Abstract
Despite rapid growth in our knowledge of potential disease targets following completion of the first drafts of the human genome over 10 years ago, the success rate of new therapeutic discovery has been frustratingly low. In addition to the widely reported costs and single-digit success rate of the entire drug discovery and development process, it has recently been estimated that even the preliminary process of transitioning new targets to preclinical development succeeds in less than 3% of attempts [Vogel (ed.) Drug Discovery and Evaluation: Pharmacological Assays. 3rd ed. Springer, Berlin (2007)]. At these early stages of development, poor understanding of therapeutic mechanisms and lack of compound selectivity are often to blame for failed compounds. It is worth noting than the emerging class of nucleic acid-based therapeutics, including miRNA and RNAi, are likely to be even more prone to unexpected system-wide and off-target activities. For all therapeutic approaches, it is clear that discovery strategies permitting the assessment of drug targets in their native context are required. At the same time, these strategies need to retain the high throughput of current reductionist approaches to enable broad assessment of chemical space for small molecule and genetic therapeutics. We describe here an integrated system based on high-content cellular analysis combined with system-wide pathway interrogation. The platform can be applied to novel therapeutic target and drug candidate identification, and for providing detailed mechanistic and selectivity information at an early stage of development.
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Westwick, J.K., Lamerdin, J.E. (2011). Improving Drug Discovery with Contextual Assays and Cellular Systems Analysis. In: Luttrell, L., Ferguson, S. (eds) Signal Transduction Protocols. Methods in Molecular Biology, vol 756. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-160-4_3
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DOI: https://doi.org/10.1007/978-1-61779-160-4_3
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