Statistical identifiability and convergence evaluation for nonlinear pharmacokinetic models with particle swarm optimization

Computer Methods and Programs in Biomedicine

Volumn 113, Issue 2, 2014, Pages 413-432

  Kim, Seongho ^a   Li, Lang ^b  

^a WAYNE STATE UNIVERSITY   (United States)

^b INDIANA UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Michaelis Menten kinetic equation; Nonlinear models; Particle swarm optimization; Pharmacokinetics; Statistical identifiability

Indexed keywords

ESTIMATION APPROACHES; GLOBAL OPTIMIZATION ALGORITHM; IDENTIFIABILITY; LOCAL OPTIMIZATION ALGORITHM; MICHAELIS-MENTEN KINETIC; NON-LINEAR MODEL; OPTIMIZATION APPROACH; PHARMACOKINETIC MODEL;

ALGORITHMS; GLOBAL OPTIMIZATION; INTEGRAL EQUATIONS; KINETIC ENERGY; KINETIC THEORY; MODEL CHECKING; PARTICLE SWARM OPTIMIZATION (PSO); PHARMACOKINETICS;

COMPUTER SIMULATION;

MIDAZOLAM;

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; BINOCULAR CONVERGENCE; CHEMICAL REACTION KINETICS; CLINICAL ARTICLE; COMPARTMENT MODEL; CONTROLLED STUDY; DRUG BLOOD LEVEL; EVALUATION STUDY; EVOLUTIONARY ALGORITHM; HUMAN; INTERMETHOD COMPARISON; KINETICS; LIVER CLEARANCE; MICHAELIS MENTEN KINETICS; MONTE CARLO METHOD; NONLINEAR SYSTEM; NORMAL DISTRIBUTION; PARTICLE SWARM OPTIMIZATION; PLASMA CONCENTRATION-TIME CURVE; REACTION OPTIMIZATION; STATISTICAL ANALYSIS;

MICHAELIS-MENTEN KINETIC EQUATION; NONLINEAR MODELS; PARTICLE SWARM OPTIMIZATION; PHARMACOKINETICS; STATISTICAL IDENTIFIABILITY;

ALGORITHMS; HUMANS; HYPNOTICS AND SEDATIVES; MIDAZOLAM; NONLINEAR DYNAMICS; PHARMACOKINETICS;

EID: 84892798928     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2013.10.003     Document Type: Article

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