ISSN:
1432-0843
Keywords:
Key words ALIMTA
;
Pemetrexed disodium
;
Population pharmacokinetics
;
NONMEM
Source:
Springer Online Journal Archives 1860-2000
Topics:
Medicine
Notes:
Abstract Purpose: To evaluate the population pharmacokinetics of pemetrexed disodium in cancer patients enrolled in four different open-label, multicenter, nonrandomized phase II studies. Methods: Pemetrexed disodium was administered as a 10-min intravenous infusion (600 mg/m2) every 21 days. A total of four blood samples were to be collected each cycle per patient (n=103 patients) during cycles 1 and 3. Plasma concentration-time data were analyzed by nonlinear mixed-effect modeling using NONMEM to estimate pemetrexed disodium pharmacokinetic parameters (mean, and between- and within-patient variability) as well as relationships between the pharmacokinetic parameters and various patient-specific factors (demographic and physiologic data). Results/Conclusions: The pharmacokinetics of pemetrexed disodium were best characterized by a two-compartment model with initial distribution and terminal elimination half-lives of 0.63 h and 2.73 h, respectively. The typical value of systemic clearance (CL) in liters per hour included a relationship to creatinine clearance (CrCL) with a slope of 0.0292. Typical values of central volume (Vc), distributional CL (Q), and peripheral volume (Vp) were 11.3 l, 3.21 l/h, and 5.20 l, respectively. Between-patient variability was 19.6%, 15.6%, and 21.7% for CL, Vc, and Vp, respectively. A combined additive/proportional error model was used to describe residual variability, with a coefficient of variation of 23.7% for the proportional component and a standard deviation of 0.0410 μg/ml for the additive component. Significant patient-specific factors on CL were calculated CrCL, body weight, and to a lesser extent alanine transaminase and folate deficiency. Gender and body weight were significant factors on Vc while both body surface area and albumin were significant factors on Vp. In conclusion, population pharmacokinetic modeling revealed relationships between pharmacokinetic parameters and various patient specific factors.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/s002800000144
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