Berg backs AI-driven discovery platform to save time, money in R&D

Berg Pharma President and CTO Niven Narain

With its big claims about how artificial intelligence can slash drug development timelines and a lead candidate based on a coenzyme best known as a dietary supplement, Berg is always likely to provoke skepticism. But the company is sticking to its guns, with President and CTO Niven Narain pointing to early drug discovery successes as evidence of its legitimacy.

Berg set up shop in 2006 without a lead candidate or therapeutic target, putting it behind the point at which many biotechs start. A Phase I trial started in 2012. Talking to Bio-IT World, Narain cited the speed at which Berg has gone from a blank slate to having two candidates in clinical trials as evidence the company can deliver on claims it can halve the money and time needed to develop a drug. Narain thinks the bullish claim is achievable given just how time-consuming and expensive R&D is today.

"If I spend $650 million, and 7 years, from the time I have an IND [investigational new drug] to develop a drug, I'm sure you'd agree that's still a lot of money," Narain said. The obvious time-saving in Berg's approach--which creates virtual models of healthy and diseased cells--is the elimination of hit-to-lead optimization and screening. Berg sidesteps these processes by picking naturally occurring molecules from its virtual models and using these as the basis for a drug.

This approach led to the identification of coenzyme Q10 as a potential treatment for a broad range of solid tumors. But with the company yet to advance a candidate into Phase III--which gobbles up drug development budgets and stretches timelines--the hardest steps are still to come.

- read the Bio-IT World feature

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