Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Baklouti S

PROVIDER: S-EPMC10581936 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Publications

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

Baklouti Sarah S Comets Emmanuelle E Gandia Peggy P Concordet Didier D

Clinical pharmacokinetics 20230917 11

<h4>Background</h4>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 analysi ...[more]

PMID: 37717242

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Dataset Information

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

Background

Objective

Methods

Results

Conclusion

Publications

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

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