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24 - RNAi and the drug discovery process
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- By Steven A. Haney, Wyeth Research, Peter Lapan, Wyeth Research, Jeff Aalfs, Wyeth Research, Chris Miller, Wyeth Research, Paul Yaworsky, Wyeth Research, Chris Childs, Wyeth Research
- Edited by Krishnarao Appasani, GeneExpression Systems, Inc., Massachusetts
- Foreword by Andrew Fire, Stanford University, California, Marshall Nirenberg
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- Book:
- RNA Interference Technology
- Published online:
- 31 July 2009
- Print publication:
- 17 January 2005, pp 331-346
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- Chapter
- Export citation
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Summary
Introduction
Drug discovery is a complex process that seeks to identify therapeutics for treating human disease. It has very high failure rate, and by one estimate, the total cost for a therapeutic successfully brought to market is 803 million dollars (DiMasi et al., 2003). Failure occurs at all points in the process, with failures at the pre-development stages being the most common, and failures at the clinical stages being the most costly. Scientists working in drug discovery are continually challenged to identify ways to improve the process. Current efforts are largely “target-based” approaches. Once chosen, the target may be studied in vitro for more than a year, and in model systems of the disease for up to four years. Errors in determining whether a given target is truly effective in treating a disease may not be detected until Phase II or Phase III clinical studies, which follow many years of study and a financial investment of tens or hundreds of millions of dollars. As such, target validation is a critical aspect of the drug discovery process.
The pharmaceutical industry has invested heavily in genomics because of its promise to provide a continuing supply of drug targets (Wiley, 1998; Ohlstein et al., 2000; Baba, 2001). Implicit in this investment has been the expectation that the targets provided by genomics are highly validated (Debouck and Metcalf, 2000). Thus, genomics has grown broadly across the drug discovery process, from target identification to phamacogenomics.