Literature DB >> 23007443

Mechanism-based pharmacodynamic modeling.

Melanie A Felmlee1, Marilyn E Morris, Donald E Mager.   

Abstract

Pharmacodynamic modeling is based on a quantitative integration of pharmacokinetics, pharmacological systems, and (patho-) physiological processes for understanding the intensity and time-course of drug effects on the body. Application of such models to the analysis of meaningful experimental data allows for the quantification and prediction of drug-system interactions for both therapeutic and adverse drug responses. In this chapter, commonly used mechanistic pharmacodynamic models are presented with respect to their important features, operable equations, and signature profiles. In addition, literature examples showcasing the utility of these models to adverse drug events are highlighted. Common model types that are covered include simple direct effects, biophase distribution, indirect effects, signal transduction, and irreversible effects.

Entities:  

Mesh:

Year:  2012        PMID: 23007443      PMCID: PMC3684160          DOI: 10.1007/978-1-62703-050-2_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  32 in total

1.  Precursor-dependent indirect pharmacodynamic response model for tolerance and rebound phenomena.

Authors:  A Sharma; W F Ebling; W J Jusko
Journal:  J Pharm Sci       Date:  1998-12       Impact factor: 3.534

2.  RELATIONSHIP BETWEEN ELIMINATION RATE OF DRUGS AND RATE OF DECLINE OF THEIR PHARMACOLOGIC EFFECTS.

Authors:  G LEVY
Journal:  J Pharm Sci       Date:  1964-03       Impact factor: 3.534

3.  The pharmacology of vascular smooth muscle.

Authors:  R F FURCHGOTT
Journal:  Pharmacol Rev       Date:  1955-06       Impact factor: 25.468

4.  Assessment of drug interactions relevant to pharmacodynamic indirect response models.

Authors:  Justin Earp; Wojciech Krzyzanski; Abhijit Chakraborty; Miren K Zamacona; William J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-10       Impact factor: 2.745

5.  The population pharmacokinetics of citalopram after deliberate self-poisoning: a Bayesian approach.

Authors:  Lena E Friberg; Geoffrey K Isbister; L Peter Hackett; Stephen B Duffull
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-08       Impact factor: 2.745

6.  Pharmacokinetic-pharmacodynamic modeling of the respiratory depressant effect of norbuprenorphine in rats.

Authors:  Ashraf Yassen; Jingmin Kan; Erik Olofsen; Ernst Suidgeest; Albert Dahan; Meindert Danhof
Journal:  J Pharmacol Exp Ther       Date:  2007-02-05       Impact factor: 4.030

Review 7.  Characteristics of indirect pharmacodynamic models and applications to clinical drug responses.

Authors:  A Sharma; W J Jusko
Journal:  Br J Clin Pharmacol       Date:  1998-03       Impact factor: 4.335

8.  Transit compartments versus gamma distribution function to model signal transduction processes in pharmacodynamics.

Authors:  Y N Sun; W J Jusko
Journal:  J Pharm Sci       Date:  1998-06       Impact factor: 3.534

9.  An improved pharmacodynamic model for formation of methemoglobin by antimalarial drugs.

Authors:  A A Fasanmade; W J Jusko
Journal:  Drug Metab Dispos       Date:  1995-05       Impact factor: 3.922

10.  Dapsone-induced hematologic toxicity: comparison of the methemoglobin-forming ability of hydroxylamine metabolites of dapsone in rat and human blood.

Authors:  C Vage; N Saab; P M Woster; C K Svensson
Journal:  Toxicol Appl Pharmacol       Date:  1994-12       Impact factor: 4.219

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  19 in total

Review 1.  Recent findings in the pharmacology of inhaled nicotine: Preclinical and clinical in vivo studies.

Authors:  Asti Jackson; Ben Grobman; Suchitra Krishnan-Sarin
Journal:  Neuropharmacology       Date:  2020-06-24       Impact factor: 5.250

2.  A distributed delay approach for modeling delayed outcomes in pharmacokinetics and pharmacodynamics studies.

Authors:  Shuhua Hu; Michael Dunlavey; Serge Guzy; Nathan Teuscher
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-01-24       Impact factor: 2.745

3.  Model-Based Prediction of Acid Suppression and Proposal of a New Dosing Regimen of Fexuprazan in Humans.

Authors:  Min-Soo Kim; Nora Lee; Areum Lee; Yoon-Jee Chae; Suk-Jae Chung; Kyeong-Ryoon Lee
Journal:  Pharmaceuticals (Basel)       Date:  2022-06-03

4.  Utilization of Pharmacokinetic/Pharmacodynamic Modeling in Pharmacoepidemiological Studies: A Systematic Review on Antiarrhythmic and Glucose-Lowering Medicines.

Authors:  Soroush Mohammadi Jouabadi; Mitra Nekouei Shahraki; Payam Peymani; Bruno H Stricker; Fariba Ahmadizar
Journal:  Front Pharmacol       Date:  2022-06-20       Impact factor: 5.988

Review 5.  Avibactam Pharmacokinetic/Pharmacodynamic Targets.

Authors:  Wright W Nichols; Paul Newell; Ian A Critchley; Todd Riccobene; Shampa Das
Journal:  Antimicrob Agents Chemother       Date:  2018-05-25       Impact factor: 5.191

6.  Development of 2-aminooxazoline 3-azaxanthene β-amyloid cleaving enzyme (BACE) inhibitors with improved selectivity against Cathepsin D.

Authors:  Jonathan D Low; Michael D Bartberger; Kui Chen; Yuan Cheng; Mark R Fielden; Vijay Gore; Dean Hickman; Qingyian Liu; E Allen Sickmier; Hugo M Vargas; Jonathan Werner; Ryan D White; Douglas A Whittington; Stephen Wood; Ana E Minatti
Journal:  Medchemcomm       Date:  2017-04-27       Impact factor: 3.597

Review 7.  Mapping genes for drug chronotherapy.

Authors:  Kun Wei; Qian Wang; Jingwen Gan; Shilong Zhang; Meixia Ye; Claudia Gragnoli; Rongling Wu
Journal:  Drug Discov Today       Date:  2018-06-28       Impact factor: 7.851

8.  Modeling the synergistic properties of drugs in hormonal treatment for prostate cancer.

Authors:  Trevor Reckell; Kyle Nguyen; Tin Phan; Sharon Crook; Eric J Kostelich; Yang Kuang
Journal:  J Theor Biol       Date:  2021-01-07       Impact factor: 2.691

9.  Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data.

Authors:  Jaydeep Yadav; Mehdi El Hassani; Jasleen Sodhi; Volker M Lauschke; Jessica H Hartman; Laura E Russell
Journal:  Drug Metab Rev       Date:  2021-05-25       Impact factor: 6.984

10.  Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

Authors:  Annie Lumen; Kevin McNally; Nysia George; Jeffrey W Fisher; George D Loizou
Journal:  Front Pharmacol       Date:  2015-05-27       Impact factor: 5.810

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