Recently, something remarkable happened that most people missed: The country quietly launched its first government-backed, state-of-the-art bio-foundry-designed to scale engineering biology. More on the way. This marks the beginning of a new era in biotechnology where scientists can design, print, and test novel biological materials with a speed and flexibility that was once limited to software engineers writing code.
Bio engineering (Shutterstock)
This new wave is being driven not only by advances in biotechnology but by its convergence with Artificial Intelligence (AI). We are entering an age where machines can design life. The same underlying technology that powers ChatGPT, Gemini, and Grok is now being applied to DNA, proteins, and cellular processes. Instead of just prompting a chatbot to summarize a document, researchers can now prompt Large Biological Language Models (LBLM, the biological equivalent of GPTs) trained on millions of protein and genomic sequences to suggest a new cancer-targeting antibody, a biodegradable plastic enzyme, a synthetic vaccine component or a tailored gene editing tool. This is generative biology—and India is building the infrastructure to scale it.
The Department of Biotechnology’s BioE3 policy-short for Biotechnology for Economy, Environment, and Employment is in motion. A national call has been issued for setting up Bio-AI hubs and build new layer of AI capabilities across the country. These will be nodes where interinstitutional and interdisciplinary teams come together to shape future of AI-driven biology to solve real-world problems in health care, agriculture, and climate. This is happening very fast and the funding cycle is now actively underway.
India has unique advantages in this race. The government’s IndiaAI Compute Portal makes high-end GPUs accessible to researchers and startups across the country, removing one of the biggest barriers to advancing AI capabilities. Our biological datasets are vast and diverse, spanning everything from cancer proteomics to crop genomes, from tribal microbiomes to traditional medicine records. And our entrepreneurs are used to doing more with less, building scalable solutions without waiting for billion-dollar budgets.
The next logical step is to create what I call Bharat Bio-mind, a national AI engine for biology that combines computing power, curated datasets, secure cloud infrastructure, and interdisciplinary talent. Bio-mind would not be another government department or a closed lab, it would be a platform, accessible to those solving real problems from scientists decoding disease to biotech startups improving yields, to pharma companies developing new therapies to meet urgent medical needs.
Bio-mind would function as an independent but co-located unit within leading academic institutions, operationally autonomous but deeply connected to research and talent. Its AI engineers, model developers, and computational biologists would work directly with industry and researchers to develop AI-powered solutions for high-value problems such as molecules that break down toxins, proteins that neutralise disease and therapy simulations that reduces time in clinical trials. The tools to build these exist, but they require collaboration and computing infrastructure that most institutions cannot create on their own.
Bio-mind would not operate in isolation, it would formally link to the world’s largest biological databases, such as those in Europe and the US, while simultaneously strengthening India’s own sovereign data resources. It would serve as shared infrastructure for building and testing AI models that reflect regional diversity and meet local needs. More importantly, it would evolve through use. The models built by Bio-mind would be refined through feedback from those who actually deploy them. That cycle of iteration—prompt, build, test, improve—is how innovation scales.
The Nobel-winning AI model AlphaFold is proof that convergence of AI and biology is reshaping the biotech industry as never before. At the lab level, digital interns called Bio-AI agents are being trained to scan thousands of proteins, flag drug targets, simulate bioreactors, and draft reports. In manufacturing, they can detect anomalies, reorder inventory, and improve quality control. These agents will not replace scientists, they will augment them. But the platform that powers them needs to be built thoughtfully, with strong governance and aligned incentives.
We have to be very cautious. The same technology that can create life-saving therapies can be misused to produce biological weapons. As DNA synthesisers become cheaper and more accessible, the risks increase. Bio-mind must include ethical guardrails, strict access controls, and real-time auditability. Just as we regulate dual-use exports or sensitive AI models, we must take biosecurity seriously before the first crisis forces our hand.
If we do this right, India can offer the world something it urgently needs: an open, collaborative, and secure way to innovate in biology. We can reduce drug development costs, accelerate cures for rare diseases, develop sustainable materials, and ensure food resilience in the face of climate change. This is engineering of biology powered by AI, and is already underway.
The government has shown the vision, extending support and academia has the talent and infrastructure. But it is industry that must now step forward, not as isolated players looking for the next IPO, but as co-builders of a national platform.
This article is authored by Dr Dhananjay Kumar Tiwary, senior fellow, Brown University, US (onn leave from his position as adviser, Department of Biotechnology, Government of India).
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