Exscientia and BMS expand AI drug discovery deal, with potential $1.2B+ value – BioWorld Online

Building on a deal first struck in 2019, artificial intelligence (AI) specialist Exscientia Ltd. has agreed to take responsibility for a multitarget drug discovery collaboration with Bristol Myers Squibb Co. that could be worth more than $1.2 billion in all. The expanded collaboration, first established with BMS-acquired Celgene Corp., includes $50 million in up-front funding, up to $125 million in near to mid-term potential milestones, plus additional clinical, regulatory and commercial payments. It remains focused on small-molecule drug candidates in areas including oncology and immunology.

Under terms of the agreement, Exscientia will take responsibility for AI-design and experimental work necessary to discover drug candidates for BMS. Neither party has disclosed specific products of their work yet, though Exscientia CEO Andrew Hopkins told BioWorld that his company plans to announce milestones as the projects develop. Should they succeed, Exscientia would receive tiered royalties on net sales of any marketed drug products resulting from the collaboration.

The deal provided yet further recognition of the tremendous interest and belief in AI-driven discovery approaches that have bloomed within big pharma. Momentum behind the trend has driven deals for Exscientia with Roche Holding AG, Glaxosmithkline plc, Sanofi SA and Evotec AG, as well as substantial investments in the company.

In April, Exscientia closed a $225 million series D financing led by Softbank Vision Fund 2, replete with an additional $300 million equity commitment. Prior to that in March, the Oxford, U.K.-based company extended its series C financing, adding a further $40 million to the $60 million raised in May 2020. Earlier financings included a $26 million series B round and $17.6 million in series A support.

Underpinning the BMS deal, as well as the others, is Exscientia's Centaur AI platform, an approach that the company said allows it to "identify emerging hotspots of opportunity" from genetic data and global biological literature before applying those insights to "learn which areas of chemistry are most likely to balance complex requirements" for each discovery project.

In a statement about the deal, BMS president of research and early development Rupert Vessey said Exscientia would be applying AI technologies proving "capable of generating best-in-class molecules while also reducing discovery times." BMS declined to make Vessey available for an interview to discuss the deal.

While its not yet clear how AI-centric approaches to discovery will ultimately stack up to more traditional approaches in terms of efficiency or clinical success, progress is clearly underway.

Since its founding in 2012, Exscientia has advanced three AI-designed molecules to the clinic: EXS-21546, an in-house adenosine 2A receptor antagonist in testing for the potential oral treatment of cancer, and two programs partnered with Sumitomo Dainippon Pharma Co. Ltd. (DSP), of Osaka, Japan.

The first of the DSP-partnered programs is DSP-1181, an oral long-acting 5-HT1A receptor agonist under development as a potential treatment for obsessive-compulsive disorder. Clinical development of the candidate began in January 2020, less than 12 months after the project began, contrasting with a typical average of 4.5 years from discovery to the clinic using conventional techniques, Exscientia said last year.

Adding to the progress, on May 13 Exscientia announced a second DSP-partnered candidate is entering a phase I study in the U.S. for the treatment of Alzheimer's disease psychosis. The molecule, DSP-0038, is both an antagonist for the 5-HT2A receptor and agonist for the 5-HT1A receptor, while selectively avoiding similar receptors and unwanted targets, such as the dopamine D2 receptor, the partners said.

As made clear in an announcement of its most recent financing, Exscientia has no small ambitions around the potential for its AI-driven platforms, noting it will "continue expanding the technology platform toward autonomous drug design." The objective, Hopkins said, is "enabling automated systems to also make key decisions by themselves, minimizing the requirements for human intervention. For autonomous driving, for example, the car will sense when it needs to brake and will then perform that response."

"It is the same principle for drug design and discovery where an autonomous system would determine what type of experiment would be required," he said.

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Exscientia and BMS expand AI drug discovery deal, with potential $1.2B+ value - BioWorld Online