Pharmacokinetic Parameter Category

Background. Meropenem, a broad spectrum carbapenem antibiotic, is often used for newborns despite of limited data available on neonatal pharmacokinetics. Due to pharmacokinetic and pharmacodynamic differences as well as to significant changes in the human body related to growth and maturation of organs and systems, direct scaling and dosing extrapolation from adults or older children with adjustment on patients weight can result in increased risk of toxicity or treatment failures. Aims to evaluate the pharmacokinetics of meropenem in premature neonates based on therapeutic drug monitoring data in real clinical settings. Materials. Of 53 pre-term neonates included in the pharmacokinetic/pharmacodynamic analysis, in 39 (73.6%) patients, gestational age ranged from 23 to 30 weeks. Population and individual pharmacokinetic parameter values were estimated by the NPAG program from the Pmetrics package based on peak-trough therapeutic drug monitoring. Samples were assayed by high-performance liquid chromatography. One-compartment pharmacokinetic model with zero-order input and first-order elimination was used to fit concentration data and to predict pharmacokinetic parameter (%T MIC of free drug) for virtual patients with simulated fast, moderate and slow meropenem elimination received different dosage by minimum inhibitory concentration (MIC) level. Univariate and multivariate regression analysis was used to evaluate the influence of patients covariates (gestational age, postnatal age, postconceptual age, body weight, creatinine clearance calculated by Schwartz formula, etc) on estimated meropenem pharmacokinetic parameters. Results. The identified population pharmacokinetic parameters of meropenem in pre-term newborns (elimination half-lives T1/2 = 1.93 0.341 h; clearance CL = 0.26 0.085 L/h/ kg; volume of distribution V = 0.71 0.22 L/h) were in good agreement with those published in the literature for adults, neonates and older children. Pharmacokinetic/pharmacodynamic modeling demonstrated that a meropenem dosage regimen of 90 mg/kg/day administered using prolonged 3-hour infusion every 8 hours should be considered as potentially effective therapy if nosocomial infections with resistant organisms (MIC 8 mg/L) are treated. Conclusions. Neonates and especially pre-term neonates have a great pharmacokinetic variability. Meropenem dosing in premature newborns derived from population pharmacokinetic/pharmacodynamic model can partly overcome the variability, but not all pharmacokinetic variability can be explained by covariates in a model. Further personalizing based on Bayesian forecasting approach and a patients therapeutic drug monitoring data can help to achieve desired pharmacodynamic target.

Download Full-text

HPLC-analysis and preliminary pharmacokinetic parameter estimations of chloroquine

Pharmaceutisch Weekblad ◽

10.1007/bf02193437 ◽

1981 ◽

Vol 3 (1) ◽

pp. 1575-1579

Author(s):

B. Oosterhuis ◽

M. Van Den Berg ◽

J. Wetsteyn ◽

C. J. Van Boxtel

Keyword(s):

Pharmacokinetic Parameter ◽

Hplc Analysis ◽

Parameter Estimations

Download Full-text

An iterative curve stripping technique for pharmacokinetic parameter estimation

Journal of Pharmacy and Pharmacology ◽

10.1111/j.2042-7158.1986.tb04519.x ◽

1986 ◽

Vol 38 (2) ◽

pp. 97-101 ◽

Cited By ~ 15

Author(s):

Adrian Dunne

Keyword(s):

Parameter Estimation ◽

Pharmacokinetic Parameter

Download Full-text

Evaluation of a Bayesian Method for Predicting Vancomycin Dosing

DICP ◽

10.1177/106002808902300404 ◽

1989 ◽

Vol 23 (4) ◽

pp. 294-300 ◽

Cited By ~ 9

Author(s):

Michael E. Burton ◽

Donald L. Gentle ◽

Michael R. Vasko

Keyword(s):

Pharmacokinetic Parameter ◽

Peak Serum ◽

Population Estimates ◽

Parameter Estimates ◽

Initial Population ◽

Program Performance ◽

Concentration Data ◽

Bayesian Algorithm ◽

Large Patient ◽

Serum Vancomycin

The purpose of this study is to evaluate the performance of a vancomycin dosing program in predicting dosages necessary to achieve desired serum vancomycin concentrations in a relatively large patient population. With the completion of initial performance evaluation, revised pharmacokinetic parameter estimates derived in the initial evaluation are used to reevaluate program performance. The program uses population estimates of vancomycin's volume of distribution (Vd) and clearance (Cl) to initially predict dosing, then individualizes those estimates by a Bayesian algorithm (iterations) which uses dosing and the resulting serum vancomycin concentration data. Use of the Bayesian forecaster with one iteration significantly increases the calculated Cl value as compared with population estimates; two and three iterations significantly increase both Vd and Cl when compared with population estimates. Absolute values of the predicted minus observed peak serum vancomycin concentrations (accuracy) are 17.7 ± 14.0, 6.1 ± 3.6, and 3.4 ± 2.1 mg/L for dosing using population estimates, Bayesian with one iteration, and Bayesian with two iterations, respectively. Similarly, accuracy of predictions for trough concentrations is 13.8 ± 12.4, 3.5 ± 3.2, and 3.2 ± 2.6 mg/L for each method, respectively. Bias of dosing predictions in achieving desired peak and trough serum vancomycin concentrations is also significantly reduced by using the Bayesian algorithm. Use of the mean Vd and Cl values from three iterations as the starting parameters in a new group of 12 patients significantly improves program performance when compared with use of initial population parameters. Time of sampling for peak serum concentrations has no effect on program performance. In patients with impaired renal function, use of population estimates resulted in less accurate dosing prediction, but this less accurate performance was not observed with use of the Bayesian forecaster. These data demonstrate the accuracy and lack of bias in individualized dosing predictions using the Bayesian dosing method and the ability of revised pharmacokinetic parameter estimates to improve performance.

Download Full-text