The NONMEM System

Beal, Stuart L.; Sheiner, Lewis B.

doi:10.2307/2684123

Cited by 697 publications

(767 citation statements)

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“…The development of population pharmacokinetic models for carboplatin and e toposide was undertaken using nonlinear mixed effects modeling implemented as part of the NONMEM version VI, level 1.1 software [9]. The first-order conditional estimation method with η/ε interaction was used to obtain parameter estimates together with either ADVAN1 with the TRANS2 reparameterisation, for one-compartment models, or ADVAN3 and TRANS4 for two-compartment models.…”

Section: Pharmacokinetic Analysismentioning

confidence: 99%

Pharmacokinetics of carboplatin and etoposide in infant neuroblastoma patients

Veal

Cole

Errington

et al. 2009

Cancer Chemother Pharmacol

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Purpose Carboplatin and etoposide are commonly used chemotherapeutics for the treatment of many paediatric cancers. However, there are very limited published data concerning the pharmacokinetics of these agents in infants and very young children, for whom dose reductions are frequently implemented.Methods Etoposide (5 mg/kg; 2hr i.v. infusion) was co-administered with carboplatin (6.6 mg/kg; 1hr i.v. infusion) on each of 3 days of treatment and samples were taken between 0.5 and 4 hours after the start of administration, from a total of 19 neuroblastoma patients aged less than 1 year at diagnosis and weighing <12kg at treatment. Pharmacokinetic analysis was carried out using a non-linear mixed effects modelling (NONMEM) approach.Results Two compartment structural models were selected for both carboplatin and etoposide analysis. Body weight was strongly associated with carboplatin clearance, with a slightly weaker relationship observed with etoposide clearance. Carboplatin clearance values ranged from 12.8-33.6 ml/min, with total AUC values of 4.2-9.3 mg/ml.min achieved over the 3 days of treatment. Clearance values normalized to body weight were significantly higher in patients <12kg than in children >12kg, with mean ± SD values of 2.9 ± 0.4 and 2.5 ± 0.4 ml/min/kg respectively (P<0.05).Etoposide exhibited a median half-life of 4.6 hours (range: 4.1-6.6), a median AUC of 7.1 mg/ml.min (range: 3.4-11.0) and a median clearance of 6.6 ml/min (range: 3.2-13.0). ConclusionResults suggest that prediction of absolute carboplatin clearance values may be difficult in infant patients <12kg, with a small but significant difference in clearance values normalized to body weight observed in this patient group. Etoposide pharmacokinetic data support previous findings that question the utility of modified dosing in infants. The current study demonstrates the feasibility of generating informative pharmacokinetic data in infants and young children.

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Section: Pharmacokinetic Analysismentioning

confidence: 99%

Pharmacokinetics of carboplatin and etoposide in infant neuroblastoma patients

Veal

Cole

Errington

et al. 2009

Cancer Chemother Pharmacol

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“…To provide a robust mathematical analysis, model development was performed independently in two software packages (S-ADAPT and NONMEM) which utilize different estimation algorithms. The importance sampling Monte Carlo parametric expectation-maximization method (pmethod ϭ 4) in S-ADAPT (version 1.57 [31]) using SADAPT-TRAN (32,33) and the first-order conditional estimation method with the interaction option (FOCEϩI) in NONMEM VI (level 1.2; using the ADVAN9 subroutine; NONMEM Project Group, Icon Development Solutions, Ellicott City, MD [34]) were applied. Models were evaluated based on the S-ADAPT objective function value (Ϫ1ϫ log likelihood), NONMEM objective function value (Ϫ2ϫ log likelihood), and a series of standard diagnostic plots as previously described (35)(36)(37).…”

Section: Fig 2 Mechanistic Synergy With Drug B Enhancing the Rate Of mentioning

confidence: 99%

Quantifying Subpopulation Synergy for Antibiotic Combinations via Mechanism-Based Modeling and a Sequential Dosing Design

Landersdorfer

et al. 2013

Antimicrob Agents Chemother

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Quantitative modeling of combination therapy can describe the effects of each antibiotic against multiple bacterial populations. Our aim was to develop an efficient experimental and modeling strategy that evaluates different synergy mechanisms using a rapidly killing peptide antibiotic (nisin) combined with amikacin or linezolid as probe drugs. Serial viable counts over 48 h were obtained in time-kill experiments with all three antibiotics in monotherapy against a methicillin-resistant Staphylococcus aureus USA300 strain (inoculum, 10 8 CFU/ml). A sequential design (initial dosing of 8 or 32 mg/liter nisin, switched to amikacin or linezolid at 1.5 h) assessed the rate of killing by amikacin and linezolid against nisin-intermediate and nisin-resistant populations. Simultaneous combinations were additionally studied and all viable count profiles comodeled in S-ADAPT and NONMEM. A mechanism-based model with six populations (three for nisin times two for amikacin) yielded unbiased and precise (r ‫؍‬ 0.99, slope ‫؍‬ 1.00; S-ADAPT) individual fits. The second-order killing rate constants for nisin against the three populations were 5.67, 0.0664, and 0.00691 liter/(mg · h). For amikacin, the maximum killing rate constants were 10.1 h ؊1 against its susceptible and 0.771 h ؊1 against its less-susceptible populations, with 14.7 mg/liter amikacin causing half-maximal killing. After incorporating the effects of nisin and amikacin against each population, no additional synergy function was needed. Linezolid inhibited successful bacterial replication but did not efficiently kill populations less susceptible to nisin. Nisin plus amikacin achieved subpopulation synergy. The proposed sequential and simultaneous dosing design offers an efficient approach to quantitatively characterize antibiotic synergy over time and prospectively evaluate antibiotic combination dosing strategies.

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“…Population models were originally introduced in the context of pharmacokinetic studies for drug development and evaluation (Beal and Sheiner, 1980;Beal and Sheiner, 1982;Sheiner, 1984) . A number of applications can be found in the pharmacokinetic literature (Aarons, 1992;Sheiner and Ludden, 1992;Vozeh et al, 1996;Yuh et al, 1994) .…”

Section: Population Modelsmentioning

confidence: 99%

“…Another classification of the relevant statistical methods differentiates maximum likelihood (Beal and Sheiner, 1980) and Bayesian approaches (Racine-Poon, 1985) . Modelling in toxicology ought to be particularly well served by a Bayesian approach.…”

Section: Bayesian Analysis Of Population Modelsmentioning

confidence: 99%

Applications of population approaches in toxicology

Bois

2001

Toxicology Letters

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Many experimental or observational studies in toxicology are best analysed in a population framework.Recent examples include investigations of the extent and origin of intra-individual variability in toxicity studies, incorporation of genotypic information to address intra-individual variability, optimal design of experiments, and extension of toxicokinetic modelling to the analysis of biomarker studies in industrial hygiene or epidemiological contexts. Bayesian statistics provide powerful numerical methods for fitting population models, particularly when complex mechanistic toxicokinetic or toxicodynamic models are involved. Challenges and limitations to the use of population models, in terms of basic structure, computational burden, ease of implementation and data accessibility, are identified and discussed.

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The NONMEM System

Cited by 697 publications

References 0 publications

Pharmacokinetics of carboplatin and etoposide in infant neuroblastoma patients

Pharmacokinetics of carboplatin and etoposide in infant neuroblastoma patients

Quantifying Subpopulation Synergy for Antibiotic Combinations via Mechanism-Based Modeling and a Sequential Dosing Design

Applications of population approaches in toxicology

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