Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?

BACKGROUND AND OBJECTIVES

Precision dosing requires selecting the appropriate population pharmacokinetic model, which can be assessed through external evaluations (EEs). The lack of understanding of how different study design factors influence EE study outcomes makes it challenging to select the most suitable model for clinical use. This study aimed to evaluate the impact of sample size, sampling strategy, and handling of concentrations below the lower limit of quantification (BLQ) on the outcomes of EE for four population pharmacokinetic models using vancomycin and tobramycin as examples.

METHODS

Three virtual patient populations undergoing vancomycin or tobramycin therapy were simulated with varying sample size and sampling scenarios. The three approaches used to handle BLQ data were to (1) discard them, (2) impute them as LLOQ/2, or (3) use a likelihood-based approach. EEs were performed with NONMEM and R.

RESULTS

Sample size did not have an important impact on the EE results for a given scenario. Increasing the number of samples per patient did not improve predictive performance for two out of the three evaluated models. Evaluating a model developed with rich sampling did not result in better performance than those developed with regular therapeutic drug monitoring. A likelihood-based method to handle BLQ samples impacted the outcomes of the EE with lower bias for predicted troughs.

CONCLUSIONS

This study suggests that a large sample size may not be necessary for an EE study, and models selected based on TDM may be more generalizable. The study highlights the need for guidelines for EE of population pharmacokinetic models for clinical use.

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

Predicting drug exposures using population pharmacokinetic models through Bayesian forecasting software can improve individual pharmacokinetic/pharmacodynamic target attainment. However, selecting the most adapted model to be used is challenging due to the lack of guidance on how to design and interpret external evaluation studies. The confusion around the choice of statistical metrics and acceptability criteria emphasises the need for further research to fill this methodological gap as there is an urgent need for the development of standards and guidelines for external evaluation studies. Herein we discuss the scientific challenges faced by pharmacometric researchers and opportunities for future research with a focus on antibiotics.

Development and Evaluation of a Height-Based Tobramycin Initial Dosing Nomogram for the Treatment of Adult Cystic Fibrosis Pulmonary Exacerbations

ABSTRACT

Tobramycin is widely used to treat pulmonary exacerbations of cystic fibrosis. Height has been previously found to be significantly more predictive of tobramycin pharmacokinetics than body weight. This study aimed to develop a height-based initial dosing nomogram and evaluate its performance in peak concentration (Cmax) precision relative to standard and fixed dosing. Monte Carlo simulations were performed to develop a nomogram representing the doses required to reach Cmax targets at different heights. Cmax data observed at 2 clinical centers [McGill University Health Centre (MUHC) and Institut universitaire de cardiologie et pneumologie de Québec (IUCPQ-UL)] were compared with population-predicted Cmax using the doses derived from the nomogram alongside a fixed dose. Height-based dosing resulted in significantly less variable-predicted Cmax values [coefficient of variation (CV) MUHC = 15.7% and IUCPQ-UL = 10.8%] than the Cmax values observed in clinical practice (CV MUHC = 30.0% and CV IUCPQ-UL = 26.9%) and predicted Cmax values obtained from a fixed dose (CV MUHC = 21.2% and CV IUCPQ-UL = 16.3%). An initial dosing nomogram was developed to help reduce pharmacokinetic variability in the observed Cmax. More precise dosing would allow for better clinical outcomes in adult patients with cystic fibrosis.

Consideration of height-based tobramycin dosing regimens for the treatment of adult cystic fibrosis pulmonary exacerbations

AIMS

Some population pharmacokinetic models have been developed using height to explain some of the interindividual variability in tobramycin pharmacokinetics in cystic fibrosis patients. However, their predictive performance when extrapolated to other clinical centres is unclear. Therefore, the aim of this study was to externally evaluate the predictability of tobramycin population pharmacokinetic models with an independent dataset and perform simulations using previously recommended height-based dosing regimens.

METHODS

A literature search was conducted through the PubMed database to identify relevant population pharmacokinetic models. Tobramycin plasma concentration data from April 2014 to November 2019 were retrospectively collected from the Institut universitaire de cardiologie et de pneumologie de Québec, Canada. External evaluations were performed using NONMEM® v7.5 and RStudio® v1.3.1073. Monte Carlo simulations were performed to evaluate the probability of target attainment of C_max /MIC ratios for several dosing regimens.

RESULTS

The validation dataset included 27 patients and 143 concentration samples. Three models were evaluated. Only the ones by Crass et al. and Alghanem et al. performed satisfactorily in terms of prediction-based diagnostics with MDPE values of -3.4% and 29.3% and MDAPE values of 19.0 and 29.5%, respectively. In simulation-based evaluations, both pcVPC and NPDE showed no evidence of model misspecification. Our simulations suggest that patients treated with a once-daily dose of 3.4 mg/cm should produce peak and trough levels consistent with current guidelines.

CONCLUSION

Our results show that the models by Crass et al. and Alghanem et al. are appropriate for simulation-based applications to aid individualized dosing in our population and that height-based dosing regimens could be considered in cystic fibrosis patients.

Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new in vitro and in vivo strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, in vivo model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

[Delayed delivery in multiple pregnancy: about a case and literature review]

Delayed delivery is designed to allow the remaining fetus(es) to develop after premature expulsion of the first twin in the second trimester of pregnancy. This decision is aimed to allow the remaining fetus(es) to reach full fetal growth. We here report a clinical case of delayed delivery in a patient with triple pregnancy in whom the time between the expulsion of the first twin and the birth of the third twin was 10 weeks. The purpose of this study was to highlight the benefit and indications for delayed delivery.