The year is 2025 and AI is seemingly everywhere. While the benefits of employing huge datasets alongside machine learning has obvious upside for biopharma, leaders are still figuring out where the tools will fit into the grander scheme of drugmaking. The trajectory of AI in the life sciences has so far been somewhat scattershot, said Brendan Frey, founder and chief innovation officer at genetic AI drug discovery company Deep Genomics. 

“Between 2015 and 2022, the success of Deep Genomics was similar to the success you see in other AI drug discovery companies in that era — we all struggled to identify drugs that would be meaningfully differentiated in the clinic,” said Frey, who is considered a pioneer in the field with his contributions to deep learning long before AI was in the zeitgeist. “It’s a disruptive technology, and it’s not going to be easy to figure out how to make it work. It’s going to be non-linear and complicated, and it’s going to take time.”

Biopharma execs across the industry are wrestling with how drugmakers can nestle into the AI revolution without compromising the fundamentals that define them in the first place. Today, we’re featuring insights from industry leaders seeking to bring new technology into the fold while also understanding the risk. We also spoke to a biopharma’s “chief patient officer,” a new role the company’s using to boost clinical trial diversity.

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