What is it about?
We developed a computational approach to facilitate quick drug discovery for advanced prostate cancer. By integrating patient biology data and large-scale drug screen databases we identified potentially efficacious drugs for therapy-resistant prostate cancer. Specifically, we identified a drug named COL-3 and validated its efficacy through additional experiments.
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Why is it important?
Traditional drug research and development pipelines are costly and time consuming, thus highlighting a need for quicker identification for aggressive diseases such as castration-resistant prostate cancer (CRPC). In this paper we utilized a computational method to repurpose currently existing drugs. Many existing drugs already have established safety profiles and/or have gained approval for patient care; consequently repurposing of these drugs can meet the urgent demand for treatments in CRPC.
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This page is a summary of: Computational drug discovery for castration-resistant prostate cancers through in vitro drug response modeling, Proceedings of the National Academy of Sciences, April 2023, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2218522120.
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