Exscientia was founded by Professor Andrew Hopkins FRS FMedSci with fellow innovators in 2012. Exscientia has quickly established itself as a leader in harnessing AI to identify promising drug molecules and precision-engineer medicines more rapidly and effectively.
Crucial early funding
Early Biotechnology and Biological Sciences Research Council (BBSRC) funding proved crucial to demonstrating the potential and practicality of using these AI-led approaches and underpinned Exscientia’s formation and early development.
The founding team of technologists Jérémy Besnard, Richard Bickerton, Adrian Schreyer and Willem van Hoorn was further complemented with seasoned ‘drug hunter’ Andy Bell and biotech executive Mark Swidells.
In October 2021, Exscientia was floated on the Nasdaq stock market, raising $510 million, the largest initial public offering for a European biotech ever. From small beginnings, with just five staff, Exscientia now employs over 400 people. Headquartered in England at the Oxford Science Park, Exscientia has a diverse global team with offices and labs in Scotland, Austria, Japan and the US.
Where it all started
Andrew Hopkins was a PhD student at Oxford in the 1990s, researching the design of new HIV drugs. He recognised the need to accelerate the identification of molecules with the potential to form the basis of more effective drugs.
After nearly a decade of working in industry, he returned to academia and moved to the University of Dundee, where his research had a clear goal. To find ways of mining and interpreting huge volumes of bioscience data much more quickly and efficiently than was possible using traditional human and computer-based methods.
In 2009 Hopkins applied for a small BBSRC grant, a pathfinder award for the experimental proof of concept for drug design. Following this, he was awarded a BBSRC Follow-on Fund award (£150,000) for ‘commercialising multitarget drug design’, a project that directly supported the formation of Exscientia.
Cumulatively, this backed his collaborative work on designing and testing novel compounds with machine learning algorithms. As a result, this produced an automated and adaptive methodology for designing drug ligands to multitarget profiles, which has a 75% prediction success rate. This was the necessary groundwork for Exscientia’s current AI technology for drug discovery.
In 2015, against stiff competition, Hopkins secured BBSRC’s Commercial Innovator of the Year award.
Andrew Hopkins went on to be elected a life-long Fellow of the Royal Society and the Academy of Medical Sciences in May 2023. He received the honours in recognition of his exceptional contributions to the advancement of science and technology. Around the same time, for its end-to-end AI-driven precision medicine platform Exscientia won the Prix Galien for Digital Health US in October 2022 and the Prix Galien UK in the same category in May 2023.
Impacts of the research
Successful speed boost
Exscientia’s drug hunters use its AI platform, Centaur, to help generate new molecules and drug targets that have a higher chance of translating successfully into clinical settings. The average industry timeline to discover a clinical development candidate takes around 4.5 years from synthesising between 2,500 and 5,000 molecules.
Based on performance to date, it takes Exscientia around 12 to 15 months from synthesising around 200 to 350 precision-designed compounds. This underscores how the company’s AI-driven approach is not only differentiated in terms of precision design but also faster and more efficient than conventional methods.
Exscientia has also raised multimillion investment in (and revenue from) AI-guided drug design. The rapid growth was detailed in the 2021 Research Excellence Framework (REF) impact case study. Since then, in early 2022, the company signed a landmark collaboration with Sanofi for up to 15 targets worth up to $5.2 billion. A few months earlier, Bristol Myers Squibb had expanded an ongoing collaboration with Exscientia to include multiple additional targets in oncology and immunology.
But it’s not always the volume of a collaboration that makes it compelling. In 2022, the biotech also expanded and signed new research collaborations with:
- the University of Oxford
- MD Anderson Cancer Center in Texas
- Charitè in Berlin, Germany, in 2023 to help expedite academic research with the help of advanced AI
In turn, these partnerships further inform Exscientia’s understanding of patient needs to ensure the solutions being worked on meet real-world medical needs and expectations.
Exscientia’s first AI-designed molecule was developed with Sumitomo Pharma Co., Ltd. (‘Sumitomo Pharma’) to treat obsessive-compulsive disorder. It took just 12 months to discover and represents the first ever AI-designed drug candidate to enter clinical trials. Sumitomo Pharma later announced that it was not continuing with this molecule. However, two additional compounds developed in collaboration with Sumitomo are ongoing in clinical trials.
The company was able to bolster its emerging pipeline with further wholly and partially owned novel drug candidates. In March 2023, it announced that five programmes across oncology and immunology and inflammation were either in clinical stage or investigational new drug (IND)-enabling studies. The latter involves a series of tests that measure a new drug’s safety before clinical trials commence and is a requirement for Food and Drug Administration approval.
For its A2a candidate, EXS21546, Exscientia has received clinical trial application approval to initiate the Phase 1/2 IGNITE trial.
EXS21546 is a selective antagonist of the adenosine A2a receptor, meaning it binds to the A2a receptor and prevents it from binding with adenosine. Blocking this receptor with different molecules has been an area of research for some time, including therapeutic applications. EXS21546 has been designed for anti-cancer immunotherapy.
During this trial, the team will continue to validate their adenosine patient selection biomarker discovered pre-clinically, aiming at enriching patients who are more likely to respond to treatment. The trial will enrol up to 110 patients.
A CDK7 inhibitor, GTAEXS617, developed in partnership with GT Apeiron, was also on track to enrol the first patient in a phase 1/2 study. This programme, too, showcases what makes an Exscientia drug unique: precision design aiming to transform patient benefit and patient selection strategies.
In October 2022, at the ENA congress, the company highlighted patient selection data. For the first time, Exscientia showed how it integrates machine learning, data from primary human tumour samples, and multiomics sequencing capabilities to predict the tumour efficacy of a drug candidate.
CDK7 is a specialised protein involved in DNA repair, the cell cycle, and regulating transcription (turning DNA into proteins). CDK7 is also an important marker for some types of cancer, with previous research suggesting that inhibition of CDK7 could be an effective therapy for HER2+ breast cancers.
With the CDK7 and A2a programmes, plus three in the clinical or IND-enabling stage including a PKC theta compound in-licensed by Bristol Myers Squibb, an important picture is painted. We can begin to see the hallmark of what an Exscientia drug may look like. It’s AI and machine learning not just applied in the processes of how a new medical entity is designed but also in how the right patients to benefit from that future drug are identified.
Supporting the next generation of researchers
It was as a DPhil student that Andrew Hopkins first formed his idea, which has revolutionised drug discovery since. Exscientia is now supporting the next generation of researchers through BBSRC’s Collaborative Training Partnership (CTP) scheme. This is in conjunction with a wider UK Research and Innovation (UKRI) Centres for Doctoral Training in AI investment.
Exscientia, in collaboration with Merck Sharp & Dohme Ltd, Heptares Therapeutics Limited, and the Queen Mary University of London, will be leading the BBSRC AI for Drug Discovery programme. BBSRC awarded £1.5 million of CTP funding, which will be used for 15 four-year PhD studentships in AI drug discovery. With a focus on interdisciplinarity, diversity and industry experience, the programme will equip students with the skills needed to work at the interface between AI technology and pharmaceuticals.
Ongoing PhD research within this programme includes, but is not limited to, exciting topics such as:
- next-generation text mining in drug discovery
- using AI to investigate and modulate gene function in patient populations and biobanks
- AI detection of druggable features from high content imaging data
Exscientia is also participating in several Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Programmes, too, building on earlier EPSRC support to Exscientia.
Where next for AI approaches
Using automated computer algorithms to detect patterns in big, complex datasets can slash up to two-thirds off the cost of early-stage drug development and drastically cut time-to-market. By enhancing and applying these faster learning techniques, Exscientia aims to contribute to better patient outcomes and to help healthcare budgets deliver better value for money.
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