Pragmatic physiologically-based pharmacokinetic modeling to support clinical implementation of optimized gentamicin dosing in term neonates and infants: proof-of-concept

Introduction: Modeling and simulation can support dosing recommendations for clinical practice, but a simple framework is missing. In this proof-of-concept study, we aimed to develop neonatal and infant gentamicin dosing guidelines, supported by a pragmatic physiologically-based pharmacokinetic (PBPK) modeling approach and a decision framework for implementation.Methods: An already existing PBPK model was verified with data of 87 adults, 485 children and 912 neonates, based on visual predictive checks and predicted-to-observed pharmacokinetic (PK) parameter ratios. After acceptance of the model, dosages now recommended by the Dutch Pediatric Formulary (DPF) were simulated, along with several alternative dosing scenarios, aiming for recommended peak (i.e., 8-12 mg/L for neonates and 15-20 mg/L for infants) and trough (i.e., <1 mg/L) levels. We then used a decision framework to weigh benefits and risks for implementation.Results: The PBPK model adequately described gentamicin PK. Simulations of current DPF dosages showed that the dosing interval for term neonates up to 6 weeks of age should be extended to 36-48 h to reach trough levels <1 mg/L. For infants, a 7.5 mg/kg/24 h dose will reach adequate peak levels. The benefits of these dose adaptations outweigh remaining uncertainties which can be minimized by routine drug monitoring.Conclusion: We used a PBPK model to show that current DPF dosages for gentamicin in term neonates and infants needed to be optimized. In the context of potential uncertainties, the risk-benefit analysis proved positive; the model-informed dose is ready for clinical implementation.

Automated summary

This study developed dosing guidelines for neonatal and infant gentamicin using a physiologically-based pharmacokinetic (PBPK) modeling approach. The simulations showed that the current dosages need to be optimized to achieve recommended drug levels. These findings have important implications for clinical practice.