Exscientia Initiates Clinical Study to Further Evaluate Functional Precision Medicine Platform in Cancer Patients

Multicentre EXCYTE-2 study to evaluate precision medicine platform in patients with acute myeloid leukaemia

Supports ongoing development of LSD1 inhibitor (EXS74539) currently in preclinical development

Exscientia plc (Nasdaq: EXAI) today announced the initiation of EXCYTE-2, an observational clinical study in acute myeloid leukaemia (AML) to investigate the relationship between ex vivo drug response (EVDR) measured in primary blood or bone marrow samples using the company’s deep learning, single-cell precision medicine platform and actual patient clinical response.

The EXCYTE-2 study will collect blood and bone marrow samples from first-line patients with AML, with an option to expand to second-line patients. Both patient groups represent areas of high unmet medical need with low survival rates. Biobanked tissue samples, alongside clinical patient data including diagnostic and outcome data, will be collected from treatment centres with samples to be processed by Exscientia or partner laboratories. These partner laboratories will be using Exscientia’s cloud-based AI to analyse samples remotely.

In addition, the study allows for the evaluation of activity of EXS74539 (‘539), Exscientia’s LSD1 inhibitor, in a large clinically annotated sample set. This work has the potential to support the ongoing development of ‘539, particularly in the selection of patients for future clinical trials.

The EXCYTE-2 study builds on other previously initiated precision medicine focused studies, including EXALT-1 and EXCYTE-1. The EXALT-1 trial was an interventional trial and the first trial to leverage analysis of drug action in primary human cancer tissues using high content imaging and deep learning to guide treatment selection and improve outcomes in patients with late-stage haematological cancers. EXCYTE-2 will leverage the progress the company has made on its AI-driven precision medicine platform since the EXALT-1 trial was completed and will specifically evaluate earlier stage patient populations. EXCYTE-1 is an ongoing prospective observational study focused on ovarian cancer.

“This study continues our focus on establishing AI-led ex vivo drug testing in human tissue samples as the most comprehensive strategy for preclinical testing of novel therapies, additive to mouse and other animal models,” said Dr. Nikolaus Krall, EVP of Precision Medicine at Exscientia. “A robust correlation between our platform’s results and clinical outcomes has the potential to change clinical practice for the benefit of AML patients.”

About EXCYTE-2

The EXCYTE-2 trial is a multicentre two-phase study evaluating the correlation between clinical and ex vivo drug response as measured using Exscientia’s AI-based precision medicine platform in AML.

Initially the trial will focus on newly diagnosed AML patients, with the option to include relapsing/refractory AML patients after an interim analysis. Blood or bone marrow collected from patients prior to initiation of therapy will be obtained from biobanks. The EVDR of commonly used standard of care therapies will then be evaluated in these patient samples by Exscientia’s AI-based precision medicine platform. These results will be compared against patients’ clinical response to treatment, which will be chosen and evaluated by physicians blinded to the EVDR data. Complete remission will be used as the primary clinical endpoint and assessed to monitor association with EVDR. Measurable residual disease is included as a secondary clinical endpoint.

About Exscientia

Exscientia is an AI-driven precision medicine company committed to discovering, designing and developing the best possible drugs in the fastest and most effective manner. Exscientia developed the first-ever functional precision oncology platform to successfully guide treatment selection and improve patient outcomes in a prospective interventional clinical study, as well as to progress AI-designed small molecules into the clinical setting. Our internal pipeline is focused on leveraging our precision medicine platform in oncology, while our partnered pipeline broadens our approach to other therapeutic areas. By pioneering a new approach to medicine creation, we believe the best ideas of science can rapidly become the best medicines for patients. For more information visit us on www.exscientia.ai or follow us on LinkedIn @ex-scientia and X @exscientiaAI.

Forward-looking statements

This press release contains forward-looking statements as that term is defined in the Private Securities Litigation Reform Act of 1995, including with respect to the progress of discovery and development of candidate molecules. Any statement describing Exscientia’s goals, plans, expectations, projections, intentions or beliefs is a forward-looking statement and should be considered an at-risk statement. Such statements are subject to a number of risks, uncertainties and assumptions, including those related to the process of discovering, developing and commercialising product candidates that are safe and effective for use as human therapeutics; and the endeavour of building a business around such product candidates. In light of these risks and uncertainties, and other risks and uncertainties that are described in the Risk Factors section and other sections of Exscientia’s Annual Report on Form 20-F, filed with the Securities and Exchange Commission (SEC) on March 23, 2023 (File No. 001-40850), and other filings that Exscientia makes with the SEC from time to time (which are available at https://www.sec.gov/), the events and circumstances discussed in such forward-looking statements may not occur, and Exscientia’s actual results could differ materially and adversely from those anticipated or implied thereby. Although Exscientia’s forward-looking statements reflect the good faith judgement of its management, these statements are based only on facts and factors currently known by the Company. As a result, you are cautioned not to rely on these forward-looking statements.

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