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Drug Discovery: Overview

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

Drug Regulation

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Drug regulation encompasses the management of drug usage by evaluating its safety and efficacy through assessments conducted by regulatory authorities. Regrettably, the history of drug regulation is marred by several catastrophic events. One such incident is the Elixir Sulfanilamide tragedy, in which the toxic compound diethyl glycol was included in a sweet-tasting medication, leading to numerous fatalities. This event prompted the enactment of the Food, Drug, and Cosmetic Act in 1938. Under...

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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...

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Updated: May 18, 2026

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

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

Published on: December 11, 2016

Why open drug discovery needs four simple rules for licensing data and models.

Antony J Williams¹, John Wilbanks, Sean Ekins

¹Royal Society of Chemistry, Wake Forest, North Carolina, USA. tony27587@gmail.com

Plos Computational Biology

|October 3, 2012

Summary

Data licensing is crucial for open drug discovery. We propose four rules to ensure data accessibility and usability in scientific databases, preventing future integration hurdles.

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Last Updated: May 18, 2026

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

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

Published on: December 11, 2016

Area of Science:

Biomedical Informatics
Data Science
Drug Discovery

Background:

Scientific databases have rapidly expanded online, increasing data accessibility.
Data licensing is an emerging challenge for integrating and utilizing scientific data.
Ensuring data provenance and usability is vital for scientific progress.

Purpose of the Study:

To address potential hurdles in data licensing for open drug discovery.
To propose a framework for licensing scientific data to promote integration and usability.
To encourage scientists to consider data licensing in future database construction.

Main Methods:

Formulation of four proposed rules for data licensing.
Analysis of the impact of licensing on data accessibility and integration.
Consideration of extending licensing principles to computational models.

Main Results:

A set of four rules for licensing data in open drug discovery has been formulated.
These rules aim to facilitate data integration and usability.
The proposed framework can be extended to computational models derived from data.

Conclusions:

Data licensing is a critical factor for the future of open drug discovery and scientific database integration.
Adoption of standardized licensing rules can prevent future usability and progress barriers.
Scientists must proactively consider data licensing when developing or reusing scientific databases.