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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 |
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author | Schmidt, B J |
author_facet | Schmidt, B J |
author_sort | Schmidt, B J |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4039391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-40393912014-06-02 Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine Schmidt, B J CPT Pharmacometrics Syst Pharmacol Perspective 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. Nature Publishing Group 2014-03 2014-03-19 /pmc/articles/PMC4039391/ /pubmed/24646725 http://dx.doi.org/10.1038/psp.2014.2 Text en Copyright © 2014 American Society for Clinical Pharmacology and Therapeutics http://creativecommons.org/licenses/by-nc-nd/3.0/ CPT: Pharmacometrics and Systems Pharmacology is an open-access journal published by Nature Publishing Group. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Perspective Schmidt, B J Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine |
title | Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine |
title_full | Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine |
title_fullStr | Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine |
title_full_unstemmed | Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine |
title_short | Systems Biology for Simulating Patient Physiology During the Postgenomic Era of Medicine |
title_sort | systems biology for simulating patient physiology during the postgenomic era of medicine |
topic | Perspective |
url | 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 |
work_keys_str_mv | AT schmidtbj systemsbiologyforsimulatingpatientphysiologyduringthepostgenomiceraofmedicine |