Abstract
In this paper, the two non-linear mixed-effects programs NONMEM and NLME were compared for their use in population pharmacokinetic/pharmacodynamic (PK/PD) modelling. We have described the first-order conditional estimation (FOCE) method as implemented in NONMEM and the alternating algorithm in NLME proposed by Lindstrom and Bates. The two programs were tested using clinical PK/PD data of a new gonadotropin-releasing hormone (GnRH) antagonist degarelix currently being developed for prostate cancer treatment. The pharmacokinetics of intravenous administered degarelix was analysed using a three compartment model while the pharmacodynamics was analysed using a turnover model with a pool compartment. The results indicated that the two algorithms produce consistent parameter estimates. The bias and precision of the two algorithms were further investigated using a parametric bootstrap procedure which showed that NONMEM produced more accurate results than NLME together with the nlmeODE package for this specific study.
Original language | English |
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Journal | Journal of Pharmacokinetics and Pharmacodynamics |
Volume | 31 |
Issue number | 6 |
Pages (from-to) | 441-461 |
ISSN | 1567-567X |
Publication status | Published - 2004 |
Keywords
- population pharmacokinetic/pharmacodynamic modelling; non-linear mixed-effects programs; NONMEM; NLME; degarelix; GnRH antagonist.