Dr. Thomas J. Fuchs is a pioneer in computational pathology, and is the Founder and Chief Scientific Officer at Paige, the leader in computational pathology focused on building artificial intelligence (AI) to transform the clinical diagnosis and treatment of cancer. He is also an Associate Professor for Machine Learning at Weill-Cornell University, and Director of the Warren Alpert Center for Digital and Computational Pathology at Memorial Sloan Kettering Cancer Center in New York City.
Dr. Fuchs previously served as a research technologist at NASA’s Jet Propulsion Laboratory in Pasadena focusing on space exploration research. He earned his PhD (Dr.Sc.) from ETH and received his MSc degree (Dipl.-Ing.) from Technical University Graz. Dr. Fuchs was named one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare in 2019.
TALK TITLE
The Digital Biomarker Revolution: How Large-Scale, Clinical-Grade AI Enables Novel CDXs from Histopathology
ABSTRACT
At NASA we were confronted daily with Goldin’s modified adage: “faster, better, cheaper; pick two”. In healthcare it is becoming drastically more important with the development and validation of increasingly more complex biomarkers for prognostic and predictive purposes. This idea becomes even more relevant, as multiple testing methodologies are required to generate all the information needed to make treatment decisions. Many hospital pathology labs are not equipped to perform all the recommended testing, necessitating the tests to be sent out, limiting patient access, and utilizing expensive testing with no promise of an actionable result.
Digital Biomarkers are drastically changing the CDX landscape. These novel data-driven approaches build on Paige’s experience with large-scale clinical systems that are constantly validated on tens of thousands of patients. Paige is working with biopharma partners to develop the next generation of digital biomarkers that empowers pathologists, facilitates patient access to treatment and trials, differentiates drug pipelines and portfolios from the competition, and maximizes both biopharma R&D and commercialization ROI.