Performance and robustness of the Monte Carlo importance sampling algorithm using parallelized S-ADAPT for basic and complex mechanistic models

AAPS Journal

Volumn 13, Issue 2, 2011, Pages 212-226

  Bulitta, Jurgen B ^a,b   Landersdorfer, Cornelia B ^a,b  

^a ORDWAY RESEARCH INSTITUTE   (United States)

^b UNIVERSITY AT BUFFALO   (United States)

Author keywords

mechanistic population pharmacokinetic; Monte Carlo importance sampling; Monte Carlo parametric expectation maximization (MC PEM) algorithm; nonlinear mixed effects modeling in S ADAPT; parallel computing; pharmacodynamic modeling

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; DEPENDENT VARIABLE; INTERMETHOD COMPARISON; MONTE CARLO METHOD; PHARMACODYNAMICS; SAMPLING; STATISTICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; MODELS, BIOLOGICAL; MONTE CARLO METHOD; PHARMACEUTICAL PREPARATIONS; PHARMACOKINETICS;

EID: 79957468849     PISSN: 15507416     EISSN: None     Source Type: Journal    
DOI: 10.1208/s12248-011-9258-9     Document Type: Article

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