Pharmaceutical companies are betting big on AI, hoping it will transform consumer health through more efficient clinical trials, research, and process optimization. But AI's progress is far from linear. While the relatively new tech is making strides in some areas, it remains stuck in others, often leaving the industry ‘two steps forward, one step back’. 

To understand where AI is gaining traction, we spoke with Harini Gopalakrishnan, ex-Global CTO of Life Sciences at Snowflake. With a wealth of experience across AWS, Sanofi, and Cognizant, and a history of groundbreaking work in AI platforms for life sciences, Gopalakrishnan is a leading voice in the intersection of big data and AI in pharma.

Halving timelines: "AI is definitely making an impact," Gopalakrishnan begins. "The transformation in research is much more pronounced because you can go from 12 years to 6 years. So, the value chain and time to value are much bigger if you solve that problem." AI, she explains, is accelerating the pace of discovery by reducing timelines and making research more efficient, an area where the industry is already seeing some disruption.

Needle in a haystack: However, she cautions, AI’s journey in pharma is far from simple. "It’s also like finding a needle in a haystack," she says. "There are around 10-12 AI-based drugs in clinical trials, but none of them have been approved yet. It’s still in a try-and-test phase." Gopalakrishnan emphasizes that, while AI holds promise, it is not yet poised to overhaul clinical trials entirely. "It's not like we are going to reduce or replace clinical trials completely. It's more about optimizing for a better success story. The ROI is probably bigger in terms of cash, but it doesn't necessarily imply a faster time to market. It's about being more precise in how you run the trials," she explains.