Artificial intelligence (AI) has the potential to reshape the pharmaceutical industry, potentially cutting drug development time by up to 70% and reducing the number of clinical trial phases, according to industry leaders speaking at Gitex Asia 2025.
During a panel discussion moderated by Giang Nguyen, chief technology officer at Nanyang Biologics, which has developed a drug-target interaction graph neural network for drug discovery, the experts explored the potential and challenges of integrating AI into drug discovery and development.
Alok Khettry, chief operating officer at India’s Bharat Serums and Vaccines, noted that AI can help to speed up clinical trials that involve multiple phases. “Today, we look at phase one to phase four, but this may change in the next few years, when you may have only two phases,” he said.
In developing drugs to treat cancer, rare conditions and diseases like Alzheimer’s, Khettry said AI can reduce development time by as much as 70% and drive “huge cost savings”. He cited cases where the use of AI has helped to bring a drug to market, from identifying drug candidates to the pre-clinical trial stage, in just 36 months.
Frank Yang, founding partner and CEO of Blue Ocean Capital Group, a Chinese venture capital firm focused on life sciences, highlighted AI’s potential in treating conditions that are difficult to diagnose. “AI is going to be a huge weapon in rare disease diagnostics,” said Yang, recounting a case where AI had helped to identify a rare disease possibility missed by doctors.
He also pointed to the use of newer generative AI models in drug development, though he warned of the “illusion provided by this type of AI” and stressed the importance of validating model outputs.
The panel also touched on AI’s potential to bridge the gap between modern science and traditional medicine, such as Ayurveda and traditional Chinese medicine (TCM). Yang said AI-powered TCM clinics have emerged in China, where robots assist in diagnosis and treatment suggestions. “The number of years of experience of TCM physicians matter and these robots have an average of 20 years of experience,” added.
AI can also help with building the scientific validation often lacking in alternative therapies, said Khettry. “One problem with alternative medicine is the lack of evidence, so AI can definitely help in developing that evidence faster,” he added.
Despite the optimism, challenges remain, particularly for established pharmaceutical companies. Khettry noted the difficulty of harnessing AI in legacy drug development processes, from identifying drug targets to designing drug molecules. “AI has to be integrated right from the beginning,” he said. “If you have old R&D processes, integrating AI into those processes can be difficult. There’s also the mindset and cultural issue that will come in.”
From an investor’s perspective, Yang pointed out the symbiotic relationship between startups and large pharmaceutical companies, noting that while startups account for 80% of novel drug candidates in the market, large corporations are needed to commercialise them.
He advised startups that are looking to tap AI in drug discovery to develop a unique “weapon”, whether it’s a drug candidate or a delivery platform, citing Ribo Life Sciences, one of Blue Ocean’s portfolio companies that has built a platform pharmaceutical companies can use to develop drugs, from early research to commercialisation.
To pave the way for broader adoption of AI in the pharmaceutical industry, the panel agreed on the need for supportive ecosystems. Yang called for public sector investment in infrastructure such as shared data resources and compute power, alongside supportive regulatory environments and incentive programmes.
Khettry cited global initiatives such as the Coalition for Epidemic Preparedness Innovations as successful models for funding drug development. “They work with governments, the private sector and philanthropic organisations to fund the development of vaccines against infectious diseases,” he said. “Collaboration is the order of the day, and so if we want to save cost and take advantage of the power of AI, then public-private partnerships are going to be the way forward.”