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2020 Jeff & Loyd Zisk-PCF Young Investigator Award

Antonio Rodriguez-Calero, MD

University of Bern

Mentors: Mark Rubin, MD; Savatore Piscuoglio, PhD

Molecular Pathology-Artificial Intelligence Approach to Therapy Response Prediction for Castration Resistant Prostate Cancer

Description:

  • In the past few years, a multitude of new therapies have become approved for patients with advanced prostate cancer. However, how to choose between therapies at the time of each new treatment decision for individual patients, remains unclear. Predictive biomarkers are urgently needed to guide appropriate selection of the next best therapy for each patient.
  • Dr. Antonio Rodriguez-Calero is developing a new classification system for metastatic castration resistant prostate cancer (mCRPC), which will improve precision medicine treatment decisions for patients.
  • In this project, Dr. Rodriguez-Calero will integrate comprehensive tumor genomic and gene expression data, pathology, and clinical data from patients on a recently completed precision medicine clinical trial, and use this in combination with machine learning, to develop a new classifier for mCRPC that predicts patient treatment responses and outcomes.
  • This classifier will be validated in other patient cohorts and simplified to include only the most critical data elements.
  • If successful, this project will ultimately result in a molecular testing kit that can be used in clinics to select optimal standard treatments and improve clinical trial design for patients with advanced prostate cancer.

What this means to patients: Dr. Antonio Rodriguez-Calero is developing a new artificial intelligence-based classification system for mCRPC based on molecular, pathology, and clinical data that will improve precision medicine treatment selection for patients with advanced prostate cancer.