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.
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.
Authors: Rosalba Alonso Campero; Roberto Bernardo Escudero; Doris Del Cisne Valle Alvarez; Mario González de la Parra; Salvador Namur Montalvo; Victoria Burke Fraga; Rodolfo Silva Hernandez; Alberto De Lago Acosta Journal: Clin Ther Date: 2007-02 Impact factor: 3.393
Authors: Sandy J Close; Christopher R McBurney; Cory G Garvin; David C Chen; Steven J Martin Journal: Pharmacotherapy Date: 2002-08 Impact factor: 4.705
Authors: Jacqueline G Gerhart; Fernando O Carreño; Andrea N Edginton; Jaydeep Sinha; Eliana M Perrin; Karan R Kumar; Aruna Rikhi; Christoph P Hornik; Vincent Harris; Samit Ganguly; Michael Cohen-Wolkowiez; Daniel Gonzalez Journal: Clin Pharmacokinet Date: 2021-10-07 Impact factor: 5.577
Authors: Yi Shuan S Wu; Michael Cohen-Wolkowiez; Christoph P Hornik; Jacqueline G Gerhart; Julie Autmizguine; Marjan Cobbaert; Daniel Gonzalez Journal: Antimicrob Agents Chemother Date: 2021-06-17 Impact factor: 5.938
Authors: Samit Ganguly; Andrea N Edginton; Jacqueline G Gerhart; Michael Cohen-Wolkowiez; Rachel G Greenberg; Daniel Gonzalez Journal: Clin Pharmacokinet Date: 2021-06-22 Impact factor: 5.577