(T-084) A COMBINED EX VIVO AND PHYSIOLOGICALLY-BASED PHARMACOKINETIC APPROACH TO INCORPORATE DRUG-DRUG INTERACTIONS FOR DOSING DURING CONTINUOUS RENAL REPLACEMENT THERAPY

Abdullah Hamadeh, PhD – Research Associate, University of Waterloo; Porter Hunt, PhD – Research Associate, University of Utah; Danielle Green, MD – Assistant Professor, University of Utah; Carina Imburgia, BS – Lab Specialist, University of Utah; Aviva Whelan, MD – Fellow, University of Utah; Rachel Hudson, PhD – Postdoc Fellow, University of Utah; Andrew Chevalier, MD – Fellow, University of Utah; Andrea Edginton, PhD – Professor, University of Waterloo; Kevin Watt, MD, PhD – Professor, University of Utah

Objective: Continuous renal replacement therapy (CRRT) circuits can interact with drugs and alter pharmacokinetics (PK) in children.¹ Studies investigating drug-circuit interactions are usually performed with individually administered drugs and therefore do not account for drug-drug interactions (DDIs). DDIs can increase toxicity, lead to therapeutic failure, and have been associated with increased hospital stay.² In order to provide appropriate drug dosing during CRRT, DDIs, patient factors, and drug-circuit interactions with the potential to impact PK must be taken into account. However, the combined role of drug-circuit interactions and critical illness in DDIs is currently unknown. To address this, we developed a pediatric CRRT physiologically-based pharmacokinetic (PBPK) model to describe the DDI between fluconazole, a moderate CYP3A4 inhibitor, and midazolam, a CYP3A4 substrate.

Methods: Individual 15-compartment population PBPK models for midazolam and fluconazole were built in PK-Sim® utilizing previously published models.^3,4 These models were optimized, combined, and the fluconazole CYP3A4 inhibitory constant was then added to create a final DDI model.⁵ A CRRT compartment was created in Mobi® and connected to the DDI model through the venous blood compartment. The CRRT compartment was parameterized using data from ex vivo experiments where drugs were administered to isolated CRRT circuits to determine drug-circuit interactions. Albumin, hematocrit, and glomerular filtration rate were adjusted to reflect changes that occur during critical illness. The CRRT-PBPK DDI model was validated using observed data from an ongoing opportunistic PK study of drugs in children on CRRT. Model bias and precision were determined using AFE, AAFE and percent of observed data within the 90% prediction interval. Simulations were run for five age-stratified virtual populations over a range of midazolam infusion doses. Midazolam doses were considered optimal if concentrations for 90% of virtual individuals were within the therapeutic range of 200 – 1000 ng/mL.

Results: The fluconazole-midazolam CRRT DDI model met acceptance criteria with all patient samples within the 90% prediction interval and AFE of 0.97 and AAFE of 1.62. Continuous midazolam infusions of 0.005 mg/kg/h for neonates and 0.025 mg/kg/h for all other ages were determined as optimal.

Conclusions: The final fluconazole-midazolam CRRT-PBPK DDI model accurately simulated drug concentrations in a critically ill child supported with CRRT. Model-informed dosing of midazolam was lower than current dosing recommendations, suggesting that dosing may need to be decreased in children supported with CRRT when fluconazole is administered concurrently. This approach can be adapted to other drugs to determine the combined effect of DDIs and drug clearance by the circuit, providing a feasible method to guide dosing in this complex population.

Citations: Citations:
[1] Veltri et al. Paediatr Drugs. 2004;6(1):45‐65.
[2] Lima et al. Front Pharmacol 2020;11:555407.
[3] Hanke et al. CPT Pharmacometrics Syst Pharmacol. 2018;7(10):647-59.
[4] Watt et al. CPT Pharmacometrics Syst Pharmacol. 2018;7(10):629-37.
[5] Gibbs et al. Drug Metab Dispos. 1999;27(2):180-7.