An active learning platform for predictive oncology in rare cancers

Wesley Tansey, PhD
Principal Investigator and Assistant Attending, Computational Oncologist in the Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center. Dr. Tansey's work is focused on statistical machine learning methods and applications to cancer.
Friday, February 21, 2025
11:00am - 12:00pm
James H. Clark Center, Room S360, 3rd floor next to the Coffee Shop
Zoom link
Abstract:
This talk is about an adaptive platform for discovering rational drug combinations for rare cancers via ex vivo drug screens. Directly testing patient tissues ex vivo against panels of anti-cancer agents has been shown in multiple recent clinical trials to provide superior treatment guidance for patients with rare and high-risk cancers. All trials to date have focused on recommending a single agent, even though rationally designed combination therapies typically lead to better outcomes. The main bottleneck in these trials is the combinatorial explosion of exhaustively screening all combinations in a panel of drugs. We developed a new Bayesian active learning algorithm called BATCHIE that enables large-scale combination drug screens over huge libraries in cancer cell line experiments. Given a set of previous experiments, BATCHIE optimally designs the next batch of combination screens to maximize the utility of the batch. To bootstrap our predictive models, we collected and integrated more than 2M ex vivo drug screen results from two dozen published studies. The talk will conclude with initial results translating our platform into the clinic for patients with desmoplastic small round cell tumor, an ultra-rare cancer with no standard of care or targetable recurrent alterations.
Biography:
Wesley Tansey is an Assistant Professor at Memorial Sloan Kettering Cancer Center. His work focuses on probabilistic machine learning methods for modeling the tumor microenvironment, finding causal drivers of response to therapy, and discovering novel combination therapies. Before joining MSK, he completed his postdoctoral training at Columbia University under the supervision of David Blei and Raul Rabadan. Wesley holds a PhD in Computer Science from the University of Texas at Austin. He is the recipient of an NCI R01/R37 MERIT grant for scalable spatial modeling, serves as the co-director of the spatial data science core in the MSK U54 Center for Tumor-Immune Systems Biology, and is a PI in the data science hub of the Break Through Cancer Consortium.