Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10886635 | Drug Discovery Today | 2005 | 7 Pages |
Abstract
The process of discovering and developing new drugs is long, costly and risk-laden. Faced with a wealth of newly discovered compounds, industrial scientists need to target resources carefully to discern the key attributes of a drug candidate and to make informed decisions. Here, we describe a quantitative approach to modelling the risk associated with drug development as a tool for scenario analysis concerning the probability of success of a compound as a potential pharmaceutical agent. We bring together the three strands of manufacture, clinical effectiveness and financial returns. This approach involves the application of a Bayesian Network. A simulation model is demonstrated with an implementation in MS Excel using the modelling engine Crystal Ball.
Keywords
Related Topics
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Biochemistry, Genetics and Molecular Biology
Biotechnology
Authors
Zhengru Tang, Mark J. Taylor, Paulo Lisboa, Mark Dyas,