A new artificial-intelligence-based tool has been developed to predict genomic subtypes of pancreatic cancer.
The innovation is a collaboration between AP-HP Greater Paris University Hospitals and Owkin, a start-up pioneering federated learning and Artificial Intelligence (AI) technologies for medical research and clinical development. The tool, which is a trained and validated AI model, can be used in clinical practice worldwide and opens the possibility of patient molecular stratification in routine care and for clinical trials.
The results of the companies’ ongoing strategic collaboration was presented at ASCO 2021. The abstract and poster, entitled “Identification of pancreatic adenocarcinoma molecular subtypes on histology slides using deep learning models”, demonstrates the first AI-based tool for predicting genomic subtypes of pancreatic cancer (PDAC) developed from machine learning applied to histology slides.
The value of machine learning
Gilles Wainrib, Chief Scientific Officer and Co-Founder of Owkin, said: “Our research shows AI can help connect information at the genomic, cellular and tissue levels, and how doing so can bring immediate value to make precision medicine a reality for patients. This study further underscores the value of using machine learning for identifying histo-genomic signals for cancer research and clinical development.”
Pancreatic adenocarcinoma is a complex and heterogeneous disease. Heterogeneity and tumour plasticity are likely major factors in the failure of many clinical trials. Multiomics studies have revealed two main tumour transcriptomic subtypes, Basal-like and Classical, that have been proposed to be predictive of patient response to first-line chemotherapy. The determination of these subtypes has been possible so far by RNA sequencing, a costly and complex technique that is not yet feasible in a clinical routine setting. Taken together, these factors make it compelling to use advanced AI methods with common histological slides, trained alongside crucial context from expert researchers, to address the unmet needs of patients.
Professor Jérôme Cros, Pathologist at Beaujon Hospital, Université de Paris, said: “This tool was developed using the unique histological and molecular resources from four APHP hospitals through a unique collaboration between pathologists from APHP, bioinformaticians from the group Carte d’Identité des Tumeurs de la Ligue Contre le Cancer, and data scientists from Owkin. It can remotely subtype tumour in minutes, paving the way for many applications from basic science to clinical practice.”
This research is part of a successful and ongoing collaboration between Owkin’s multidisciplinary teams and those of the AP-HP Greater Paris University Hospitals. Since 2019, the two have collaborated in the service of shared objectives: to improve patient care and facilitate the development of new drugs in three main areas (oncology, immunology, cardiology), and to democratise access to AI for researchers to promote innovation and medical advances.
