Predicting new drug indications for prostate cancer: The integration of an in silico proteochemometric network pharmacology platform with patient‐derived primary prostate cells

Abstract

Drug repurposing enables the discovery of potential cancer treatments using publically available data from over 4000 published Food and Drug Administration approved and experimental drugs. However, the ability to effectively evaluate the drug's efficacy remains a challenge. Impediments to broad applicability include inaccuracies in many of the computational drug‐target algorithms and a lack of clinically relevant biologic modeling systems to validate the computational data for subsequent translation.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 06, 2020
Source ID
10.1002/pros.24050

Entities

People

  • Adam Feldman
  • Aisha Naeem
  • Chris Albanese
  • D. Kumar
  • Erika Parasido
  • Henry Walthieu
  • Lucas Tricoli
  • Maria Avantaggiati
  • Muhammad S. Noon
  • Olga Rodríguez
  • Richard J. Lee
  • Sivanesan Dakshanamurthy
  • Stephen Byers

Organizations

  • Georgetown University
  • Massachusetts General Hospital
  • Ministry of Public Health
  • National Institutes of Health
  • North Carolina College
  • United States Department of Defense
  • University of Arizona

Tags

Fields of Study

  • Biology
  • Medicine

Readers

  • Computational Modeling and Simulation
  • Molecular Genetics
  • Oncology (Cancer Research).