Related Experiment Video
Updated: Feb 26, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Unlocking the potential of computational phenotypic drug discovery: methods, challenges, and future directions
Shivam Kumar1, Aman Pal1, Samrat Chatterjee2
1Complex Analysis Group, Computational and Mathematical Biology Centre, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd milestone, Faridabad-Gurgaon Expressway, Faridabad, 121001, India.
None:
Phenotypic drug discovery (PDD) identifies new drugs by observing the effects of compounds on living systems without prior knowledge of their targets. Advances in biological data and machine learning have made PDD more systematic and data-driven. This review outlines a computational framework, including phenotype representations, key tools, and public datasets. It also discusses major challenges and strategies to improve PDD's efficiency and translational potential, offering a practical guide for researchers in the field.
More Related Videos
08:04In Vitro Three-Dimensional Sprouting Assay of Angiogenesis Using Mouse Embryonic Stem Cells for Vascular Disease Modeling and Drug Testing
Published on: May 11, 2021
08:49Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Related Concept Videos
Drug Discovery: Overview
Pharmacogenomics: Identification of New Drug Targets
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu
Pharmacogenetics and Pharmacogenomics: Overview
Pharmacokinetic–Pharmacodynamic Relationship: Problems
Principles of Pharmacogenetics: Types of Genetic Variants