SEMINAR S’23-Data-Driven Modeling and Decision Support for Personalized Precision Oncology
- Post by: Bahareh Arghavani
- February 27, 2023
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Presenter: Binesh Kumar (PhD Candidate – SAIL Lab)
Time: Friday 03/07/2023, 5pm – 6pm ET
Recording: TBA
Abstract:
Cancer is one of the leading causes of death worldwide, causing nearly 10 million deaths in 2020, or almost one in six. The heterogeneity in cancer physiology between patients and the cytotoxic nature of oncology therapies requires the care providers to optimize and personalize the drug choices and dosimetry to maximize the disease-free survival rate. Molecular-level characterization of cancerous tumors heavily improves the treatment strategies by targeting genetic mutations through individualized therapy. Theranostics is a novel therapy regime in precision oncology where pairs of radiopharmaceuticals are used for diagnostic and therapeutic purposes. The success of this therapy relies on identifying the optimal care plan for each patient-level factor, tumor burden, Organs At Risk (OAR) radiation tolerance, and complex biological clearance and uptake of the therapeutics.
This webinar aims to provide an overview of research performed by Secure and Assured Intelligent Lab members to advance the state-of-the-art in Theranostics with data-driven solutions with a mission to create equitable cancer care.
Bio:
Binesh Kumar is a Ph.D. candidate at Secure and Assured Intelligent Learning Lab (SAIL Lab), University of New Haven. His research at SAIL Lab is focused on developing data-driven decision support to advance access to precision oncology. He is also a Sr. Principal research engineer at Medtronic, a leading medical devices manufacturer, where he works on developing solutions that improve minimally invasive surgical therapies.