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Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine
Systems pharmacology models capable of accurately recapitulating sophisticated patient phenotypes have enabled the investigation of mechanisms responsible for therapeutic efficacy. Although omics data sets are capable of characterizing the operation of subcellular networks, their utility in mechanis...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4039391/ https://www.ncbi.nlm.nih.gov/pubmed/24646725 http://dx.doi.org/10.1038/psp.2014.2 |
Sumario: | Systems pharmacology models capable of accurately recapitulating sophisticated patient phenotypes have enabled the investigation of mechanisms responsible for therapeutic efficacy. Although omics data sets are capable of characterizing the operation of subcellular networks, their utility in mechanistically predicting quantitative, clinically accessible outcome measures has been limited. Developing insights into clinical outcomes from omics data sets will benefit from modeling approaches that can integrate molecular networks mechanistically with simulations of patient pathophysiology across compartments and scales. |
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