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. 2019 Jul;58(7):887-898.
doi: 10.1007/s40262-018-00733-1.

Physiologically Based Pharmacokinetic Modeling for Trimethoprim and Sulfamethoxazole in Children

Elizabeth J Thompson  1 , Huali Wu  2 , Anil Maharaj  2 , Andrea N Edginton  2 , Stephen J Balevic  1   2 , Marjan Cobbaert  2 , Anthony P Cunningham  2 , Christoph P Hornik  1   2 , Michael Cohen-Wolkowiez  3   4
Affiliations

Physiologically Based Pharmacokinetic Modeling for Trimethoprim and Sulfamethoxazole in Children

Elizabeth J Thompson et al. Clin Pharmacokinet. 2019 Jul.

Abstract

Objective: The aims of this study were to (1) determine whether opportunistically collected data can be used to develop physiologically based pharmacokinetic (PBPK) models in pediatric patients; and (2) characterize age-related maturational changes in drug disposition for the renally eliminated and hepatically metabolized antibiotic trimethoprim (TMP)-sulfamethoxazole (SMX).

Methods: We developed separate population PBPK models for TMP and SMX in children after oral administration of the combined TMP-SMX product and used sparse and opportunistically collected plasma concentration samples to validate our pediatric model. We evaluated predictability of the pediatric PBPK model based on the number of observed pediatric data out of the 90% prediction interval. We performed dosing simulations to target organ and tissue (skin) concentrations greater than the methicillin-resistant Staphylococcus aureus (MRSA) minimum inhibitory concentration (TMP 2 mg/L; SMX 9.5 mg/L) for at least 50% of the dosing interval.

Results: We found 67-87% and 71-91% of the observed data for TMP and SMX, respectively, were captured within the 90% prediction interval across five age groups, suggesting adequate fit of our model. Our model-rederived optimal dosing of TMP at the target tissue was in the range of recommended dosing for TMP-SMX in children in all age groups by current guidelines for the treatment of MRSA.

Conclusion: We successfully developed a pediatric PBPK model of the combination antibiotic TMP-SMX using sparse and opportunistic pediatric pharmacokinetic samples. This novel and efficient approach has the potential to expand the use of PBPK modeling in pediatric drug development.

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Conflict of interest statement

Conflicts of interest:

S.J.B. receives salary and research support from the National Institutes of Health (5R01-HD076676–04, HH N275201000003I, the Rheumatology Research Foundation’s Scientist Development Award, and the Thrasher Research Fund.

A.N.E. receives support for research from the National Institutes of Health (1R01-HD076676–01A1 [PI: Cohen-Wolkowiez]).

None of the other authors have anything to disclose.

Figures

Fig 1
Fig 1
Model-building workflow for pediatric PBPK model
Fig 2
Fig 2
Mean observed (dots) and simulated (lines) plasma concentrations and fraction of the drug excreted unchanged in urine for TMP (A) and SMX (B) after a single oral dose of 160 mg TMP and 800 mg SMX in healthy adults. Error bars refer to range of concentration in observed patients.
Fig 3
Fig 3
Observed (dots) and simulated (lines) plasma concentration-time profiles of TMP (A) and SMX (B) following a single oral dose of 160 mg TMP and 800 mg SMX in healthy adults. Solid lines represent geometric mean of the simulated data. The shaded area represents geometric mean ± geometric SD for the simulated data. Symbols and error bars represents mean and SD for the observed data, respectively.
Fig 4
Fig 4
Simulated total drug exposure (AUCss) of TMP (A) and SMX (B) with age-based TMP-SMX dosage regimens. Dotted lines demonstrate target and toxicity thresholds.
See this image and copyright information in PMC

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