VIENNA & OXFORD, UK–(BUSINESS WIRE)–Exscientia (Nasdaq: EXAI), ETH Zurich, the Medical University of Vienna and the Center for Molecular Medicine (CeMM) today announced a new publication in detection of blood cancera journal of the American Association for Cancer Research, entitled “Deep Morphology Learning advances precision medicine through image-based ex vivo drug testing“ from the laboratory of Prof. Berend Snijder. This post hoc analysis builds on the transformative work of the EXALT-1 study, published in Cancer Discovery, by using deep learning algorithms to classify complex cell morphologies in patient cancer tissue samples into disease “morphotypes”. .
EXALT-1 was the first prospective study to demonstrate significantly improved outcomes for late-stage hematologic cancer patients using an AI-powered precision medicine platform to provide personalized treatment recommendations versus physician treatment choice. In EXALT-1, 40% of patients had an exceptional response that lasted at least three times longer than expected for their disease. The post hoc analysis published today in detection of blood cancer shows that combining the technology used in EXALT-1 with new deep learning advances that exploit cell-specific features in high-content images demonstrated potential to further improve these patient outcomes.
“Following the results of the EXALT-1 study, these results further validate our AI-driven precision medicine platform’s ability to identify highly actionable clinical treatment recommendations for blood cancer, deepen our insights, and enhance the platform’s clinical predictive power to help patients.” said Gregory Vladimer, Ph.D., VP of Translational Research at Exscientia and co-inventor of the platform technology. “Cell morphology, or assessing the properties of cells, is fundamental to diagnosing cancer. As part of this research, we were able to use deep learning within the platform to improve our ability to identify personalized cancer treatments, leading to improved clinical outcomes for patients. At Exscientia, we look forward to expanding the platform’s applications to bring personalized medicine to a wider population.”
“We believe that performing drug screening directly in tumor tissues from cancer patients represents a major advance in understanding tumor complexity compared to traditional cell model systems. The fact that we can now harness the power of deep learning to convert these terabytes of images into actionable insights is very exciting indeed,” added Prof. Berend Snijder, Principal Investigator at the Institute of Molecular Systems Biology at ETH Zurich Switzerland, added.
The impact of deep learning on the clinical predictive power of ex vivo Drug screening was evaluated in a post-hoc analysis of 66 patients over a three-year period in a combined data set of 1.3 billion patient cells from 136 ex vivo tested drugs for hematological diagnoses including acute myeloid leukemia, T-cell lymphoma, diffuse large B-cell lymphoma, chronic lymphocytic leukemia, and multiple myeloma. Patients receiving treatments recommended by the platform’s immunofluorescence analysis or deep learning on cell morphologies showed an increased rate of achieving an exceptional clinical response, defined as a progression-free survival time that lasted three times longer than expected for each patient’s specific disease. Post-hoc analysis confirmed that clinical predictions became more accurate when drug toxicity to the normal cells in the tested patient sample was also taken into account.
Exscientia’s precision medicine platform uses custom deep learning and computer vision techniques to extract meaningful single-cell data from high-content images of individual patient tissue samples. This analysis provides clinically relevant insights into which treatments provide the most benefit for an individual patient. Further evaluation of individual patient outcomes through Exscientia’s genomics and transcriptomics capabilities can help Exscientia better understand which other patients might benefit from similar treatments. The underlying technology was developed by Dr. Gregory Vladimer and Prof. Berend Snijder during their work in the laboratory of Giulio Superti-Furga at the CeMM Research Center for Molecular Medicine in Austria.
Exscientia is an AI-driven pharmatech company dedicated to discovering, designing and developing the best possible medicines in the fastest and most effective way. Exscientia has developed the first-ever precision functional oncology platform to successfully guide treatment choice and improve patient outcomes in a prospective interventional clinical trial and bring AI-engineered small molecules to the clinical setting. Our internal pipeline is focused on leveraging our precision medicine platform in oncology, while our partnered pipeline is expanding our approach into other therapeutic areas. We believe that by pioneering a new approach to drug manufacturing, the best ideas in science can quickly become the best medicines for patients.
Exscientia is headquartered in Oxford (England, UK) and has offices in Vienna (Austria), Dundee (Scotland, UK), Boston (Mass., USA), Miami (Fla., USA), Cambridge (England, UK) and Osaka (Japan).
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