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10.1080/19420862.2016.1238995 http://scihub22266oqcxt.onion/10.1080/19420862.2016.1238995 C5240652!5240652 !27661132     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27661132 &cmd=llinks): Failed to open stream: HTTP request failed! 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Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity |pdf=|usr=}}{{27661132 }} gab.com Text Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity JO: MAbs http://www.kidney.de/pget.php?&tw=1&pmid=27661132 #FOAvip Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients. Twit Text FOAVip Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity ????MAbs http://www.kidney.de/pget.php?&tw=1&pmid=27661132 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27661132 #FOAvip English Wikipedia <ref>{{Cite pmid|27661132 }}</ref> Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity #MMPMID27661132 Ait-Oudhia S ; Ovacik MA ; Mager DE MAbs 2017[Jan]; 9 (1 ): 15-28 PMID27661132 show ga Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients. |*Models, Theoretical [MESH] |Animals [MESH] |Humans [MESH] |Immunoconjugates/*pharmacokinetics [MESH]Systems pharmacology and enhanced pharmacodynamic models for understan(epmc).pdf DeepDyve Pubget Overpricing