Background and objective: Because of the pathophysiological changes associated with critical illness and the use of extracorporeal life support (ECLS) such as continuous renal replacement therapy (CRRT) and extracorporeal membrane oxygenation (ECMO), the pharmacokinetics of drugs are often altered. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for anakinra in children that accounts for the physiological changes associated with critical illness and ECLS technology to guide appropriate pharmacotherapy.
Methods: A PBPK model for anakinra was first developed in healthy individuals prior to extrapolating to critically ill children receiving ECLS. To account for the impact of anakinra clearance by the dialysis circuit, a CRRT compartment was added to the pediatric PBPK model and parameterized using data from a previously published ex-vivo study. Additionally, an ECMO compartment was added to the whole-body structure to create the final anakinra ECLS-PBPK model. The final model structure was validated by comparing predicted concentrations with observed patient data. Due to limited information in guiding anakinra dosing in this population, in-silico dose simulations were conducted to provide baseline recommendations.
Results: By accounting for changes in physiology and the addition of ECLS compartments, the final ECLS-PBPK model predicted the observed plasma concentrations in an adolescent receiving subcutaneous anakinra. Furthermore, dosing simulations suggest that anakinra exposure in adolescents receiving ECLS is similar to that in healthy counterparts.
Conclusion: The anakinra ECLS-PBPK model developed in this study is the first to predict plasma concentrations in a population receiving simultaneous CRRT and ECMO. Dosing simulations provided may be used to inform anakinra use in critically ill children and guide future clinical trial planning.
https://pubmed.ncbi.nlm.nih.gov/39331235/ Samuel Dubinsky, Abdullah Hamadeh, Carina Imburgia, Autumn McKnite, J Porter Hunt, Kristy Wong, Cassandra Rice, Joseph Rower, Kevin Watt, Andrea Edginton Clin Pharmacokinet . 2024 Sep 27. doi: 10.1007/s40262-024-01424-w
Abstract
Background and objective: Because of the pathophysiological changes associated with critical illness and the use of extracorporeal life support (ECLS) such as continuous renal replacement therapy (CRRT) and extracorporeal membrane oxygenation (ECMO), the pharmacokinetics of drugs are often altered. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for anakinra in children that accounts for the physiological changes associated with critical illness and ECLS technology to guide appropriate pharmacotherapy.
Methods: A PBPK model for anakinra was first developed in healthy individuals prior to extrapolating to critically ill children receiving ECLS. To account for the impact of anakinra clearance by the dialysis circuit, a CRRT compartment was added to the pediatric PBPK model and parameterized using data from a previously published ex-vivo study. Additionally, an ECMO compartment was added to the whole-body structure to create the final anakinra ECLS-PBPK model. The final model structure was validated by comparing predicted concentrations with observed patient data. Due to limited information in guiding anakinra dosing in this population, in-silico dose simulations were conducted to provide baseline recommendations.
Results: By accounting for changes in physiology and the addition of ECLS compartments, the final ECLS-PBPK model predicted the observed plasma concentrations in an adolescent receiving subcutaneous anakinra. Furthermore, dosing simulations suggest that anakinra exposure in adolescents receiving ECLS is similar to that in healthy counterparts.
Conclusion: The anakinra ECLS-PBPK model developed in this study is the first to predict plasma concentrations in a population receiving simultaneous CRRT and ECMO. Dosing simulations provided may be used to inform anakinra use in critically ill children and guide future clinical trial planning.