Abstract
The hope of the rapid translation of 'genes to drugs' has foundered on the reality that disease biology is complex, and that drug development must be driven by insights into biological responses. Systems biology aims to describe and to understand the operation of complex biological systems and ultimately to develop predictive models of human disease. Although meaningful molecular level models of human cell and tissue function are a distant goal, systems biology efforts are already influencing drug discovery. Large-scale gene, protein and metabolite measurements ('omics') dramatically accelerate hypothesis generation and testing in disease models. Computer simulations integrating knowledge of organ and system-level responses help prioritize _targets and design clinical trials. Automation of complex primary human cell–based assay systems designed to capture emergent properties can now integrate a broad range of disease-relevant human biology into the drug discovery process, informing _target and compound validation, lead optimization, and clinical indication selection. These systems biology approaches promise to improve decision making in pharmaceutical development.
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Acknowledgements
Writing of this review was supported in part by SBIR grants (R44 AI048255 and R43 AI049048) to BioSeek, Inc., and by NIH grants to E.C.B. The authors thank Evangelos Hytopoulos and Ivan Plavec for thoughtful criticism and input.
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E.J.K. is an employee, E.L.B. is a cofounder and vice president of research, and E.C.B. is a cofounder, chair of the SAB and member of the board of directors of BioSeek.
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Butcher, E., Berg, E. & Kunkel, E. Systems biology in drug discovery. Nat Biotechnol 22, 1253–1259 (2004). https://doi.org/10.1038/nbt1017
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DOI: https://doi.org/10.1038/nbt1017
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