To measure is to know: an approach to CADD performance metrics

Deborah Loughney; Brian L Claus; Stephen R Johnson

doi:10.1016/j.drudis.2011.05.003

To measure is to know: an approach to CADD performance metrics

Drug Discov Today. 2011 Jul;16(13-14):548-54. doi: 10.1016/j.drudis.2011.05.003. Epub 2011 May 13.

Authors

Deborah Loughney¹, Brian L Claus, Stephen R Johnson

Affiliation

¹ Computer-Assisted Drug Design, Molecular Sciences and Candidate Optimization, Bristol-Myers Squibb, PO Box 5400, Princeton, NJ 08543-5400, USA.

PMID: 21605697
DOI: 10.1016/j.drudis.2011.05.003

Abstract

With the financial and productivity challenges currently facing the pharmaceutical industry, there is constant pressure to justify resources and improve efficiency. With process-driven activities, understanding the contribution of these resources is reasonably straightforward. By contrast, measuring the contribution of knowledge workers is less obvious. Here, we present an impact-oriented approach to assessing the performance of an industrial computer-assisted drug design group. We discuss how these metrics are used to understand and optimize resource allocation in support of drug discovery programs.

MeSH terms

Computer-Aided Design*
Drug Design*
Drug Discovery / methods
Drug Industry / economics
Drug Industry / methods*
Efficiency, Organizational
Humans
Research / economics
Research Design