Drug discovery and development involves a series of difficult, systematic decision-making exercises, each of which is based on data acquired from bioassays and clinical trials. Since assays and trials are designed to elucidate the underlying pathophysiology of a disease, it is not sufficient to merely acquire data, but one must also interpret those findings in the context of the physiology they are meant to represent. Recently, these efforts have been enhanced by the use of biosimulation as a means of integrating and interpreting the vast new data sets generated by classically designed systems biology studies. Only when data describing gene expression, cell function, and whole-body physiology are interpreted in the context of integrated system function, will current error rates experienced during drug discovery and development be minimized.
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