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Celgene inks drug discovery deal worth at least £25m with AI firm Exscientia

Published on 21/03/19 at 11:42am

Celgene has entered into a new three-year partnership with British artificial intelligence and drug discovery firm Exscientia to the value of at least $25 million, it has emerged, in a bid to galvanise small molecule drug discovery in oncology and autoimmunity.

Transactions stemming from the deal include this initial upfront payment in addition to “substantial” milestone payments subject to future regulatory and commercial successes.

The collaboration will leverage Exscientia’s Centaur Chemist AI technology to accelerate Celgene’s drug discovery and development efforts in the pre-clinical setting, by “at least three-quarters” according to the AI firm.

The deal is the latest in a series for Exscientia, with the Oxford-based company previously penning partnerships with Roche, Sanofi, GSK and Evotec.

“We’re incredibly proud to collaborate with Celgene and to sign another partnership with a key industry player, reinforcing our place at the forefront of AI drug discovery. Today, patients can wait more than ten years from initial drug discovery to its availability as a treatment,” commented Professor Andrew Hopkins, CEO of Exscientia. “With autoimmune diseases and cancer rates increasing, the pharmaceutical industry’s R&D productivity needs to dramatically improve – and technology is a key part of this. Since our pioneer Nature papers in the field, we have been developing our AI platform on the principle that AI combined with human creativity can significantly accelerate the drug discovery process and thus drastically improve access of new drugs to the market. We’re excited to work with Celgene to drive this transformational change in new therapeutic areas.”

Dr Lawrence Hamann, Corporate Vice President, Chemistry at Celgene, also remarked: “We are tremendously excited to collaborate with such leaders in the development and application of AI tools to accelerate drug discovery.  Exscientia have a proven track record of success in this emergent field, and we believe that reducing the number of iteration cycles in optimizing structure-activity and developability relationships through their platform will very favourably impact our ability to deliver high quality development candidates targeting unmet needs in oncology and autoimmunity.”

Matt Fellows

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