Population pharmacokinetics/pharmacodynamics modeling: parametric and nonparametric methods.

As clinicians acquire experience with the clinical and pharmacokinetic behavior of a drug, it is usually optimal to record this experience in the form of a population pharmacokinetic model, and then to relate the behavior of the model to the clinical effects of the drug or to a linked pharmacodynamic model. The role of population modeling is thus to describe and record clinical experience with the behavior of a drug in a certain group or population of patients or subjects.

[1]  S L Beal,et al.  Population pharmacokinetic data and parameter estimation based on their first two statistical moments. , 1984, Drug metabolism reviews.

[2]  R. Jelliffe,et al.  A computer program for estimation of creatinine clearance from unstable serum creatinine levels, age, sex, and weight , 1972 .

[3]  L B Sheiner,et al.  Forecasting individual pharmacokinetics , 1979, Clinical pharmacology and therapeutics.

[4]  Marie Davidian,et al.  The Nonlinear Mixed Effects Model with a Smooth Random Effects Density , 1993 .

[5]  A. Mallet A maximum likelihood estimation method for random coefficient regression models , 1986 .

[6]  A. Mallet,et al.  Preliminary results of three methods for population pharmacokinetic analysis (NONMEM, NPML, NPEM) of amikacin in geriatric and general medicine patients. , 1994, International journal of bio-medical computing.

[7]  Alan Schumitzky,et al.  Model-Based, Goal-Oriented, Individualised Drug Therapy , 1998, Clinical pharmacokinetics.

[8]  R Jouvent,et al.  Nonparametric Estimation of Population Characteristics of the Kinetics of Lithium from Observational and Experimental Data: Individualization of Chronic Dosing Regimen Using a New Bayesian Approach , 1994, Therapeutic drug monitoring.

[9]  D. Bates,et al.  Nonlinear mixed effects models for repeated measures data. , 1990, Biometrics.

[10]  R W Jelliffe,et al.  Application of a Bayesian method to monitor and adjust vancomycin dosage regimens , 1990, Antimicrobial Agents and Chemotherapy.

[11]  L. Bertilsson,et al.  Geographical/Interracial Differences in Polymorphic Drug Oxidation , 1995, Clinical pharmacokinetics.

[12]  L B Sheiner,et al.  The population approach to pharmacokinetic data analysis: rationale and standard data analysis methods. , 1984, Drug metabolism reviews.

[13]  Adrian F. M. Smith,et al.  Bayesian Analysis of Linear and Non‐Linear Population Models by Using the Gibbs Sampler , 1994 .

[14]  B. Lindsay The Geometry of Mixture Likelihoods: A General Theory , 1983 .

[15]  A. Schumitzky Nonparametric EM Algorithms for estimating prior distributions , 1991 .

[16]  E. Vonesh,et al.  Mixed-effects nonlinear regression for unbalanced repeated measures. , 1992, Biometrics.

[17]  Roger W. Jelliffe,et al.  Individualizing Drug Dosage Regimens: Roles of Population Pharmacokinetic and Dynamic Models, Bayesian Fitting, and Adaptive Control , 1993, Therapeutic drug monitoring.

[18]  A Schumitzky,et al.  Design of dosage regimens: a multiple model stochastic control approach. , 1994, International journal of bio-medical computing.

[19]  Leon Aarons The estimation of population pharmacokinetic parameters using an EM algorithm. , 1993, Computer methods and programs in biomedicine.