Exscientia (Nasdaq: EXAI), ETH Zurich, the Medical University of Vienna and the Center for Molecular Medicine (CeMM) of the Austrian Academy of Sciences today announced a new publication in Blood Cancer Discoverya journal of the American Association for Cancer Research, titled “Deep Morphology Learning Enhances Precision Medicine by Image-Based Ex Vivo Drug Testing” known from the laboratory of Prof. Berend Snijder. The 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 tissue samples from cancer patients into disease “morphotypes”. .
EXALT-1 was the first prospective study to show significantly better outcomes for patients with late-stage hematologic cancer, using an AI-powered precision medicine platform to guide personalized treatment recommendations—compared to the physician’s treatment of choice. In EXALT-1, 40% of patients had an exceptional response that lasted at least three times longer than expected for their disease. The today in Blood Cancer Discovery A published post-hoc analysis shows that combining the technology used in EXALT-1 with new deep learning advances that exploit cell-specific features in high-resolution images has the potential to improve patient outcomes even further.
“Following the results of the EXALT-1 study, these results further validate our AI-powered precision medicine platform’s ability to identify highly actionable clinical treatment recommendations for blood cancers. This deepens our insights and increases the clinical predictive power of the platform to helping patients,” says Dr. Gregory Vladimer, VP Translational Research at Exscientia and co-inventor of the platform technology. “Cell morphology, which is the assessment of the properties of cells, is fundamental to the diagnosis of cancer. This research allowed us to use deep learning within the platform to improve our ability to identify personalized cancer therapies, leading to better clinical results for patients. At Exscientia, we look forward to expanding the applications of the platform to bring personalized medicine to a broader population.”
“We believe that performing drug screening directly in the tumor tissue of cancer patients is a major advance in understanding the complexity of tumors compared to traditional cell model systems. The fact that we can now use the power of deep learning to capture these terabytes of images Converting them into actionable insights is very exciting indeed,” added Prof. Berend Snijder, Principal Investigator at the Institute for Molecular Systems Biology at ETH Zurich.
The impact of deep learning on clinical predictive power ex vivo-Drug screenings were performed in a post-hoc analysis of 66 patients over a three-year period in a combined dataset of 1.3 billion patient cells across 136 ex vivo-assessed tested agents for hematological diagnoses including acute myeloid leukemia, T-cell lymphoma, diffuse large B-cell lymphoma, chronic lymphocytic leukemia, and multiple myeloma. Patients who received treatment recommended by the platform’s immunofluorescence analysis or deep learning of cell morphologies demonstrated a higher rate of exceptional clinical response, defined as a progression-free survival time that lasted three times longer than expected for the patient’s specific disease. Post-hoc analysis confirmed that the clinical predictions became more accurate when the drug’s toxicity to the normal cells within the patient sample tested 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-resolution images of individual tissue samples from patients. This analysis provides clinically relevant insights into which treatments provide the most benefit for an individual patient. Further evaluating 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 as part of their work in the laboratory of Giulio Superti-Furga at the CeMM Research Center for Molecular Medicine in Austria.
About Exscientia
Exscientia is a pharmaceutical technology company dedicated to discovering, designing and developing the best possible medicines in the fastest and most effective way using AI. Exscientia has developed the first functional precision oncology platform that successfully guides treatment choices and improves patient outcomes in a prospective clinical intervention study. She is also advancing small molecule compounds developed with the help of AI to clinical development. Our internal pipeline is focused on leveraging our precision medicine platform in oncology, while our partnered pipeline is expanding our approach to other therapeutic areas. We believe that with our new approach to creating medicines, the best ideas in science can be quickly translated into the best medicines for patients.
Exscientia is headquartered in Oxford (UK) and has offices in Vienna (Austria), Dundee (UK), Boston (Massachussetts, USA), Miami (Florida, USA), Cambridge (UK) and Osaka (Japan).
Visit us at https://www.exscientia.ai or follow us on Twitter @exscientiaAI.
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