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European Journal of Drug Metabolism and Pharmacokinetics
Erschienen in:

05.05.2024 | Original Research Article

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

verfasst von: Mehdi El Hassani, Uwe Liebchen, Amélie Marsot

Erschienen in: European Journal of Drug Metabolism and Pharmacokinetics | Ausgabe 4/2024

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Abstract

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.
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Literatur
1.
Marsot A. Pharmacokinetic variability in pediatrics and intensive care: toward a personalized dosing approach. J Pharm Pharm Sci. 2018;21(1):354–62.PubMedCrossRef
2.
Powell JR, Cook J, Wang Y, Peck R, Weiner D. Drug dosing recommendations for all patients: a roadmap for change. Clin Pharmacol Ther. 2021;109(1):65–72.PubMedCrossRef
3.
Mould DR, Upton RN. Basic concepts in population modeling, simulation, and model-based drug development-part 2: introduction to pharmacokinetic modeling methods. CPT Pharmacomet Syst Pharmacol. 2013;2(4): e38.CrossRef
4.
Kantasiripitak W, Van Daele R, Gijsen M, Ferrante M, Spriet I, Dreesen E. Software tools for model-informed precision dosing: how well do they satisfy the needs? Front Pharmacol. 2020;11:620.PubMedPubMedCentralCrossRef
5.
Aljutayli A, Thirion DJG, Bonnefois G, Nekka F. Pharmacokinetic equations versus Bayesian guided vancomycin monitoring: pharmacokinetic model and model-informed precision dosing trial simulations. Clin Transl Sci. 2022;15(4):942–53.PubMedPubMedCentralCrossRef
6.
Gu JQ, Guo YP, Jiao Z, Ding JJ, Li GF. How to handle delayed or missed doses: a population pharmacokinetic perspective. Eur J Drug Metab Pharmacokinet. 2020;45(2):163–72.PubMedCrossRef
7.
Patanwala AE, Spremo D, Jeon M, Thoma Y, Alffenaa JWC, Stocker S. Discrepancies between Bayesian vancomycin models can affect clinical decisions in the critically ill. Crit Care Res Pract. 2022;2022:7011376.PubMedPubMedCentral
8.
El Hassani M, Marsot A. External evaluation of population pharmacokinetic models for precision dosing: current state and knowledge gaps. Clin Pharmacokinet. 2023;62(4):533–40.PubMedCrossRef
9.
Cheng Y, Wang C-Y, Li Z-R, Pan Y, Liu M-B, Jiao Z. Can population pharmacokinetics of antibiotics be extrapolated? Implications of external evaluations. Clin Pharmacokinet. 2021;60(1):53–68.PubMedCrossRef
10.
Kim YK, Lee JH, Jang HJ, Zang DY, Lee DH. Predicting antibiotic effect of vancomycin using pharmacokinetic/pharmacodynamic modeling and simulation: dense sampling versus sparse sampling. Antibiotics (Basel). 2022;11(6):743.PubMedCrossRef
11.
Aarons L, Ogungbenro K. Optimal design of pharmacokinetic studies. Basic Clin Pharmacol Toxicol. 2010;106(3):250–5.PubMedCrossRef
12.
Beal SL. Sample size determination for confidence intervals on the population mean and on the difference between two population means. Biometrics. 1989;45(3):969–77.PubMedCrossRef
13.
14.
Ogungbenro K, Aarons L. How many subjects are necessary for population pharmacokinetic experiments? Confidence interval approach. Eur J Clin Pharmacol. 2008;64(7):705–13.PubMedCrossRef
15.
Chan Kwong AHXP, Calvier EAM, Fabre D, Gattacceca F, Khier S. Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine. J Pharmacokinet Pharmacodyn. 2020;47(5):431–46.PubMedPubMedCentralCrossRef
16.
Keizer RJ, Jansen RS, Rosing H, Thijssen B, Beijnen JH, Schellens JH, et al. Incorporation of concentration data below the limit of quantification in population pharmacokinetic analyses. Pharmacol Res Perspect. 2015;3(2): e00131.PubMedPubMedCentralCrossRef
17.
Huang S, Ding Q, Yang N, Sun Z, Cheng Q, Liu W, et al. External evaluation of published population pharmacokinetic models of posaconazole. Front Pharmacol. 2022;13:1005348.PubMedPubMedCentralCrossRef
18.
Konecki C, Feliu C, Cazaubon Y, Giusti D, Tonye-Libyh M, Brixi H, et al. External evaluation of population pharmacokinetic models and bayes-based dosing of infliximab. Pharmaceutics. 2021;13(8):1191.PubMedPubMedCentralCrossRef
19.
Beal SL. Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn. 2001;28(5):481–504.PubMedCrossRef
20.
Santacana E, Rodríguez-Alonso L, Padullés A, Guardiola J, Rodríguez-Moranta F, Serra K, et al. External evaluation of population pharmacokinetic models of infliximab in patients with inflammatory bowel disease. Ther Drug Monit. 2018;40(1):120–9.PubMedCrossRef
21.
Hanafin PO, Nation RL, Scheetz MH, Zavascki AP, Sandri AM, Kwa AL, et al. Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients. CPT Pharmacomet Syst Pharmacol. 2021;10(12):1525–37.CrossRef
22.
Yang N, Wang J, Xie Y, Ding J, Wu C, Liu J, et al. External evaluation of population pharmacokinetic models to inform precision dosing of meropenem in critically ill patients. Front Pharmacol. 2022;13: 838205.PubMedPubMedCentralCrossRef
23.
Nguyen TH, Comets E, Mentré F. Extension of NPDE for evaluation of nonlinear mixed effect models in presence of data below the quantification limit with applications to HIV dynamic model. J Pharmacokinet Pharmacodyn. 2012;39(5):499–518.PubMedCrossRef
24.
Irby DJ, Ibrahim ME, Dauki AM, Badawi MA, Illamola SM, Chen M, et al. Approaches to handling missing or “problematic” pharmacology data: pharmacokinetics. CPT Pharmacomet Syst Pharmacol. 2021;10(4):291–308.CrossRef
25.
Ahn JE, Karlsson MO, Dunne A, Ludden TM. Likelihood based approaches to handling data below the quantification limit using NONMEM VI. J Pharmacokinet Pharmacodyn. 2008;35(4):401–21.PubMedCrossRef
26.
27.
Mehrotra N, Tang L, Phelps SJ, Meibohm B. Evaluation of vancomycin dosing regimens in preterm and term neonates using Monte Carlo simulations. Pharmacotherapy. 2012;32(5):408–19.PubMedCrossRef
28.
Dong M, Rodriguez AV, Blankenship CA, McPhail G, Vinks AA, Hunter LL. Pharmacokinetic modelling to predict risk of ototoxicity with intravenous tobramycin treatment in cystic fibrosis. J Antimicrob Chemother. 2021;76(11):2923–31.PubMedPubMedCentralCrossRef
29.
El Hassani M, Simard C, Pilote S, Cloutier I, Soufsaf S, Marsot A. Consideration of height-based tobramycin dosing regimens for the treatment of adult cystic fibrosis pulmonary exacerbations. Br J Clin Pharmacol. 2021;88(5):2246–55.PubMedCrossRef
30.
Smit C, Wasmann RE, Wiezer MJ, van Dongen HPA, Mouton JW, Brüggemann RJM, et al. Tobramycin clearance is best described by renal function estimates in obese and non-obese individuals: results of a prospective rich sampling pharmacokinetic study. Pharm Res. 2019;36(8):112.PubMedPubMedCentralCrossRef
31.
32.
Alghanem S, Paterson I, Touw DJ, Thomson AH. Influence of multiple courses of therapy on aminoglycoside clearance in adult patients with cystic fibrosis. J Antimicrob Chemother. 2013;68(6):1338–47.PubMedCrossRef
33.
Teutonico D, Musuamba F, Maas HJ, Facius A, Yang S, Danhof M, et al. Generating virtual patients by multivariate and discrete re-sampling techniques. Pharm Res. 2015;32(10):3228–37.PubMedPubMedCentralCrossRef
34.
Owen JS, Fiedler-Kelly J (2014) Introduction to population pharmacokinetic/pharmacodynamic analysis with nonlinear mixed effects models. John Wiley & Sons, Hoboken, NJ
35.
Germovsek E, Osborne L, Gunaratnam F, Lounis SA, Busquets FB, Standing JF, et al. 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. 2019;74(4):1003–11.PubMedCrossRef
36.
Vancocin (vancomycin hydrochloride) [package insert]. Baudette, MN: ANI Pharmaceuticals; 2017
37.
Aljutayli A, El-Haffaf I, Marsot A, Nekka F. An update on population pharmacokinetic analyses of vancomycin, part II: in pediatric patients. Clin Pharmacokinet. 2022;61(1):47–70.PubMedCrossRef
38.
Smit C, Wasmann RE, Goulooze SC, Hazebroek EJ, Van Dongen EPA, Burgers DMT, et al. A prospective clinical study characterizing the influence of morbid obesity on the pharmacokinetics of gentamicin: towards individualized dosing in obese patients. Clin Pharmacokinet. 2019;58(10):1333–43.PubMedPubMedCentralCrossRef
39.
Crass RL, Pai MP. Optimizing estimated glomerular filtration rate to support adult to pediatric pharmacokinetic bridging studies in patients with cystic fibrosis. Clin Pharmacokinet. 2019;58(10):1323–32.PubMedPubMedCentralCrossRef
40.
Frymoyer A, Hersh AL, El-Komy MH, Gaskari S, Su F, Drover DR, et al. Association between vancomycin trough concentration and area under the concentration-time curve in neonates. Antimicrob Agents Chemother. 2014;58(11):6454–61.PubMedPubMedCentralCrossRef
41.
Bauer RJ. NONMEM tutorial part II: estimation methods and advanced examples. CPT Pharmacomet Syst Pharmacol. 2019;8(8):538–56.CrossRef
42.
Maitre PO, Ausems ME, Vozeh S, Stanski DR. Evaluating the accuracy of using population pharmacokinetic data to predict plasma concentrations of alfentanil. Anesthesiology. 1988;68(1):59–67.PubMedCrossRef
43.
Hara M, Masui K, Eleveld DJ, Struys MMRF, Uchida O. Predictive performance of eleven pharmacokinetic models for propofol infusion in children for long-duration anaesthesia. Br J Anaesth. 2017;118(3):415–23.PubMedCrossRef
44.
Miyabe-Nishiwaki T, Masui K, Kaneko A, Nishiwaki K, Nishio T, Kanazawa H. Evaluation of the predictive performance of a pharmacokinetic model for propofol in Japanese macaques (Macaca fuscata fuscata). J Vet Pharmacol Ther. 2013;36(2):169–73.PubMedCrossRef
45.
Comets E, Brendel K, Mentré F. Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: the npde add-on package for R. Comput Methods Programs Biomed. 2008;90(2):154–66.PubMedCrossRef
46.
Hughes JH, Tong DMH, Faldasz JD, Frymoyer A, Keizer RJ. Evaluation of neonatal and paediatric vancomycin pharmacokinetic models and the impact of maturation and serum creatinine covariates in a large multicentre data set. Clin Pharmacokinet. 2023;62(1):67–76.PubMedCrossRef
47.
Heus A, Uster DW, Grootaert V, Vermeulen N, Somers A, In’t Veld DH, et al. Model-informed precision dosing of vancomycin via continuous infusion: a clinical fit-for-purpose evaluation of published PK models. Int J Antimicrob Agents. 2022;59(5): 106579.PubMedCrossRef
48.
Colin PJ, Allegaert K, Thomson AH, Touw DJ, Dolton M, de Hoog M, et al. Vancomycin pharmacokinetics throughout life: results from a pooled population analysis and evaluation of current dosing recommendations. Clin Pharmacokinet. 2019;58(6):767–80.PubMedCrossRef
49.
Cunio CB, Uster DW, Carland JE, Buscher H, Liu Z, Brett J et al. Towards precision dosing of vancomycin in critically ill patients: an evaluation of the predictive performance of pharmacometric models in ICU patients. Clin Microbiol Infect. 2021;27(5):783.e7–783.e14
50.
Nguyen TH, Mouksassi MS, Holford N, Al-Huniti N, Freedman I, Hooker AC, et al. Model evaluation of continuous data pharmacometric models: metrics and graphics. CPT Pharmacomet Syst Pharmacol. 2017;6(2):87–109.CrossRef
51.
Bensken WP, Pieracci FM, Ho VP. Basic introduction to statistics in medicine, part 1: describing data. Surg Infect (Larchmt). 2021;22(6):590–6.PubMedCrossRef
52.
Hsu LF. A survey of population pharmacokinetic reports submitted to the USFDA: an analysis of common issues in NDA and BLA from 2012 to 2021. Clin Pharmacokinet. 2022;61(12):1697–703.PubMedCrossRef
53.
Savic RM, Karlsson MO. Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutions. AAPS J. 2009;11(3):558–69.PubMedPubMedCentralCrossRef
Metadaten
Titel
Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?
verfasst von
Mehdi El Hassani
Uwe Liebchen
Amélie Marsot
Publikationsdatum
05.05.2024
Verlag
Springer International Publishing
Erschienen in
European Journal of Drug Metabolism and Pharmacokinetics / Ausgabe 4/2024
Print ISSN: 0378-7966
Elektronische ISSN: 2107-0180
DOI
https://doi.org/10.1007/s13318-024-00897-1

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