scholarly journals Individualized population pharmacokinetic model with limited sampling for cyclosporine monitoring after liver transplantation in clinical practice

2007 ◽  
Vol 26 (10) ◽  
pp. 1447-1454 ◽  
Author(s):  
P. LANGERS ◽  
S. C. L. M. CREMERS ◽  
J. DEN HARTIGH ◽  
E. M. T. RIJNBEEK ◽  
J. RINGERS ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Clinical Practice ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic ◽  
Limited Sampling

scholarly journals Mining Small Routine Clinical Data: A Population Pharmacokinetic Model and Optimal Sampling Times of Capecitabine and its Metabolites

2019 ◽  
Vol 22 ◽  
pp. 112-121 ◽  
Author(s):  
Esther Oyaga-Iriarte ◽  
Asier Insausti ◽  
Lorea Bueno ◽  
Onintza Sayar ◽  
Azucena Aldaz
Keyword(s):  
Clinical Practice ◽  
Clinical Data ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Visual Predictive Check ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Multicompartmental Model ◽  
Sampling Times

Purpose: The present study was performed to demonstrate that small amounts of routine clinical data allow to generate valuable knowledge. Concretely, the aims of this research were to build a joint population pharmacokinetic model for capecitabine and three of its metabolites (5-DFUR, 5-FU and 5-FUH2) and to determine optimal sampling times for therapeutic drug monitoring. Methods: We used data of 7 treatment cycles of capecitabine in patients with metastatic colorectal cancer. The population pharmacokinetic model was built as a multicompartmental model using NONMEM and was internally validated by visual predictive check. Optimal sampling times were estimated using PFIM 4.0 following D-optimality criterion. Results: The final model was a multicompartmental model which represented the sequential transformations from capecitabine to its metabolites 5-DFUR, 5-FU and 5-FUH2 and was correctly validated. The optimal sampling times were 0.546, 0.892, 1.562, 4.736 and 8 hours after the administration of the drug. For its correct implementation in clinical practice, the values were rounded to 0.5, 1, 1.5, 5 and 8 hours after the administration of the drug. Conclusions: Capecitabine, 5-DFUR, 5-FU and 5-FUH2 can be correctly described by the joint multicompartmental model presented in this work. The aforementioned times are optimal to maximize the information of samples. Useful knowledge can be obtained for clinical practice from small databases.

scholarly journals Pharmacokinetic Modeling and Limited Sampling Strategies Based on Healthy Volunteers for Monitoring of Ertapenem in Patients with Multidrug-Resistant Tuberculosis

2017 ◽  
Vol 61 (4) ◽  
Author(s):  
S. P. van Rijn ◽  
M. A. Zuur ◽  
R. van Altena ◽  
O. W. Akkerman ◽  
J. H. Proost ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Sampling Strategy ◽  
Free Fraction ◽  
Limited Sampling Strategy ◽  
Population Pharmacokinetic ◽  
Time Curve ◽  
Limited Sampling ◽  
Mdr Tb

ABSTRACT Ertapenem is a broad-spectrum carbapenem antibiotic whose activity against Mycobacterium tuberculosis is being explored. Carbapenems have antibacterial activity when the plasma concentration exceeds the MIC at least 40% of the time (40% T MIC). To assess the 40% T MIC in multidrug-resistant tuberculosis (MDR-TB) patients, a limited sampling strategy was developed using a population pharmacokinetic model based on data for healthy volunteers. A two-compartment population pharmacokinetic model was developed with data for 42 healthy volunteers using an iterative two-stage Bayesian method. External validation was performed by Bayesian fitting of the model developed with data for volunteers to the data for individual MDR-TB patients (in which the fitted values of the area under the concentration-time curve from 0 to 24 h [AUC0–24, fit values] were used) using the population model developed for volunteers as a prior. A Monte Carlo simulation (n = 1,000) was used to evaluate limited sampling strategies. Additionally, the 40% T MIC with the free fraction (f 40% T MIC) of ertapenem in MDR-TB patients was estimated with the population pharmacokinetic model. The population pharmacokinetic model that was developed was shown to overestimate the area under the concentration-time curve from 0 to 24 h (AUC0–24) in MDR-TB patients by 6.8% (range, −17.2 to 30.7%). The best-performing limited sampling strategy, which had a time restriction of 0 to 6 h, was found to be sampling at 1 and 5 h (r 2 = 0.78, mean prediction error = −0.33%, root mean square error = 5.5%). Drug exposure was overestimated by a mean percentage of 4.2% (range, −15.2 to 23.6%). When a free fraction of 5% was considered and the MIC was set at 0.5 mg/liter, the minimum f 40% T MIC would have been exceeded in 9 out of 12 patients. A population pharmacokinetic model and limited sampling strategy, developed using data from healthy volunteers, were shown to be adequate to predict ertapenem exposure in MDR-TB patients.

scholarly journals Population Pharmacokinetic Model for Intravenous ASN100 in Healthy Subjects

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S529-S529
Author(s):  
Scott A Van Wart ◽  
Christopher Stevens ◽  
Zoltan Magyarics ◽  
Steven A Luperchio ◽  
Paul G Ambrose
Keyword(s):  
Healthy Subjects ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic

scholarly journals Pharmacokinetics and Pharmacogenetics of Cyclophosphamide in a Neonate and Infant Childhood Cancer Patient Population

2021 ◽  
Vol 14 (3) ◽  
pp. 272
Author(s):  
Shelby Barnett ◽  
Julie Errington ◽  
Julieann Sludden ◽  
David Jamieson ◽  
Vianney Poinsignon ◽  
...  
Keyword(s):  
Cancer Patient ◽  
Childhood Cancer ◽  
Patient Population ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Drug Clearance ◽  
Current Data ◽  
Population Pharmacokinetic ◽  
Older Children ◽  
Patient Groups

Infants and young children represent an important but much understudied childhood cancer patient population. The pharmacokinetics and pharmacogenetics of the widely used anticancer prodrug cyclophosphamide were investigated in children <2 years of age. Concentrations of cyclophosphamide and selected metabolites were determined in patients administered cyclophosphamide at doses ranging from 100–1500 mg/m2 (5–75 mg/kg), with various infusion times as determined by the standard treatment regimen that each patient was receiving. Polymorphisms in genes including CYP2B6 and CYP2C19 were investigated. Data generated for cyclophosphamide were analysed using a previously published population pharmacokinetic model. Cyclophosphamide pharmacokinetics was assessed in 111 samples obtained from 25 patients ranging from 4–23 months of age. The average cyclophosphamide clearance for the patients was 46.6 mL/min/m2 (ranging from 9.4–153 mL/min/m2), with marked inter-patient variability observed (CV 41%). No significant differences in cyclophosphamide clearance or exposure (AUC) were observed between patient groups as separated by age or body weight. However, marked differences in drug clearance and metabolism were noted between the current data in children <2 years of age and recently published results from a comparable study conducted by our group in older children, which reported significantly lower cyclophosphamide clearance values and metabolite exposures using the same population pharmacokinetic model for analysis. Whilst this study demonstrates no significant differences in cyclophosphamide clearance in patients <2 years, it highlights large differences in dosing protocols across tumour types. Furthermore, the study suggests marked differences in cyclophosphamide clearance in children less than two years of age as compared to older patients.

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