Literature DB >> 15518244

Fuzzy simulation of pharmacokinetic models: case study of whole body physiologically based model of diazepam.

Ivelina I Gueorguieva1, Ivan A Nestorov, Malcolm Rowland.   

Abstract

The aim of the present study is to develop and implement a methodology that accounts for parameter variability and uncertainty in the presence of qualitative and semi-quantitative information (fuzzy simulations) as well as when some parameters are better quantitatively defined than others (fuzzy-probabilistic approach). The fuzzy simulations method consists of (i) representing parameter uncertainty and variability by fuzzy numbers and (ii) simulating predictions by solving the pharmacokinetic model. The fuzzy-probabilistic approach includes an additional transformation between fuzzy numbers and probability density functions. To illustrate the proposed method a diazepam WBPBPK model was used where the information for hepatic intrinsic clearance determined by in vitro-in vivo scaling was semi-quantitative. The predicted concentration time profiles were compared with those resulting from a Monte Carlo simulation. Fuzzy simulations can be used as an alternative to Monte Carlo simulation.

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Year:  2004        PMID: 15518244     DOI: 10.1023/b:jopa.0000039564.35602.78

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  23 in total

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  13 in total

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Authors:  Ivelina Gueorguieva; Ivan A Nestorov; Leon Aarons; Malcolm Rowland
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2.  Reducing whole body physiologically based pharmacokinetic models using global sensitivity analysis: diazepam case study.

Authors:  Ivelina Gueorguieva; Ivan A Nestorov; Malcolm Rowland
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3.  Diazepam pharamacokinetics from preclinical to phase I using a Bayesian population physiologically based pharmacokinetic model with informative prior distributions in WinBUGS.

Authors:  Ivelina Gueorguieva; Leon Aarons; Malcolm Rowland
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-06-29       Impact factor: 2.745

4.  Optimal design for multivariate response pharmacokinetic models.

Authors:  Ivelina Gueorguieva; Leon Aarons; Kayode Ogungbenro; Karin M Jorga; Trudy Rodgers; Malcolm Rowland
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-03-21       Impact factor: 2.745

5.  Simulating pharmacokinetic and pharmacodynamic fuzzy-parameterized models: a comparison of numerical methods.

Authors:  Kok-Yong Seng; Ivan Nestorov; Paolo Vicini
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-08-21       Impact factor: 2.745

6.  Physiologically based pharmacokinetic modeling of drug disposition in rat and human: a fuzzy arithmetic approach.

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7.  Population pharmacokinetic reanalysis of a Diazepam PBPK model: a comparison of Stan and GNU MCSim.

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Review 8.  Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine.

Authors:  Clara Hartmanshenn; Megerle Scherholz; Ioannis P Androulakis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-09-19       Impact factor: 2.745

9.  A framework for 2-stage global sensitivity analysis of GastroPlus™ compartmental models.

Authors:  Megerle L Scherholz; James Forder; Ioannis P Androulakis
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10.  Physiologically based pharmacokinetic tissue compartment model selection in drug development and risk assessment.

Authors:  Matthew D Thompson; Daniel A Beard
Journal:  J Pharm Sci       Date:  2011-10-03       Impact factor: 3.534

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