scholarly journals External validation of the predictive performance of population pharmacokinetic models for phenobarbital in pediatric patients

2020 ◽  
Author(s):  
Sunae Ryu ◽  
Woo Jin Jung ◽  
Zheng Jiao ◽  
Jung Woo Chae ◽  
Hwi-yeol Yun
Keyword(s):  
External Validation ◽  
Predictive Performance ◽  
Validation Dataset ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Models ◽  
Bayesian Forecasting ◽  
Predictive Capability ◽  
Young Infants ◽  
Simulation Based

Aim: Several studies have reported population pharmacokinetic models for phenobarbital (PB), but the predictive performance of these models has not been well documented. This study aims to do external validation of the predictive performance in published pharmacokinetic models. Methods: Therapeutic drug monitoring data collected in neonates and young infants treated with PB for seizure control, was used for external validation. A literature review was conducted through PubMed to identify population pharmacokinetic models. Prediction- and simulation-based diagnostics, and Bayesian forecasting were performed for external validation. The incorporation of size or maturity functions into the published models was also tested for prediction improvement. Results: A total of 79 serum concentrations from 28 subjects were included in the external validation dataset. Seven population pharmacokinetic studies of PB were selected for evaluation. The model by Voller et al. [27] showed the best performance concerning prediction-based evaluation. In simulation-based analyses, the normalized prediction distribution error of two models (those of Shellhaas et al. [24] and Marsot et al. [25]) obeyed a normal distribution. Bayesian forecasting with more than one observation improved predictive capability. Incorporation of both allometric size scaling and maturation function generally enhanced the predictive performance, but with marked improvement for the adult pharmacokinetic model. Conclusion: The predictive performance of published pharmacokinetic models of PB was diverse, and validation may be necessary to extrapolate to different clinical settings. Our findings suggest that Bayesian forecasting improves the predictive capability of individual concentrations for pediatrics.

scholarly journals External Evaluation of Vancomycin Population Pharmacokinetic Models at Two Clinical Centers

2021 ◽  
Vol 12 ◽  
Author(s):  
Yi-Xi Liu ◽  
Haini Wen ◽  
Wan-Jie Niu ◽  
Jing-Jing Li ◽  
Zhi-Ling Li ◽  
...  
Keyword(s):  
Serum Creatinine ◽  
Prediction Error ◽  
Visual Predictive Check ◽  
Model Performance ◽  
Predictive Performance ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Models ◽  
Bayesian Forecasting ◽  
Simulation Based ◽  
Prediction And Simulation

Background: Numerous vancomycin population pharmacokinetic models in neonates have been published; however, their predictive performances remain unknown. This study aims to evaluate their external predictability and explore the factors that might affect model performance.Methods: Published population pharmacokinetic models in neonates were identified from the literature and evaluated using datasets from two clinical centers, including 171 neonates with a total of 319 measurements of vancomycin levels. Predictive performance was assessed by prediction- and simulation-based diagnostics and Bayesian forecasting. Furthermore, the effect of model structure and a number of identified covariates was also investigated.Results: Eighteen published pharmacokinetic models of vancomycin were identified after a systematic literature search. Using prediction-based diagnostics, no model had a median prediction error of ≤ ± 15%, a median absolute prediction error of ≤30%, and a percentage of prediction error that fell within ±30% of >50%. A simulation-based visual predictive check of most models showed there were large deviations between observations and simulations. After Bayesian forecasting with one or two prior observations, the predicted performance improved significantly. Weight, age, and serum creatinine were identified as the most important covariates. Moreover, employing a maturation model based on weight and age as well as nonlinear model to incorporate serum creatinine level significantly improved predictive performance.Conclusion: The predictability of the pharmacokinetic models for vancomycin is closely related to the approach used for modeling covariates. Bayesian forecasting can significantly improve the predictive performance of models.

POPULATION PHARMACOKINETICS AND DOSING OPTIMIZATION OF TEICOPLANIN IN CHILDREN WITH MALIGNANT HAEMATOLOGICAL DISEASE

2015 ◽  
Vol 101 (1) ◽  
pp. e1.41-e1
Author(s):  
Wei Zhao ◽  
Daolun Zhang ◽  
Thomas Storme ◽  
André Baruchel ◽  
Xavier Declèves ◽  
...  
Keyword(s):  
Population Pharmacokinetics ◽  
Haematological Malignancy ◽  
External Validation ◽  
Predictive Performance ◽  
Paediatric Population ◽  
Pharmacokinetic Parameters ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
High Risk Population ◽  
Dosing Regimen

BackgroundChildren with haematological malignancy represent an identified subgroup of the paediatric population with specific pharmacokinetic parameters. In these patients, inadequate empirical antibacterial therapy may result in infection-related morbidity and increased mortality, making optimization of the dosing regimen essential. As paediatric data are limited, our aim was to evaluate the population pharmacokinetics of teicoplanin in order to define the appropriate dosing regimen in this high-risk population.MethodsThe current dose of teicoplanin was evaluated in children with haematological malignancy. Population pharmacokinetics of teicoplanin was analysed using NONMEM software. The dosing regimen was optimised based on the final model.ResultsEighty-five children (age range: 0.5 to 16.9 years) were included. Therapeutic drug monitoring and opportunistic samples (n=143) were available for analysis. With the current recommended dose of 10 mg/kg/day, 41 children (48%) had sub-therapeutic steady-state trough concentrations (Css,min<10 mg/liter). A two-compartment pharmacokinetic model with first-order elimination was developed. Systematic covariate analysis identified that bodyweight (size) and creatinine clearance significantly influenced teicoplanin clearance. The model was validated internally. Its predictive performance was further confirmed in an external validation. In order to reach the target AUC of 750 mg·h/L, 18 mg/kg was required for infants, 14 mg/kg for children and 12 mg/kg for adolescents. A patient-tailored dose regimen was further developed and reduced variability in AUC and Css,min values compared to the mg/kg-basis dose, making the modelling approach an important tool for dosing individualization.ConclusionsThis first population pharmacokinetic study of teicoplanin in children with haematological malignancy provided evidence-based support to individualize teicoplanin therapy in this vulnerable population.

scholarly journals Assessing Predictive Performance of Published Population Pharmacokinetic Models of Intravenous Tobramycin in Pediatric Patients

2016 ◽  
Vol 60 (6) ◽  
pp. 3407-3414 ◽  
Author(s):  
Celeste Bloomfield ◽  
Christine E. Staatz ◽  
Sean Unwin ◽  
Stefanie Hennig
Keyword(s):  
Pediatric Patients ◽  
Predictive Performance ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Data ◽  
Pharmacokinetic Models ◽  
Simulation Based ◽  
Disposition Model ◽  
Relationship Of ◽  
Mean Square Errors ◽  
Pharmacokinetic Behavior

Several population pharmacokinetic models describe the dose-exposure relationship of tobramycin in pediatric patients. Before the implementation of these models in clinical practice for dosage adjustment, their predictive performance should be externally evaluated. This study tested the predictive performance of all published population pharmacokinetic models of tobramycin developed for pediatric patients with an independent patient cohort. A literature search was conducted to identify suitable models for testing. Demographic and pharmacokinetic data were collected retrospectively from the medical records of pediatric patients who had received intravenous tobramycin. Tobramycin exposure was predicted from each model. Predictive performance was assessed by visual comparison of predictions to observations, by calculation of bias and imprecision, and through the use of simulation-based diagnostics. Eight population pharmacokinetic models were identified. A total of 269 concentration-time points from 41 pediatric patients with cystic fibrosis were collected for external evaluation. Three models consistently performed best in all evaluations and had mean errors ranging from −0.4 to 1.8 mg/liter, relative mean errors ranging from 4.9 to 29.4%, and root mean square errors ranging from 47.8 to 66.9%. Simulation-based diagnostics supported these findings. Models that allowed a two-compartment disposition generally had better predictive performance than those that used a one-compartment disposition model. Several published models of the pharmacokinetics of tobramycin showed reasonable low levels of bias, although all models seemed to have some problems with imprecision. This suggests that knowledge of typical pharmacokinetic behavior and patient covariate values alone without feedback concentration measurements from individual patients is not sufficient to make precise predictions.

scholarly journals Performance of Population Pharmacokinetic Models in Predicting Polymyxin B Exposures

2020 ◽  
Vol 8 (11) ◽  
pp. 1814
Author(s):  
Vincent Tam ◽  
Lawrence Lee ◽  
Tat-Ming Ng ◽  
Tze-Peng Lim ◽  
Benjamin Cherng ◽  
...  
Keyword(s):  
Bacterial Infections ◽  
Area Under The Curve ◽  
Predictive Performance ◽  
Total Body Weight ◽  
Polymyxin B ◽  
Multidrug Resistant ◽  
Patient Specific ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Models

Polymyxin B is the last line of defense in treating multidrug-resistant gram-negative bacterial infections. Dosing of polymyxin B is currently based on total body weight, and a substantial intersubject variability has been reported. We evaluated the performance of different population pharmacokinetic models to predict polymyxin B exposures observed in individual patients. In a prospective observational study, standard dosing (mean 2.5 mg/kg daily) was administered in 13 adult patients. Serial blood samples were obtained at steady state, and plasma polymyxin B concentrations were determined by a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. The best-fit estimates of clearance and daily doses were used to derive the observed area under the curve (AUC) in concentration–time profiles. For comparison, 5 different population pharmacokinetic models of polymyxin B were conditioned using patient-specific dosing and demographic (if applicable) variables to predict polymyxin B AUC of the same patient. The predictive performance of the models was assessed by the coefficient of correlation, bias, and precision. The correlations between observed and predicted AUC in all 5 models examined were poor (r2 < 0.2). Nonetheless, the models were reasonable in capturing AUC variability in the patient population. Therapeutic drug monitoring currently remains the only viable approach to individualized dosing.

scholarly journals P99 Clinical validation of published vancomycin population PK models in critically ill neonates

2019 ◽  
Vol 104 (6) ◽  
pp. e58.2-e59
Author(s):  
A van der Veen ◽  
RJ Keizer ◽  
W de Boode ◽  
A Somers ◽  
R Brüggemann ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
A Priori ◽  
Predictive Performance ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Suitable Model ◽  
List Type ◽  
A Posteriori ◽  
Target Attainment

BackgroundVancomycin is commonly used for treatment of severe Gram+ neonatal infections. Currently, even with the use of optimized dosing regimens and therapeutic drug monitoring (TDM), target attainment rates are abominable, leaving patients at risk for therapeutic failure and toxicity. Model-informed precision dosing (MIPD) offers a large potential to improve therapy in the individual patient.The aim of this study was to identify a suitable model for bedside MIPD by assessing the predictive performance of published population pharmacokinetic (popPK) models.MethodsA literature search was conducted to identify parametric popPK models. PK vancomycin data were retrospectively collected from NICU patients at the Radboud University Hospital, Nijmegen, The Netherlands. The model predictive performance was assessed by comparison of predictions to observations, calculation of bias (Mean Percentage Errors, MPE) and imprecision (Normalized Root Mean Squared Errors, NRMSE). Evaluations included both a priori (model covariate input) and a posteriori (model covariate and TDM concentration input) scenarios.Results265 TDM measurements from 65 neonates (median postmenstrual age:32 weeks [range:25–45 weeks]; median weight:1281g [range:597–5360g]; median serum creatinine:0,48 mg/dL [range:0,15–1,28 mg/dL]) were used for model evaluation. Six popPK models were evaluated1–6. A posteriori predictions of all models were consistently more accurate and precise compared to the a priori (starting dose) predictions. PopPK models of Frymoyer et al. and Capparelli et al. consistently performed best through all evaluations in both the a priori and a posteriori scenario (MPE ranging from -18 to 6,4% in a priori scenario and -6,5 to -3,8% in a posteriori scenario; NRMSE ranging from 34 to 40% in a priori scenario and 23 to 24% in a posteriori scenario).ConclusionLarge differences in predictive performance of popPK models were observed. Repeated therapeutic drug monitoring remains necessary to increase target attainment rate. Best performing models for bedside MIPD were identified in our patient population.ReferencesZhao W, Lopez E, Biran V, et al. ( 2013). Vancomycin continuous infusion in neonates: Dosing optimisation and therapeutic drug monitoring. Arch Dis Child;98(6):449–453.Capparelli EV, Lane JR, Romanowski GL, et al. ( 2001). The influences of renal function and maturation on vancomycin elimination in newborns and infants. J Clin Pharmacol, 41:927–934.De Cock RFW, Allegaert K, Brussee JM, et al. ( 2014). Simultaneous pharmacokinetic modeling of gentamicin, tobramycin and vancomycin clearance from neonates to adults: towards a semi-physiological function for maturation in glomerular filtration. Pharm Res;31(10):2642–2654.Frymoyer A, Hersh AL, El-Komy MH, et al. ( 2014). Association between vancomycin trough concentration and area under the concentration-time curve in neonates. Antimicrob Agents Chemother, 58(11):6454–6461.Anderson BJ, Allegaert K, Van Den Anker JN, Cossey V, Holford NHG. ( 2006). Vancomycin pharmacokinetics in preterm neonates and the prediction of adult clearance. Br J Clin Pharmacol;63(1):75–84.Germovsek E, Osborne L, Gunaratnam F, Lounis SA, Busquets FB, Sinha AK. ( 2019). Development and external evaluation of a population pharmacokinetic model for continuous and intermittent administration of vancomycin in neonates and infants using prospectively collected data. J Antimicrob Chemother, 1–9.Disclosure(s)R. Keizer is an employee and stockholder of InsightRX.

scholarly journals Towards Rational Dosing Algorithms for Vancomycin in Neonates and Infants Based on Population Pharmacokinetic Modeling

2015 ◽  
Vol 60 (2) ◽  
pp. 1013-1021 ◽  
Author(s):  
Esther J. H. Janssen ◽  
Pyry A. J. Välitalo ◽  
Karel Allegaert ◽  
Roosmarijn F. W. de Cock ◽  
Sinno H. P. Simons ◽  
...  
Keyword(s):  
Pediatric Population ◽  
External Validation ◽  
Population Pharmacokinetic ◽  
Target Area ◽  
Pharmacokinetic Models ◽  
Time Curve ◽  
Population Pharmacokinetic Modeling ◽  
Model Based ◽  
Dosing Algorithm ◽  
Dosing Regimens

ABSTRACTBecause of the recent awareness that vancomycin doses should aim to meet a target area under the concentration-time curve (AUC) instead of trough concentrations, more aggressive dosing regimens are warranted also in the pediatric population. In this study, both neonatal and pediatric pharmacokinetic models for vancomycin were externally evaluated and subsequently used to derive model-based dosing algorithms for neonates, infants, and children. For the external validation, predictions from previously published pharmacokinetic models were compared to new data. Simulations were performed in order to evaluate current dosing regimens and to propose a model-based dosing algorithm. The AUC/MIC over 24 h (AUC24/MIC) was evaluated for all investigated dosing schedules (target of >400), without any concentration exceeding 40 mg/liter. Both the neonatal and pediatric models of vancomycin performed well in the external data sets, resulting in concentrations that were predicted correctly and without bias. For neonates, a dosing algorithm based on body weight at birth and postnatal age is proposed, with daily doses divided over three to four doses. For infants aged <1 year, doses between 32 and 60 mg/kg/day over four doses are proposed, while above 1 year of age, 60 mg/kg/day seems appropriate. As the time to reach steady-state concentrations varies from 155 h in preterm infants to 36 h in children aged >1 year, an initial loading dose is proposed. Based on the externally validated neonatal and pediatric vancomycin models, novel dosing algorithms are proposed for neonates and children aged <1 year. For children aged 1 year and older, the currently advised maintenance dose of 60 mg/kg/day seems appropriate.

scholarly journals Exploring sirolimus pharmacokinetic variability using data available from the routine clinical care of renal transplant patients – population pharmacokinetic approach

2019 ◽  
Vol 38 (3) ◽  
pp. 323-331
Author(s):  
Bojana Golubović ◽  
Katarina Vučićević ◽  
Dragana Radivojević ◽  
Sandra Vezmar Kovačević ◽  
Milica Prostran ◽  
...  
Keyword(s):  
Liver Function ◽  
Population Analysis ◽  
Clinical Care ◽  
External Validation ◽  
Therapeutic Index ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Variability ◽  
Dose Individualization ◽  
Transplant Patients

Summary Background Due to wide intra- and inter-individual pharmacokinetic variability and narrow therapeutic index of sirolimus, the therapeutic drug monitoring (TDM) of sirolimus with detailed biochemical and clinical monitoring is necessary for dose individualization in kidney transplant patients. The purpose of the study was to explore and identify factors that contribute to pharmacokinetic variability by developing and validating a population model using routine TDM data and routinely monitored biochemical and clinical parameters. Methods The data obtained by routine monitoring of 38 patients over a period of one year from the sirolimus treatment initiation, were collected from patients’ records. Population analysis was performed using the software NONMEM®. The validity of the model was tested by the internal and external validation techniques. Results The pharmacokinetic variability was partially explained with patient’s age and liver function. CL/F was found to decrease with age. According to the developed model, sirolimus CL/F decreases by, in average, 37% in patients with aspartate aminotransferase (AST) greater than 37 IU/L. The internal and external validation confirmed the satisfactory prediction of the developed model. Conclusions The population modeling of routinely monitored data allowed quantification of the age and liver function influence on sirolimus CL/F. According to the final model, patients with compromised liver function expressed via AST values require careful monitoring and dosing adjustments. Proven good predictive performance makes this model a useful tool in everyday clinical practice.

scholarly journals Model Based Identification of Linezolid Exposure–toxicity Thresholds in Hospitalized Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Jie Fang ◽  
Xiao-Shan Zhang ◽  
Chun-Hong Zhang ◽  
Zi-Ye Zhou ◽  
Lu Han ◽  
...  
Keyword(s):  
Steady State ◽  
Serum Albumin ◽  
White Cell Count ◽  
Plasma Concentrations ◽  
Regression Tree ◽  
Predictive Performance ◽  
Volume Of Distribution ◽  
Classification And Regression Tree ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic

Evidence supports linezolid therapeutic drug monitoring as the exposure–response relationship has been identified for toxicity among patients receiving linezolid, but the data to establish the upper limit are limited and the published toxicity thresholds range widely. The purpose of this study was to determine the linezolid exposure–toxicity thresholds to improve the safety of linezolid. This is a multicenter retrospective study of adult patients treated with linezolid from 2018 to 2019. The population pharmacokinetic model of linezolid was established based on 270 plasma concentrations in 152 patients, which showed creatinine clearance and white cell count are covariates affecting the clearance of linezolid, and serum albumin is the covariate affecting the volume of distribution. Classification and regression tree analysis was used to determine the linezolid exposure thresholds associated with an increased probability of toxicity. Among 141 patients included for toxicity analysis, the rate of occurring toxicity was significantly higher among patients with an AUC0-24, d1 ≥163 mg h/L, AUC0-24, d2 ≥207 mg h/L, AUC0-24, ss ≥210 mg h/L, and Cmin,d2 ≥6.9 mg/L, Cmin,ss ≥6.9 mg/L, while no threshold was discovered for Cmin, d1. Those exposure thresholds and duration of linezolid treatment were independently associated with linezolid-related toxicity in the logistic regression analyses. In addition, the predictive performance of the AUC0-24 and Cmin thresholds at day 2 and steady state were close. Considering that the AUC estimation is cumbersome, Cmin threshold at 48 h and steady state with a value of ≥6.9 mg/L is recommended to improve safety, especially for patients with renal insufficiency and patients with low serum albumin.

scholarly journals Simplified Dosing Regimens for Gentamicin in Neonatal Sepsis

2021 ◽  
Vol 12 ◽  
Author(s):  
S. D’Agate ◽  
F. Tshinanu Musuamba ◽  
E. Jacqz-Aigrain ◽  
O. Della Pasqua
Keyword(s):  
Body Weight ◽  
Bacterial Infections ◽  
Drug Disposition ◽  
External Validation ◽  
World Health ◽  
Fixed Dose ◽  
Therapeutic Drug ◽  
Resource Limited Settings ◽  
Young Infants ◽  
Resource Limited

Background: The effectiveness of antibiotics for the treatment of severe bacterial infections in newborns in resource-limited settings has been determined by empirical evidence. However, such an approach does not warrant optimal exposure to antibiotic agents, which are known to show different disposition characteristics in this population. Here we evaluate the rationale for a simplified regimen of gentamicin taking into account the effect of body size and organ maturation on pharmacokinetics. The analysis is supported by efficacy data from a series of clinical trials in this population.Methods: A previously published pharmacokinetic model was used to simulate gentamicin concentration vs. time profiles in a virtual cohort of neonates. Model predictive performance was assessed by supplementary external validation procedures using therapeutic drug monitoring data collected in neonates and young infants with or without sepsis. Subsequently, clinical trial simulations were performed to characterize the exposure to intra-muscular gentamicin after a q.d. regimen. The selection of a simplified regimen was based on peak and trough drug levels during the course of treatment.Results: In contrast to current World Health Organization guidelines, which recommend gentamicin doses between 5 and 7.5 mg/kg, our analysis shows that gentamicin can be used as a fixed dose regimen according to three weight-bands: 10 mg for patients with body weight &lt;2.5 kg, 16 mg for patients with body weight between 2.5 and 4 kg, and 30 mg for those with body weight &gt;4 kg.Conclusion: The choice of the dose of an antibiotic must be supported by a strong scientific rationale, taking into account the differences in drug disposition in the target patient population. Our analysis reveals that a simplified regimen is feasible and could be used in resource-limited settings for the treatment of sepsis in neonates and young infants with sepsis aged 0–59 days.

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.

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