scholarly journals Pharmacokinetics of perioperative FVIII in adult patients with haemophilia A: An external validation and development of an alternative population pharmacokinetic model

Haemophilia ◽  
2021 ◽  
Author(s):  
Jing Zhu ◽  
Yi Shuan Wu ◽  
Ryan J. Beechinor ◽  
Ryan Kemper ◽  
Laura H. Bukkems ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
External Validation ◽  
Adult Patients ◽  
Population Pharmacokinetic ◽  
Haemophilia A

scholarly journals Optimal sampling strategies for darunavir and external validation of the underlying population pharmacokinetic model

2020 ◽  
Author(s):  
Gabriel Stillemans ◽  
Leila Belkhir ◽  
Bernard Vandercam ◽  
Anne Vincent ◽  
Vincent Haufroid ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
External Validation ◽  
Diagnostic Methods ◽  
Validation Dataset ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Validation Set

Abstract Purpose A variety of diagnostic methods are available to validate the performance of population pharmacokinetic models. Internal validation, which applies these methods to the model building dataset and to additional data generated through Monte Carlo simulations, is often sufficient, but external validation, which requires a new dataset, is considered a more rigorous approach, especially if the model is to be used for predictive purposes. Our first objective was to validate a previously published population pharmacokinetic model of darunavir, an HIV protease inhibitor boosted with ritonavir or cobicistat. Our second objective was to use this model to derive optimal sampling strategies that maximize the amount of information collected with as few pharmacokinetic samples as possible. Methods A validation dataset comprising 164 sparsely sampled individuals using ritonavir-boosted darunavir was used for validation. Standard plots of predictions and residuals, NPDE, visual predictive check, and bootstrapping were applied to both the validation set and the combined learning/validation set in NONMEM to assess model performance. D-optimal designs for darunavir were then calculated in PopED and further evaluated in NONMEM through simulations. Results External validation confirmed model robustness and accuracy in most scenarios but also highlighted several limitations. The best one-, two-, and three-point sampling strategies were determined to be pre-dose (0 h); 0 and 4 h; and 1, 4, and 19 h, respectively. A combination of samples at 0, 1, and 4 h was comparable to the optimal three-point strategy. These could be used to reliably estimate individual pharmacokinetic parameters, although with fewer samples, precision decreased and the number of outliers increased significantly. Conclusions Optimal sampling strategies derived from this model could be used in clinical practice to enhance therapeutic drug monitoring or to conduct additional pharmacokinetic studies.

Reply to Baklouti et al., “Why Is It Desirable To Do the External Evaluation of a Population Pharmacokinetic Model?”

2021 ◽  
Author(s):  
Pier Giorgio Cojutti ◽  
Matteo Rinaldi ◽  
Eleonora Zamparini ◽  
Nicolò Rossi ◽  
Sara Tedeschi ◽  
...  
Keyword(s):  
Pharmacokinetic Study ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Optimal Treatment ◽  
Adult Patients ◽  
Population Pharmacokinetic ◽  
External Evaluation ◽  
Population Pharmacokinetic Study ◽  
Osteoarticular Infections ◽  
French Group

We thank Baklouti et al. (1) for commenting on our population pharmacokinetic study of dalbavancin for optimal treatment of adult patients with staphylococcal osteoarticular infections (2) and for suggesting that our model tends to underestimate the concentrations observed in a group of French patients (French group).…

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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