Why AI alone won’t resolve drug discovery challenges

A digital representation of a protein structure. [Image courtesy of NIH]

Big Pharma and researchers are sharpening their focus on AI to speed drug discovery. But the path to fully AI-driven drug discovery faces substantial hurdles, according to Adityo Prakash, CEO of Verseon. “When it comes to drug discovery, AI has a data problem with which the pharmaceutical industry has not yet come to terms,” he said.

Prakash explained there is simply “not enough data” to rely on AI as the primary means of small molecule drug discovery. He discussed these challenges further in an article in American Pharmaceutical Review titled “Exploring New Chemical Space for the Treatments of Tomorrow.”

The limitations and challenges of AI-first methods

Even with high-throughput screening to automate the process of testing pre-synthesized drug candidates against disease-associated target proteins, the pharma…

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Generative AI could boost biopharma R&D productivity by billions, according to McKinsey

[Image credit: Seventyfour/Adobe Stock]

Generative AI stands to add trillions of dollars of value to the world economy, according to a recent McKinsey report. The consultancy noted that about three-quarters of the value of generative AI spans four areas — customer operations, marketing and sales, software engineering and R&D. The latter could see a 12% annual lift in global functional spending as a result of generative AI, representing an approximately $328 billion windfall annually.

An evolution or revolution: UBS and McKinsey’s take on generative AI in biopharma

The investment bank UBS recently reached more muted conclusions, noting that generative AI would represent more of an evolution than a revolution for biopharma.

Conversely, McKinsey bets the technology could deliver productivity gains that account for 10% to 15% of overall R&D costs. This potential largely stems from the applicatio…

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Verseon’s hybrid AI platform aims to unlock a universe of drug candidates

[Bhaskar/Adobe Stock]

The clinical-stage company Verseon (Fremont, California) is unique among companies exploring the use of AI in drug discovery given its focus on what it calls the “uncharted” chemical space. While Big Pharma companies typically test compounds from their collections for specific diseases, these collections often have constraints and overlapping compounds. Adityo Prakash, CEO of Verseon, estimates that researchers have developed about seven million chemically distinct compounds globally in the past century. But compared to that figure, the number of mappable compounds based on organic synthesis principles is a staggering 10^33.

Verseon is exploring uncharted chemical space

Adityo Prakash

Prakash emphasizes that while most AI companies involved in drug discovery focus on the narrower subset contained in current libraries, Verseon has …

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