leveraging AI in its ‘Superior Drug Growth’ platform, which makes use of machine studying to fine-tune medical trials and predict remedy outcomes. These functions display how AI is not only confined to manufacturing however is reworking the complete healthcare worth chain, from analysis to affected person care. These improvements additionally point out India’s potential to paved the way in AI-powered healthcare options.

However with nice energy comes nice accountability and a number of latest challenges. Knowledge governance is a giant one. AI fashions are solely nearly as good as the information they’re skilled on, and in a rustic as various as India, that’s no small feat. The Digital Private Knowledge Safety Act 2023 is a begin, nevertheless it doesn’t tackle the precise wants of AI in biomanufacturing, like making certain that datasets are clear, various, and free from hidden biases. Mental property is one other thorny situation. As AI begins to play a much bigger position in inventing new molecules and processes, questions on inventorship, information possession, and licensing have gotten extra pressing. With out clear, harmonised insurance policies, the chance of stifling innovation or ending up in expensive authorized battles persists.

Create, not simply copy

So, what’s the best way ahead? First, India wants to maneuver shortly in the direction of a risk-based, adaptive regulatory framework. This implies defining the context of use for each AI instrument, setting clear requirements for information high quality and mannequin validation, and making certain ongoing oversight as programs evolve.

Second, India must put money into infrastructure and expertise — and never simply within the metropolitan cities however throughout the nation.

Third, it must foster a tradition of collaboration, bringing collectively regulators, business, academia, and worldwide companions to share greatest practices and resolve issues collectively.

If the nation will get this proper, the rewards are huge. India’s legacy in generic drug manufacturing is safe however the future belongs to those that can harness the ability of AI to create, not simply copy. With the precise insurance policies, the precise folks, and the precise priorities, there’s no cause why the following nice leap in biomanufacturing shouldn’t come from India. The world is watching and the time to behave is now.

Deepakshi Kasat is a scientist with GlaxoSmithKline in California. The views expressed within the foregoing article are the writer’s personal and don’t contain these of the corporate.