Literature DB >> 10638394

Limited-sampling strategy models for estimating the area under the plasma concentration-time curve for amlodipine.

G Suarez-Kurtz1, F L Vicente, C G Ponte, V L Buy, C J Struchiner.   

Abstract

OBJECTIVE: Develop and validate limited-sampling strategy (LSS) models for estimating the area under the plasma concentration versus time curve (AUC) of amlodipine, using data from a bioequivalence study.
METHODS: Sixteen healthy volunteers received single 5-mg oral doses of amlodipine, as reference or test formulation, at a 14-day interval, in a randomized, crossover protocol. Plasma concentrations of amlodipine (n = 288), measured by mass spectrometry, were used to develop LSS models.
RESULTS: Linear regression analysis of the AUC0-72 and a "jack-knife" validation procedure revealed that LSS models based on two sampling times (12 h and 48 h) predict accurately (R2 = 0.99; bias < 0.01%; precision = 0.03%) the AUC0-72 of amlodipine for each formulation. Validation tests indicate that the 2-point LSS model developed for the reference formulation predicts accurately (R2 > 0.90): (a) the individual AUC0-72 for the test formulation in the same group of volunteers; (b) the individual AUC0-72 for the same reference formulation in another bioequivalence study in Brazilian volunteers; (c) the average AUC0-72 reported in seven additional international studies performed under protocols similar to the present investigation; (d) the individual AUC0-72 corresponding to concentration data points provided by a first-order compartmental pharmacokinetic model, when the relative values of either the absorption rate (Kabs) or the bioavailability (F) model parameters were set at 0.85 or 0.6, of their respective original values.
CONCLUSIONS: The 2-point LSS models developed in the current study predict accurately the AUC of amlodipine under a variety of experimental conditions and, thus, may be valuable for exploring the relationships between the pharmacokinetics and pharmacodynamics of this calcium antagonist, at reduced costs of sample acquisition and analysis, and avoiding sampling at "unsociable" hours.

Entities:  

Mesh:

Substances:

Year:  1999        PMID: 10638394     DOI: 10.1007/s002280050688

Source DB:  PubMed          Journal:  Eur J Clin Pharmacol        ISSN: 0031-6970            Impact factor:   2.953


  4 in total

1.  Omeprazole limited sampling strategies to predict area under the concentration-time curve ratios: implications for cytochrome P450 2C19 and 3A phenotyping.

Authors:  Eileen B Lawson; Jerry C Wu; R Michael Baldwin; Magnus Ingelman-Sundberg; Staffan Rosenborg; Dong-Seok Yim; Ophelia Q P Yin; Edmund V Capparelli; Joseph D Ma
Journal:  Eur J Clin Pharmacol       Date:  2011-10-19       Impact factor: 2.953

2.  Random sparse sampling strategy using stochastic simulation and estimation for a population pharmacokinetic study.

Authors:  Xiao-Hui Huang; Kun Wang; Ji-Han Huang; Ling Xu; Lu-Jin Li; Yu-Cheng Sheng; Qing-Shan Zheng
Journal:  Saudi Pharm J       Date:  2013-02-10       Impact factor: 4.330

3.  Limited sampling strategy for determining metformin area under the plasma concentration-time curve.

Authors:  Ana Beatriz Santoro; Tore Bjerregaard Stage; Claudio José Struchiner; Mette Marie Hougaard Christensen; Kim Brosen; Guilherme Suarez-Kurtz
Journal:  Br J Clin Pharmacol       Date:  2016-07-24       Impact factor: 4.335

4.  Development and validation of limited-sampling strategies for predicting amoxicillin pharmacokinetic and pharmacodynamic parameters.

Authors:  G Suarez-Kurtz; F M Ribeiro; F L Vicente; C J Struchiner
Journal:  Antimicrob Agents Chemother       Date:  2001-11       Impact factor: 5.191

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.