AI Biomanufacturing: India's Policy Challenge

India's AI Biotech Ambitions

India is at a crucial point in using artificial intelligence for biotechnology innovation. Initiatives like the BioE3 Policy and the IndiaAI Mission aim to make India a leader in AI-driven biomanufacturing and ethical AI development. However, fragmented rules and slow safeguards could hinder this.

The question is whether India can balance its ambitions with accountability as it tries to use AI's potential.

AI Transforming Biomanufacturing

India's biomanufacturing sector is seeing many new possibilities. The country has been a top supplier of generic medicines and vaccines for years, known for its scale, cost-effectiveness, and reliability. Now, AI is bringing even bigger changes to the life sciences industry.

Many biomanufacturing facilities already use robots for precise tasks, biosensors for real-time data, and AI to optimize processes like fermentation and packaging. Biocon, an Indian biotechnology firm, is using AI to improve drug screening and biologics manufacturing. By using AI-based predictive analytics, Biocon aims to increase efficiency and quality control, while lowering production costs.

Strand Life Sciences in Bengaluru uses AI in genomics and personalized medicine to speed up drug discovery and clinical diagnostics. Their platforms use machine learning to analyze biological data, making it easier to find drug targets and predict treatment responses. These examples show how AI is changing biomanufacturing and healthcare in India.

The Impact of AI

AI is changing biomanufacturing by using sensors to feed data into AI systems that can detect small issues, like temperature or pH changes, or changes in cell growth. The AI can predict problems and adjust the process before a human operator notices. Digital twins, virtual replicas of manufacturing plants, allow engineers to run simulations and test changes without affecting real equipment. This results in fewer failed batches, less waste, and higher quality products. These improvements can be transformative for India.

Government Initiatives and Challenges

The Indian government recognizes AI's potential. The BioE3 Policy, introduced in 2024, outlines plans for biomanufacturing hubs, biofoundries, and “Bio-AI Hubs” to bring together experts in science, engineering, and data. The IndiaAI Mission is working with BioE3 to ensure India’s AI revolution is innovative and ethical, focusing on building technical capacity and trust. It supports projects that focus on explainable and responsible AI, helping to set standards for AI development and use in health and biotechnology.

However, India's regulatory framework is still developing. Current rules for new drugs, biologics, and manufacturing processes were not designed for AI-driven systems. Questions arise about the reliability of AI models used to control bioreactors or predict vaccine yields. It's unclear who ensures that the data used to train these models is representative of India’s diverse conditions and that the models won't make errors. These issues are important for public trust and safety.

Globally, regulations are evolving. The European Union’s AI Act, effective since August 2024, classifies AI tools by risk level, with high-risk applications like genetic editing facing strict audits. The U.S. FDA’s 2025 guidance mandates a seven-step framework for AI credibility. These models emphasize context-specific risk evaluation and adaptive regulation, which India currently lacks. For example, the FDA’s ‘Predetermined Change Control Plans’ allow iterative AI updates for evolving cancer therapies without compromising safety. India needs similar risk-based oversight as it expands AI-powered manufacturing.

Context and Future Potential

Consider an Indian biotech startup that develops an AI platform to optimize enzyme production for the specialty chemicals industry, a sector worth $32 billion (Rs 2.74 lakh crore). If this AI is trained only on data from large, urban manufacturing sites, it might not account for the specific conditions of smaller plants in semi-urban or rural areas. Without standards for dataset diversity and model validation, the AI could recommend process changes that work in Bengaluru but fail elsewhere, resulting in lost revenue and damage to India’s reputation for quality.

The FDA’s approach emphasizes the importance of understanding how AI is being used and how strict oversight should be, depending on the risks involved.

Biomanufacturing is just one part of the potential. In the future, India could design vaccines using algorithms that predict viral mutations and provide AI-generated advisories to farmers and diagnose patients in rural areas using tools trained on India’s genetic diversity. AI platforms can also screen millions of compounds to speed up drug discovery, refine drug candidates, and streamline clinical trials.

Wipro is developing AI-powered solutions for pharmaceutical companies to streamline drug discovery by combining machine learning with computational biology. Tata Consultancy Services is using AI in its ‘Advanced Drug Development’ platform to fine-tune clinical trials and predict treatment outcomes. These applications show how AI is transforming the healthcare value chain.

Challenges and the Way Forward

AI models are only as good as the data they’re trained on, making data governance a significant challenge in India. The Digital Personal Data Protection Act 2023 is a start, but it doesn’t address the specific needs of AI in biomanufacturing, such as ensuring that datasets are clean, diverse, and free from hidden biases. Intellectual property is another issue, as AI's role in inventing new molecules and processes raises questions about inventorship, data ownership, and licensing.

To move forward, India needs a risk-based regulatory framework that defines the context of use for AI tools, sets standards for data quality and model validation, and ensures ongoing oversight. It also needs to invest in infrastructure and talent across the country and foster collaboration between regulators, industry, academia, and international partners.

By getting this right, India can secure its legacy in generic drug manufacturing and harness AI to create new innovations in biomanufacturing.