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Comparison of two population pharmacokinetic programs, NONMEM and P-PHARM, for tacrolimus.
Eur J Clin Pharmacol. 2002 Dec; 58(9):597-605.EJ

Abstract

OBJECTIVES

To compare the population modelling programs NONMEM and P-PHARM during investigation of the pharmacokinetics of tacrolimus in paediatric liver-transplant recipients.

METHODS

Population pharmacokinetic analysis was performed using NONMEM and P-PHARM on retrospective data from 35 paediatric liver-transplant patients receiving tacrolimus therapy. The same data were presented to both programs. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F). Covariates screened for influence on these parameters were weight, age, gender, post-operative day, days of tacrolimus therapy, transplant type, biliary reconstructive procedure, liver function tests, creatinine clearance, haematocrit, corticosteroid dose, and potential interacting drugs.

RESULTS

A satisfactory model was developed in both programs with a single categorical covariate--transplant type--providing stable parameter estimates and small, normally distributed (weighted) residuals. In NONMEM, the continuous covariates--age and liver function tests--improved modelling further. Mean parameter estimates were CL/F (whole liver) = 16.3 l/h, CL/F (cut-down liver) = 8.5 l/h and V/F = 565 l in NONMEM, and CL/F = 8.3 l/h and V/F = 155 l in P-PHARM. Individual Bayesian parameter estimates were CL/F (whole liver) = 17.9 +/- 8.8 l/h, CL/F (cut-down liver) = 11.6 +/- 8.8 l/h and V/F = 712 +/- 792 l in NONMEM, and CL/F (whole liver) = 12.8 +/- 3.5 l/h, CL/F (cut-down liver) = 8.2 +/- 3.4 l/h and V/F = 221 +/- 164 l in P-PHARM. Marked interindividual kinetic variability (38-108%) and residual random error (approximately 3 ng/ml) were observed. P-PHARM was more user friendly and readily provided informative graphical presentation of results. NONMEM allowed a wider choice of errors for statistical modelling and coped better with complex covariate data sets.

CONCLUSION

Results from parametric modelling programs can vary due to different algorithms employed to estimate parameters, alternative methods of covariate analysis and variations and limitations in the software itself.

Authors+Show Affiliations

School of Pharmacy, University of Queensland, Brisbane, Queensland 4072, Australia. c.staatz@pharmacy.uq.edu.auNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

12483452

Citation

Staatz, Christine E., and Susan E. Tett. "Comparison of Two Population Pharmacokinetic Programs, NONMEM and P-PHARM, for Tacrolimus." European Journal of Clinical Pharmacology, vol. 58, no. 9, 2002, pp. 597-605.
Staatz CE, Tett SE. Comparison of two population pharmacokinetic programs, NONMEM and P-PHARM, for tacrolimus. Eur J Clin Pharmacol. 2002;58(9):597-605.
Staatz, C. E., & Tett, S. E. (2002). Comparison of two population pharmacokinetic programs, NONMEM and P-PHARM, for tacrolimus. European Journal of Clinical Pharmacology, 58(9), 597-605.
Staatz CE, Tett SE. Comparison of Two Population Pharmacokinetic Programs, NONMEM and P-PHARM, for Tacrolimus. Eur J Clin Pharmacol. 2002;58(9):597-605. PubMed PMID: 12483452.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Comparison of two population pharmacokinetic programs, NONMEM and P-PHARM, for tacrolimus. AU - Staatz,Christine E, AU - Tett,Susan E, Y1 - 2002/11/15/ PY - 2002/02/18/received PY - 2002/08/28/accepted PY - 2002/12/17/pubmed PY - 2003/5/13/medline PY - 2002/12/17/entrez SP - 597 EP - 605 JF - European journal of clinical pharmacology JO - Eur J Clin Pharmacol VL - 58 IS - 9 N2 - OBJECTIVES: To compare the population modelling programs NONMEM and P-PHARM during investigation of the pharmacokinetics of tacrolimus in paediatric liver-transplant recipients. METHODS: Population pharmacokinetic analysis was performed using NONMEM and P-PHARM on retrospective data from 35 paediatric liver-transplant patients receiving tacrolimus therapy. The same data were presented to both programs. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F). Covariates screened for influence on these parameters were weight, age, gender, post-operative day, days of tacrolimus therapy, transplant type, biliary reconstructive procedure, liver function tests, creatinine clearance, haematocrit, corticosteroid dose, and potential interacting drugs. RESULTS: A satisfactory model was developed in both programs with a single categorical covariate--transplant type--providing stable parameter estimates and small, normally distributed (weighted) residuals. In NONMEM, the continuous covariates--age and liver function tests--improved modelling further. Mean parameter estimates were CL/F (whole liver) = 16.3 l/h, CL/F (cut-down liver) = 8.5 l/h and V/F = 565 l in NONMEM, and CL/F = 8.3 l/h and V/F = 155 l in P-PHARM. Individual Bayesian parameter estimates were CL/F (whole liver) = 17.9 +/- 8.8 l/h, CL/F (cut-down liver) = 11.6 +/- 8.8 l/h and V/F = 712 +/- 792 l in NONMEM, and CL/F (whole liver) = 12.8 +/- 3.5 l/h, CL/F (cut-down liver) = 8.2 +/- 3.4 l/h and V/F = 221 +/- 164 l in P-PHARM. Marked interindividual kinetic variability (38-108%) and residual random error (approximately 3 ng/ml) were observed. P-PHARM was more user friendly and readily provided informative graphical presentation of results. NONMEM allowed a wider choice of errors for statistical modelling and coped better with complex covariate data sets. CONCLUSION: Results from parametric modelling programs can vary due to different algorithms employed to estimate parameters, alternative methods of covariate analysis and variations and limitations in the software itself. SN - 0031-6970 UR - https://www.unboundmedicine.com/medline/citation/12483452/Comparison_of_two_population_pharmacokinetic_programs_NONMEM_and_P_PHARM_for_tacrolimus_ L2 - https://dx.doi.org/10.1007/s00228-002-0517-7 DB - PRIME DP - Unbound Medicine ER -