Exscientia has entered into a strategic drug discovery collaboration with GlaxoSmithKline (GSK). Exscientia will apply its AI enabled platform and combine this with GSK, in order to discover novel and selective small molecules for up to 10 disease-related targets, nominated by GSK across multiple therapeutic areas.

Exscientia will receive research payments from GSK to undertake new discovery programs with nominated targets with the goal of delivering pre-clinical candidates. In addition to research funding, Exscientia is eligible to receive near-term lead and pre-clinical candidate milestones if all objectives are achieved. The total amount payable by GSK to Exscientia on achieving these milestones is £33 million, if all 10 projects are advanced.

“This agreement with GSK is the second we have signed in recent months with a top global pharma company. The alliance provides further validation of our AI-driven platform and its potential to accelerate the discovery of novel, high-quality drug candidates. Applying our approach to client discovery projects has already delivered candidate-quality molecules in roughly one-quarter of the time, and at one-quarter of the cost of traditional approaches,” said Andrew Hopkins, chief executive officer, Exscientia. “Our intention therefore is to apply these capabilities to projects selected by GSK. Delivering efficiencies to drug discovery has the potential to revolutionize the way early projects are executed, enabling more dynamic target selections from the burgeoning set of opportunities. We look forward to a productive collaboration with GSK.”

As part of this collaboration, Exscientia is incentivized to reduce the number of compounds required for synthesis and assay in order to achieve lead and candidate compound goals. This is in response to observations that early stages of drug discovery have not been positively impacted by technologies that have delivered significant efficiencies to other fields. Exscientia will apply both its Big Data resources comprising medicinal chemistry and large-scale bioassays, and its AI-driven algorithms to design novel molecules that fulfill the requirements of the lead and candidate criteria.