title: Quantitative structure-activity relationship models that stand the test of time.
abstract: The pharmaceutical industry is in a period of intense change. While this has many drivers, attrition through the development process continues to be an important pressure. The emerging definitions of "compound quality" that are based on retrospective analyses of developmental attrition have highlighted a new direction for medicinal chemistry and the paradigm of "quality at the point of design". The time has come for retrospective analyses to catalyze prospective action. Quality at the point of design places pressure on the quality of our predictive models. Empirical QSAR models when built with care provide true predictive control, but their accuracy and precision can be improved. Here we describe AstraZeneca's experience of automation in QSAR model building and validation, and how an informatics system can provide a step-change in predictive power to project design teams, if they choose to use it.
authors: AstraZeneca R&D Mölndal, Pepparedsleden 1, Mölndal, 431 83 Sweden. Andy.davis@astrazeneca.com
authors: Andrew M
authors: AM
authors: Davis
authors: David J
authors: DJ
authors: Wood
mesh_terms: D000465:Algorithms; D001331:Automation; D001499:Bayes Theorem; D002626:Chemistry, Pharmaceutical / Q000379:methods; D003198:Computer Simulation; D015195:Drug Design; D006801:Humans; D016018:Least-Squares Analysis; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D013678:Technology, Pharmaceutical / Q000379:methods