An integrated approach for inference and mechanistic modeling for advancing drug development |
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Authors: | Aksenov Sergej V Church Bruce Dhiman Anjali Georgieva Anna Sarangapani Ramesh Helmlinger Gabriel Khalil Iya G |
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Affiliation: | Gene Network Sciences, Inc. 31 Dutch Mill Road, Ithaca, NY 14850, USA. |
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Abstract: | An important challenge facing researchers in drug development is how to translate multi-omic measurements into biological insights that will help advance drugs through the clinic. Computational biology strategies are a promising approach for systematically capturing the effect of a given drug on complex molecular networks and on human physiology. This article discusses a two-pronged strategy for inferring biological interactions from large-scale multi-omic measurements and accounting for known biology via mechanistic dynamical simulations of pathways, cells, and organ- and tissue level models. These approaches are already playing a role in driving drug development by providing a rational and systematic computational framework. |
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Keywords: | Drug development Systems biology Computational biology Biomarker Efficacy Toxicity Omic |
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