AstraZeneca takes home 2 more computer-generated drug targets from BenevolentAI

AstraZeneca takes home 2 more computer-generated drug targets from BenevolentAI

After doubling down on its drug hunting partnership with BenevolentAI earlier this year, AstraZeneca is once again reaping the benefits.

The artificial intelligence-powered molecule designer announced that the Big Pharma has selected two additional computer-generated targets for its R&D portfolio, aimed at chronic kidney disease and idiopathic pulmonary fibrosis.

That amounts to five hits from the collaboration since it first began in 2019. BenevolentAI said in an Oct. 6th press release that the project has the potential to continue racking up development milestone payments—like the two it announced this week for its work, both of undisclosed amounts—and could bring in sales-based royalty revenues in the future if the drugs reach the market.

“Our ongoing collaboration with BenevolentAI is helping us to uncover novel rare variants of complex diseases such as IPF and CKD,” Mene Pangalos, AstraZeneca’s executive VP of biopharmaceuticals R&D, said in the release.

At the top of this year, the companies re-upped their joint research efforts, with a timeline reaching into 2025, and expanded their work to include targets in heart failure and lupus.

AstraZeneca has been exploring a variety of ways to tackle heart failure, which it estimates will affect one in three people over age 55. The company’s efforts include the use of mRNA-powered therapies with Moderna through a pre-pandemic project that dates back to 2017 and more recently, through a $2.9 billion deal with Ionis.

Meanwhile, AstraZeneca collected its second pulmonary fibrosis target from BenevolentAI this past May in return for a milestone payment of an undisclosed amount. The company landed on its first target in the indication in 2021, alongside a separate target in chronic kidney disease.

BenevolentAI’s models work, in part, to predict the opportunities for drugs that may be overlooked by identifying the differences in proteins expressed by healthy and diseased cells and using knowledge graph systems to link compounds, genes, proteins and eventual illness.

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