Abstract
Systematic engagement of statisticians in preclinical research could help address the weaknesses that are undermining the likelihood of subsequent success in drug discovery and development.
References
Begley, G. C. & Ellis, L. M. Raise standards for preclinical cancer research. Nature 483, 531–533 (2012).
Prinz, F., Schlange, T. & Asadullah, K. Believe it or not: how much can we rely on published data on potential drug targets? Nature Rev. Drug Discov. 10, 712 (2011).
Ioannidis, J. P. Why most published research findings are false. PLoS Med. 2, e124 (2005).
Lendrem, D. Statistical support to non-clinical. Pharm. Stat. 1, 71–73 (2002).
Marquardt, D. W. The importance of statisticians. J. Am. Stat. Assoc. 82, 1–7 (1987).
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Ian S. Peers, Peter R. Ceuppens and Chris Harbron all hold shares in AstraZeneca.
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Peers, I., Ceuppens, P. & Harbron, C. In search of preclinical robustness. Nat Rev Drug Discov 11, 733–734 (2012). https://doi.org/10.1038/nrd3849
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DOI: https://doi.org/10.1038/nrd3849
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