External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps

Hassani, Mehdi El; Marsot, Amélie

doi:10.1007/s40262-023-01233-7

Cited by 9 publications

(4 citation statements)

References 64 publications

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“…23 This scarcity of external validation studies can be attributed in part to the absence of guidelines for population PK modeling, which hampers the precise and reliable utilization of PK models in clinical settings. 24 In this study, we overcame these challenges by using an independent data set and using multiple validation tools to evaluate the predictive performance of our previously developed gentamicin PK model in neonates with perinatal asphyxia undergoing controlled TH. Our findings demonstrate that the model performed well in predicting gentamicin concentrations during all phases of controlled TH.…”

Section: Discussionmentioning

confidence: 99%

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Predictive Performance of a Gentamicin Pharmacokinetic Model in Term Neonates with Perinatal Asphyxia Undergoing Controlled Therapeutic Hypothermia

van der Veer,

de Haan,

Franken

et al. 2024

Therapeutic Drug Monitoring

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Background: Model validation procedures are crucial when population pharmacokinetic (PK) models are used to develop dosing algorithms and to perform model-informed precision dosing. We have previously published a population PK model describing the PK of gentamicin in term neonates with perinatal asphyxia during controlled therapeutic hypothermia (TH), which showed altered gentamicin clearance during the hypothermic phase dependent on gestational age and weight. In this study, the predictive performance and generalizability of this model were assessed using an independent data set of neonates with perinatal asphyxia undergoing controlled TH. Methods: The external data set contained a subset of neonates included in the prospective observational multicenter PharmaCool Study. Predictive performance was assessed by visually inspecting observed-versus-predicted concentration plots and calculating bias and precision. In addition, simulation-based diagnostics, model refitting, and bootstrap analyses were performed. Results: The external data set included 323 gentamicin concentrations of 39 neonates. Both the model-building and external data set included neonates from multiple centers. The original gentamicin PK model predicted the observed gentamicin concentrations with adequate accuracy and precision during all phases of controlled TH. Model appropriateness was confirmed with prediction-corrected visual predictive checks and normalized prediction distribution error analyses. Model refitting to the merged data set (n = 86 neonates with 935 samples) showed accurate estimation of PK parameters. Conclusions: The results of this external validation study justify the generalizability of the gentamicin dosing recommendations made in the original study for neonates with perinatal asphyxia undergoing controlled TH (5 mg/kg every 36 or 24 h with gestational age 36–41 and 42 wk, respectively) and its applicability in model-informed precision dosing.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Predictive Performance of a Gentamicin Pharmacokinetic Model in Term Neonates with Perinatal Asphyxia Undergoing Controlled Therapeutic Hypothermia

van der Veer,

de Haan,

Franken

et al. 2024

Therapeutic Drug Monitoring

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“…Another direct application of this method is to use it for selecting a population PK model in the context of therapeutic drug monitoring (TDM). Currently, in hospital practice, model evaluation remains difficult due to the lack of guidelines [ 14 ]. However, selecting the correct model is a crucial step to ensure that the predictions made are accurate and that the resulting dosage regimen is appropriate.…”

Section: Discussionmentioning

confidence: 99%

Multivariate Exact Discrepancy: A New Tool for PK/PD Model Evaluation

Baklouti,

Comets,

Gandia

et al. 2023

Clin Pharmacokinet

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Background Pharmacokinetic models are evaluated using three types of metrics: those based on estimating the typical pharmacokinetic parameters, those based on predicting individual pharmacokinetic parameters and those that compare data and model distributions. In the third groups of metrics, the best-known methods are Visual Predictive Check (VPC) and Normalised Prediction Distribution Error (NPDE). Despite their usefulness, these methods have some limitations, especially for the analysis of dependent concentrations, i.e., evaluated in the same patient. Objective In this work, we propose an evaluation method that accounts for the dependency between concentrations. Methods Thanks to the study of the distribution of simulated vectors of concentrations, the method provides one probability per individual that its observations (i.e., concentrations) come from the studied model. The higher the probability, the better the model fits the individual. By examining the distribution of these probabilities for a set of individuals, we can evaluate the model as a whole. Results We demonstrate the effectiveness of our method through two examples. Our approach successfully detects misspecification in the structural model and identifies outlier kinetics in a set of kinetics. Conclusion We propose a straightforward method for evaluating models during their development and selecting a model to perform therapeutic drug monitoring. Based on our preliminary results, the method is very promising but needs to be validated on a larger scale. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-023-01296-6.

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“…2 ) for each model [ 12 , 13 ], where n represents the total number of patients and obs and pred indicate the observed and forecasted infliximab concentrations, respectively. No rRMSE or rBias threshold for clinical acceptability was prespecified, but lower values indicated more precise predictions [ 14 ]. We did not compute the commonly reported mean absolute percentage error or mean percentage error as many observations in our dataset were close to zero.…”

Section: Methodsmentioning

confidence: 99%

Performance of Eight Infliximab Population Pharmacokinetic Models in a Cohort of Dutch Children with Inflammatory Bowel Disease

Bevers,

Keizer,

Wong

et al. 2024

Clin Pharmacokinet

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Background and Objective Efficacy of infliximab in children with inflammatory bowel disease can be enhanced when serum concentrations are measured and further dosing is adjusted to achieve and maintain a target concentration. Use of a population pharmacokinetic model may help to predict an individual’s infliximab dose requirement. The aim of this study was to evaluate the predictive performance of available infliximab population pharmacokinetic models in an independent cohort of Dutch children with inflammatory bowel disease. Methods In this retrospective study, we used data of 70 children with inflammatory bowel disease (443 infliximab concentrations) to evaluate eight models that focused on infliximab pharmacokinetic models in individuals with inflammatory bowel disease, preferably aged ≤ 18 years. Predictive performance was evaluated with prior predictions (based solely on patient-specific covariates) and posterior predictions (based on covariates and infliximab trough concentrations). Model accuracy and precision were calculated with relative bias and relative root mean square error and we determined the classification accuracy at the trough concentration target of ≥ 5 mg/L. Results The population pharmacokinetic model by Fasanmade was identified to be most appropriate for the total dataset (relative bias before/after therapeutic drug monitoring: −20.7%/11.2% and relative root mean square error before/after therapeutic drug monitoring: 84.1%/51.6%), although differences between models were small and several were deemed suitable for clinical use. For the Fasanmade model, sensitivity and specificity for maximum posterior predictions for the next infliximab trough concentration to be ≥ 5 mg/L were respectively 83.5% and 80% with an area under the receiver operating characteristic curve of 0.870. Conclusions In our paediatric cohort, various models provided acceptable predictive performance, with the Fasanmade model deemed most suitable for clinical use. Model-informed precision dosing can therefore be expected to help to maintain infliximab trough concentrations in the target range. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-024-01354-7.

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External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps

Cited by 9 publications

References 64 publications

Predictive Performance of a Gentamicin Pharmacokinetic Model in Term Neonates with Perinatal Asphyxia Undergoing Controlled Therapeutic Hypothermia

Predictive Performance of a Gentamicin Pharmacokinetic Model in Term Neonates with Perinatal Asphyxia Undergoing Controlled Therapeutic Hypothermia

Multivariate Exact Discrepancy: A New Tool for PK/PD Model Evaluation

Performance of Eight Infliximab Population Pharmacokinetic Models in a Cohort of Dutch Children with Inflammatory Bowel Disease

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