Phenobarbital in intensive care unit pediatric population: predictive performances of population pharmacokinetic model

2017 ◽  
Vol 31 (5) ◽  
pp. 558-566 ◽  
Author(s):  
Amélie Marsot ◽  
Fabrice Michel ◽  
Estelle Chasseloup ◽  
Olivier Paut ◽  
Romain Guilhaumou ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Pediatric Population ◽  
Population Pharmacokinetic

scholarly journals Population Pharmacokinetic Model and Pharmacokinetic Target Attainment of Micafungin in Intensive Care Unit Patients

2017 ◽  
Vol 56 (10) ◽  
pp. 1197-1206 ◽  
Author(s):  
Lisa C. Martial ◽  
Rob ter Heine ◽  
Jeroen A. Schouten ◽  
Nicole G. Hunfeld ◽  
Henk J. van Leeuwen ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic ◽  
Target Attainment

scholarly journals Validation of a Pediatric Population Pharmacokinetic Model for Vancomycin

2015 ◽  
Vol 37 (3) ◽  
pp. 413-416 ◽  
Author(s):  
Andrea Hahn ◽  
Robert W. Frenck ◽  
Yuanshu Zou ◽  
Alexander A. Vinks
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Pediatric Population ◽  
Population Pharmacokinetic

scholarly journals Population Pharmacokinetics of Ceftazidime in Intensive Care Unit Patients: Influence of Glomerular Filtration Rate, Mechanical Ventilation, and Reason for Admission

2009 ◽  
Vol 53 (10) ◽  
pp. 4483-4489 ◽  
Author(s):  
Bernard Georges ◽  
Jean-Marie Conil ◽  
Thierry Seguin ◽  
Stéphanie Ruiz ◽  
Vincent Minville ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Glomerular Filtration Rate ◽  
Glomerular Filtration ◽  
Filtration Rate ◽  
Pharmacokinetic Model ◽  
Volume Of Distribution ◽  
Population Pharmacokinetic ◽  
Reason For Admission

ABSTRACT The aim of this study was to develop a population-pharmacokinetic model of ceftazidime in intensive care unit patients to include the influence of patients' characteristics on the pharmacokinetics. Forty-nine patients for model building and 23 patients for validation were included in a randomized study. They received ceftazidime at 2 g three times a day or as 6 g per day continuously. A NONMEM pharmacokinetic model was constructed, and the influences of covariates were studied. The model was validated by a comparison of the predicted and observed concentrations. A final model was elaborated from the whole population. Total clearance (CL) was significantly correlated with the glomerular filtration rate (GFR) calculated by modification of the diet in renal disease (MDRD), the central volume of distribution (V1) with intubation, and the peripheral volume of distribution (V2) with the reason for admission. The mean pharmacokinetic parameters were as follows: CL, 5.48 liters/h, 40%; V1, 10.48 liters, 34%; V2, 32.12 liters, 59%; total volume, 42.60 liters, 45%; and intercompartmental clearance, 16.19 liters/h, 42%. In the polytrauma population (mechanically ventilated), the time above the MIC at steady state never corresponds to 100% for discontinuous administration, and the target concentration of five times the MIC was reached with a 6-g/day dose only for patients with an MDRD of <150 ml/min. We showed that the GFR-MDRD, mechanical ventilation, and the reason for admission may influence the achieved concentrations of ceftazidime. Our model allows the a priori dosing to be adjusted to the individual patient.

scholarly journals Oseltamivir Pharmacokinetics and Clinical Experience in Neonates and Infants during an Outbreak of H1N1 Influenza A Virus Infection in a Neonatal Intensive Care Unit

2012 ◽  
Vol 56 (7) ◽  
pp. 3833-3840 ◽  
Author(s):  
Joseph F. Standing ◽  
Angela Nika ◽  
Vasileios Tsagris ◽  
Ioannis Kapetanakis ◽  
Helena C. Maltezou ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Influenza A ◽  
Neonatal Intensive Care ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic ◽  
Oseltamivir Carboxylate ◽  
Influenza A H1n1 ◽  
Neonates And Infants

ABSTRACTDetailed oseltamivir pharmacokinetics have yet to be reported in neonates and infants; this group is at high risk of serious influenza-associated complications. Extrapolation of doses from older patients is complicated by rapid organ and drug-metabolizing enzyme maturation. A pharmacokinetic study has been conducted during an influenza A(H1N1) outbreak in a neonatal intensive care unit. Each included patient provided 4 samples for oseltamivir and 4 samples for its active metabolite oseltamivir carboxylate. A population pharmacokinetic model was developed with NONMEM. Allometric weight scaling and maturation functions were addeda priorito scale for size and age based on literature values. Nine neonates and infants were recruited. A physiologically parameterized pharmacokinetic model predicted typical day 1 area under the curve (AUC0-12) values of 1,966 and 2,484 μg · h/liter for neonates and infants of ≤37 weeks of postmenstrual age (PMA) and >37 weeks of PMA treated with 1 mg/kg of body weight and 2 mg/kg, respectively. The corresponding steady-state AUC0-12values were 3,670 and 4,559 μg · h/liter. Premature neonates treated with 1 mg/kg and term babies treated with 2 mg/kg should have average oseltamivir carboxylate concentrations in a range similar to that for adults treated with 75 mg, corresponding to >200-fold above the half-maximal inhibitory concentration (IC50) value for influenza A(H1N1) from the start of therapy.

scholarly journals Population pharmacokinetic modeling and clinical application of vancomycin in Chinese patients hospitalized in intensive care units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhong Lin ◽  
Dan-yang Chen ◽  
Yan-Wu Zhu ◽  
Zheng-li Jiang ◽  
Ke Cui ◽  
...  
Keyword(s):  
Intensive Care ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
External Validation ◽  
Chinese Patients ◽  
Target Range ◽  
Population Pharmacokinetic ◽  
Icu Patients ◽  
Final Model ◽  
Trough Concentrations

AbstractManagement of vancomycin administration for intensive care units (ICU) patients remains a challenge. The aim of this study was to describe a population pharmacokinetic model of vancomycin for optimizing the dose regimen for ICU patients. We prospectively enrolled 466 vancomycin-treated patients hospitalized in the ICU, collected trough or approach peak blood samples of vancomycin and recorded corresponding clinical information from July 2015 to December 2017 at Tai Zhou Hospital of Zhejiang Province. The pharmacokinetics of vancomycin was analyzed by nonlinear mixed effects modeling with Kinetica software. Internal and external validation was evaluated by the maximum likelihood method. Then, the individual dosing regimens of the 92 patients hospitalized in the ICU whose steady state trough concentrations exceeded the target range (10–20 μg/ml) were adjusted by the Bayes feedback method. The final population pharmacokinetic model show that clearance rate (CL) of vancomycin will be raised under the conditions of dopamine combined treatment, severe burn status (Burn-S) and increased total body weight (TBW), but reduced under the conditions of increased serum creatinine (Cr) and continuous renal replacement therapy status; Meanwhile, the apparent distribution volume (V) of vancomycin will be enhanced under the terms of increased TBW, however decreased under the terms of increased age and Cr. The population pharmacokinetic parameters (CL and V) according to the final model were 3.16 (95%CI 2.83, 3.40) L/h and 60.71 (95%CI 53.15, 67.46). The mean absolute prediction error for external validation by the final model was 12.61% (95CI 8.77%, 16.45%). Finally, the prediction accuracy of 90.21% of the patients’ detected trough concentrations that were distributed in the target range of 10–20 μg/ml after dosing adjustment was found to be adequate. There is significant heterogeneity in the CL and V of vancomycin in ICU patients. The constructed model is sufficiently precise for the Bayesian dose prediction of vancomycin concentrations for the population of ICU Chinese 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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