Targeted therapeutics have revolutionized the way we approach cancer treatment, yet there remains a significant opportunity to build and improve upon our existing understanding of disease biology, treatment selection, and patient response.  Targeting of the tumor microenvironment (TME) is recognized as a promising area in oncology drug development due to the critical role of the TME, including tumor cells, stromal features, nuclear features, immune cells, tertiary lymphoid structures, and other important features, in regulating disease progression and therapeutic response. However, quantifiable, reproducible, and scalable measurement and characterization of the TME has been challenging with existing methods, such as manual pathology assessment.
 
In this session, PathAI will discuss the application of its AI models to research in the TME and identification of novel biomarkers for potential use in drug development. We will also have a discussion with pharma leaders on the important of advancing our understanding of the TME for the continued evolution of targeted drug development.

You’ll discover:

• How AI is key to analyzing and unlocking the secrets of disease biology within the TME from H&E whole-slide images
• The latest TME data revealing novel biomarkers and treatment targets across different oncology indications
• How biopharma companies are leveraging and incorporating AI technology across the drug discovery and development lifecycle

Featured Speakers

Ilan Wapinski is VP of Translational Research and Algorithm Products at PathAI where he heads the Translational Sciences organization, including the Biomedical Data Sciences and Scientific Program, Data and Communications Management teams. Ilan’s teams oversee the day-to-day scientific engagements with external partners as well as internal R&D initiatives. After completing his PhD in Computer Science focusing on computational genomics research at the Broad Institute, Ilan was a departmental post-doctoral fellow at the Department of Systems Biology at Harvard Medical School. Prior to joining PathAI, Ilan was the Director of Development at enEvolv, focusing on applying high throughput approaches to engineering new biological capabilities in microbial organisms. Ilan has a BA in Computer Science and Philosophy from Columbia University.

Suzana Couto is Head of Pathology at Genmab where she leads and collaborates with talented scientists to advance a diverse pipeline of biologics. Dr. Couto has over 15-years of experience in biomarker assay development focusing on immunology and oncology. She has spent her career leading teams responsible for a wide range of IHC, multiplex IF, and digital pathology applications. Prior to joining Genmab she led teams at Memorial Sloan-Kettering Cancer Center, Genentech and Celgene. Digital pathology, machine learning, and deep learning have been an essential part of her work. She believes the future of pathology lies in leveraging computational and AI workflows to scale human knowledge, integrate a large amount of information, and help advance the field of biomedical research faster than ever before.

Laura Dillon is the Head of Translational Biomarkers at Parthenon Therapeutics, a Boston-based precision oncology biotech, where she is responsible for designing and implementing Parthenon's biomarker strategy. She has over 15 years of experience in industry, academia, and government. Prior to joining Parthenon, Laura was the Director of Pathology Data Strategy at AstraZeneca, focusing on the development of novel methodologies to extract information from imaging datasets and the implementation of non-invasive bioimaging techniques to advance the drug development pipeline. Laura has a Ph.D. in Bioinformatics and Genomics from the University of Maryland.

Benjamin Chen is a Senior Director of Translational Medicine at Bristol Myers Squibb, located in Cambridge, MA, where he leads a diverse team of scientists to develop novel, experimental approaches to studying biomarkers of the tumor microenvironment and mechanisms of action for specific assets. Particular interest is directed toward analyzing spatial biomarker patterns and machine learning to leverage digital pathology capabilities in the setting of our clinical trials. Ben received his MD and PhD from Northwestern University where he worked on the basic biochemistry of influenza viruses. He then completed an Anatomic Pathology residency program at Brigham and Women’s Hospital, followed by a fellowship in Hematopathology. Before joining BMS, Ben was an Assistant Professor of Pathology at UMass Medical School in Worcester, MA, where his clinical practice focused on Heme, GI, and Molecular pathology.

Register below to watch on-demand.

Already registered? Click here to login.