Work

Growing PAINS in Academic Drug Discovery

Year: 2011

Type: article

Abstract: In a recent article it was argued that compounds published as drug leads by academic laboratories commonly contain functionality that identifies them as nonspecific 'pan-assay interference compounds' (PAINS). The article raises broad questions about why best practices for hit and lead qualification that are well known in industry are not more widely employed in academia, as well as about the role of journals in publishing manuscripts that report drug leads of little potential value. Barriers to adoption of best practices for some academic drug-discovery researchers include knowledge gaps and infrastructure deficiencies, but they also arise from fundamental differences in how academic research is structured and how success is measured. Academic drug discovery should not seek to become identical to commercial pharmaceutical research, but we can do a better job of assessing and communicating the true potential of the drug leads we publish, thereby reducing the wastage of resources on nonviable compounds.

Source: Future Medicinal Chemistry

DOI: 10.4155/fmc.11.44

Author: Adrian Whitty

Institution: Boston University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Institute of General Medical Sciences

Award: Design of Macrocyclic Inhibitors of the NEMO/IKKa/b Protein-Protein Interaction