Systems Pharmacology: Network Analysis to Identify Multiscale Mechanisms of Drug Action
By Shan Zhao, Ravi Iyengar. Annual Review of Pharmacology and Toxicology, 2012
334 citations recorded by the source corpus.
Systems approaches have long been used in pharmacology to understand drug action at the organ and organismal levels. The application of computational and experimental systems biology approaches to pharmacology allows us to expand the definition of systems pharmacology to include network analyses at multiple scales of biological organization and to explain both therapeutic and adverse effects of drugs. Systems pharmacology analyses rely on experimental “omics” technologies that are capable of measuring changes in large numbers of variables, often at a genome-wide level, to build networks for analyzing drug action. A major use of omics technologies is to relate the genomic status of an individual to the therapeutic efficacy of a drug of interest. Combining pathway and network analyses, pharmacokinetic and pharmacodynamic models, and a knowledge of polymorphisms in the genome will enable the development of predictive models of therapeutic efficacy. Network analyses based on publicly available databases such as the U.S. Food and Drug Administration’s Adverse Event Reporting System allow us to develop an initial understanding of the context within which molecular-level drug-target interactions can lead to distal effectors in a process that results in adverse phenotypes at the organ and organismal levels. The current state of systems pharmacology allows us to formulate a set of questions that could drive future research in the field. The long-term goal of such research is to develop polypharmacology for complex diseases and predict therapeutic efficacy and adverse event risk for individuals prior to commencement of therapy.
Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology
View Paper: https://www.semanticscholar.org/paper/eff87d5850df2c45dab80bb553ce9e3f2d562ade
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In Computational Theory and Mathematics
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- Huba J. M. Kiss
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In Molecular Biology
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- Peter Csermely
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- Yuzong Chen
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- Huba J. M. Kiss
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In Pharmacology
- Ruth Nussinov
- Peter Csermely
- Zi‐Yi Wang
- Jiahui Zheng
- Xin Wang
- Huba J. M. Kiss
- Tamás Korcsmáros
- Shao Li
Citations in the corpus
- Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, positive): “Both are systems-level responses, which allow the prediction of drug off-targets by computational methods (Berger & Iyengar, 2011; Zhao & Iyengar, 2012).”
- Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics (2019, background): “microRNAs, transcription factors and interacting proteins) is useful for drug discovery tasks (Supplementary Table S1) such as the investigations of target druggability (6,30), systems pharmacology (31) and the discovery of multi-target and combination therapies (32,33).”
- TCM network pharmacology: A new trend towards combining computational, experimental and clinical approaches. (2021, background): “2011 Network target: a starting point of network pharmacology research on TCM prescriptions [9] WANG Xin, et al.”