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Systems biology for simulating patient physiology during the postgenomic era of medicine.

ABSTRACT: 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.

SUBMITTER: Schmidt BJ

PROVIDER: S-EPMC4039391 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Systems biology for simulating patient physiology during the postgenomic era of medicine.

Schmidt B J BJ

CPT: pharmacometrics & systems pharmacology 20140319

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 ...[more]

PMID: 24646725

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