Literature DB >> 23197038

Reducing safety-related drug attrition: the use of in vitro pharmacological profiling.

Joanne Bowes1, Andrew J Brown, Jacques Hamon, Wolfgang Jarolimek, Arun Sridhar, Gareth Waldron, Steven Whitebread.   

Abstract

In vitro pharmacological profiling is increasingly being used earlier in the drug discovery process to identify undesirable off-target activity profiles that could hinder or halt the development of candidate drugs or even lead to market withdrawal if discovered after a drug is approved. Here, for the first time, the rationale, strategies and methodologies for in vitro pharmacological profiling at four major pharmaceutical companies (AstraZeneca, GlaxoSmithKline, Novartis and Pfizer) are presented and illustrated with examples of their impact on the drug discovery process. We hope that this will enable other companies and academic institutions to benefit from this knowledge and consider joining us in our collaborative knowledge sharing.

Mesh:

Year:  2012        PMID: 23197038     DOI: 10.1038/nrd3845

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN: 1474-1776            Impact factor:   84.694


  94 in total

Review 1.  Cardiac opioids.

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Journal:  Proc Soc Exp Biol Med       Date:  2000-05

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  169 in total

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Review 6.  An analysis of the attrition of drug candidates from four major pharmaceutical companies.

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