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Updated: May 31, 2026

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Mining small-molecule screens to repurpose drugs.

S Joshua Swamidass¹

¹Division of Laboratory and Genomic Medicine, Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA. swamidass@wustl.edu

Briefings in Bioinformatics

|July 1, 2011

Summary

Drug repurposing offers a faster, cheaper way to develop new medicines. While academic high-throughput screening data is available, methods to mine it for new drug uses have not yet accelerated discoveries as hoped.

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Last Updated: May 31, 2026

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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

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Published on: December 11, 2016

Area of Science:

Pharmacology
Drug Discovery
Medicinal Chemistry

Background:

Drug repurposing, identifying new uses for existing drugs, is a cost-effective strategy in pharmaceutical development.
Academic researchers now conduct high-throughput screening (HTS) of small molecules, generating valuable data.
This data is publicly accessible, offering opportunities for novel therapeutic discoveries.

Purpose of the Study:

To explore the potential of data mining methods for drug repurposing and repositioning.
To assess the impact of academic HTS data on accelerating the discovery of new drug indications.

Main Methods:

Analysis of publicly available academic high-throughput screening data.
Application of computational methods to mine screening data for potential drug repurposing candidates.

Main Results:

Several data mining approaches exist to analyze HTS data for drug repurposing.
Despite the availability of data and methods, the anticipated acceleration in discovering new drug uses has not yet been achieved.

Conclusions:

Drug repurposing is a promising strategy, but its full potential is hindered by current limitations in data utilization.
Further advancements in data mining and integration are needed to effectively translate academic HTS data into successful drug repositioning efforts.