AI-gorithm: GenAI promises a booster dose for Indian pharma to scale up the value game | Technology News

Artificial Intelligence, particularly Generative AI, could be a transformative tool for pharma companies that promises to significantly impact drug development in an industry that has witnessed limited progress in recent decades. For the Indian pharmaceutical industry, a traditional production hub for generic medicines and low-cost vaccines which, while holding the third position globally in volume terms, comes in at a dismal 14th place globally when ranked in terms of the value of its pharmaceutical production. GenAI offers a particularly promising template for Indian pharma to orchestrate a much-needed scale up across the value chain.

The limitations faced by the Indian pharma industry in making breakthroughs in new drug discovery is linked to the general lack of resources to compete with drug majors from the United States and Europe and the fact that most companies struggle to progress a drug beyond Phase II clinical research.

China, which is largely in a similar situation as India as far as new drug discovery goes, has managed to make a breakthrough using AI, with Hong Kong-based biotech startup Insilico Medicine creating the first fully Gen AI drug to advance to human clinical trials, where AI was leveraged throughout the preclinical drug discovery process to identify a molecule target, generate novel drug candidates, assessment of binding efficacy with the target, and prediction of clinical trial outcomes. There are others pharma majors who have tasted early success while wielding AI as a tool:

• Massachusetts Institute of Technology researchers have unearthed a potent new antibiotic compound capable of treating infections caused by drug-resistant bacteria – the first new antibiotic discovery in the last 60 years. Facilitating the identification of this compound was a machine-learning algorithm, surpassing traditional experimental approaches by rapidly screening over a hundred million chemical compounds.
• Merck and Pfizer are among the other pharma majors actively leveraging Gen AI. Merck uses its proprietary platform, AIDDISON to help in drug discovery, while Pfizer now employs Gen AI-powered chatbots to deliver personalised messages to clinical trial participants.
• In India, too, biotech incubators and pharma start-ups have started to experiment with Gen AI applications in highly targeted therapies. The process, though, needs policy support, given that in India, the links between industry and academia are tenuous compared to the Western markets.

The biggest tool for drug discovery could be AlphaFold — an AI trained by Google arm DeepMind to predict protein structures. Given that a protein’s function is determined by how its constituent amino acid chains fold up into three-dimensional shapes, knowing a protein’s structure can help potentially alter its behaviour by introducing a drug that binds to the protein. The traditional methods for determining a protein’s structure have limitations – being slow, capital intensive, and complicated – with the result that researchers had only mapped the structure of less than 20% of the human body’s 20,000 proteins till end-2022. AlphaFold promises to solve this “protein folding problem”, but predicting the points where folds would be optimum.

Another promising tool is chip major Nvidia’s BioNeMo tool, a generative AI platform that provides services to pharma companies to develop, customise and deploy foundation models for drug discovery and enabling scientists to integrate generative AI to reduce experiments and, in some cases, replace them altogether.

Nvidia-backed Recursion Pharmaceuticals, an American company based in Utah, cites AlphaFold as an “incredibly important and powerful advancement in the field” that many biopharma companies, including Recursion, are using for drug discovery. “The protein structures derived from the AlphaFold database were critical to our ability to predict the protein target for approximately 36 billion chemical compounds in the Enamine REAL Space (a chemical database that currently contains over 13 billion virtual compounds), which we announced last August. This was a massive virtual drug-target screen that was made possible, in part, by AlphaFold,” Recursion’s spokesperson Taran Loper told The Indian Express.

“It’s important to note that we’re not treating AlphaFold’s predictions as truth; we’re treating them as hypothesis-generation tools that we can then experimentally validate. AlphaFold is one tool (among many) to expand the vast search space of biology and chemistry and prioritise the most interesting insights to explore further, which is a philosophy that underpins how we use tools and technologies at Recursion. And yes, these models are improving quickly!,” Loper said.

Apart from Recursion, Nvidia already has announced a couple of other Big Pharma partnerships last year. Amgen and Roche subsidiary Genentech have both incorporated BioNeMo into their workflows.

For India, this could be of particular relevance in scaling up the value chain, driving innovation, and fostering a resilient ecosystem. “GenAI is revolutionising the health sciences sector in India. In the realm of patient care, it is significantly impacting the patient journey by empowering patients to better manage their conditions, help in making decisions and overall, a seamless patient-doctor interface… it is imperative to underscore the importance of data governance and management. As we embrace these technological advancements, ensuring data privacy and compliance with regulatory requirements must remain a top priority,” according to Suresh Subramanian, Partner and National Life Sciences Leader, EY Parthenon India. EY India’s Gen AI report has projected that GenAI could contribute $4-5 billion addition to the Gross Value Added (GVA) of the Indian pharma sector by 2030.

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