Novel opportunities for computational biology and sociology in drug discovery
2009
Yao, Lixia | Evans, James A. | Rzhet︠s︡kiĭ, A. I︠U︡ (Andreĭ I︠U︡rʹevich)
Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.
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Este registro bibliográfico ha sido proporcionado por National Agricultural Library