Development of a Pediatric Physiologically-Based Pharmacokinetic Model of Clindamycin Using Opportunistic Pharmacokinetic Data

Abstract

Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool used to characterize maturational changes in drug disposition to inform dosing across childhood; however, its use is limited in pediatric drug development. Access to pediatric pharmacokinetic data is a barrier to widespread application of this model, which impedes its development and optimization. To support the development of a pediatric PBPK model, we sought to leverage opportunistically-collected plasma concentrations of the commonly used antibiotic, clindamycin. The pediatric PBPK model was optimized following development of an adult PBPK model that adequately described literature data. We evaluated the predictability of the pediatric population PBPK model across 4 age groups, and found that 63–93% of the observed data where captured within the 90% prediction interval of the model. We then used the pediatric PBPK model to optimize intravenous clindamycin dosing for a future prospective validation trial. The optimal dosing proposed by this model are 9 mg/kg/dose in children ≤5 months of age, 12 mg/kg/dose in children >5 months to 6 years of age, and 10 mg/kg/dose in children 6-18 years of age, all administered every 8 hours. The simulated exposures achieved with the dosing regimen proposed were comparable to adult plasma and tissue exposures for treatment of community acquired methicillin resistant Staphylococcus aureus infections. Our model demonstrated the feasibility of using opportunistic pediatric data to develop pediatric PBPK models, extending the reach of this powerful modeling tool and potentially transforming the pediatric drug development field.

A Retrospective Evaluation of Allometry, PopulationPharmacokinetics,andPhysiologically‐Based Pharmacokineticsfor Pediatric Dosing Using Clearance as a Surrogate

“…Both popPK and PBPK models 9 can predict drug exposure across a wide range of ages and weights as well as consider differences in maturation and organ function. Pediatric PBPK models have been built for several small [10][11][12][13] and large molecules 14 and used for pediatric trial design and dose selection involving extrapolation from adult to pediatric or from one pediatric subpopulation to another.…”

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

“…Other recent examples of PBPK models include methotrexate and 6‐mercaptopurine, which, in combination with disease models, are being used to support clinical trial simulation for childhood leukemia . In addition, opportunistic PK data were recently used to develop a pediatric PBPK model of clindamycin by first creating an adult model from existing data and then scaling it to children . This model was able to predict concentrations of clindamycin in target tissues (eg, bone, skin) and confirm appropriate dosing.…”

The development of a population physiologically based pharmacokinetic model for mycophenolic mofetil and mycophenolic acid in humans using data from plasma, saliva, and kidney tissue

“…A combination of visual predictive checks (VPC) and numerical predictive checks were used to evaluate the predictive capability of the PBPK model. Visual predictive checks were done by overlaying a 90% predictive interval (PI) of Pop‐PBPK model‐simulated MPA, MPAG, and MMF levels in plasma, saliva, and kidney tissues at each time point over previously reported respective observed PK data (Hornik et al, ). Numerical predictive checks were achieved by calculating the percentage of observed data points ( ) representing the mean reported measured concentration that falls outside the 5th ( ) and 95th ( ) quantiles of the 90% PI of the Pop‐PBPK simulations ( or ) model using the following formula (Maharaj, Wu, Hornik, & Cohen‐Wolkowiez, ): …”