Simultaneous Assessment of Hepatic Transport and Metabolism Pathways with a Single Probe Using Individualized PBPK Modeling of 14CO2 Production Rate Data

Application of Individualized PBPK Modeling of Rate Data to Evaluate the Effect of Hemodialysis on Nonrenal Clearance Pathways

The aim of this study was to apply individualized, physiologically based pharmacokinetic modeling of ¹⁴ CO₂ production rates (iPBPK-R) measured by the erythromycin breath test to characterize the effect of hemodialysis on the function of nonrenal clearance pathways in patients with end-stage renal disease. Twelve patients previously received ¹⁴ C-erythromycin intravenously pre- and post-hemodialysis. Serial breath samples were collected after each dose over 2 hours. Eight PBPK parameters were co-estimated across periods, whereas activity of cytochrome P450 (CYP) 3A4 clearance was independently estimated for each period. Inhibition coefficients for organic anion transporting polypeptide (OATP), P-glycoprotein, and multidrug resistance-associated protein 2 activities were also estimated. Nonrenal clearance parameter estimates were explored regarding sex differences and correlations with uremic toxins and were used in hierarchical cluster analysis (HCA). Relationships between the function of nonrenal clearance pathways and uremic toxin concentrations were explored. Mean CYP 3A4 clearance increased by 2.2% post-hemodialysis. Uptake transporter activity was highly intervariable across hemodialysis. Females had 22% and 30% higher median CYP3A4 activity than males pre- and post-hemodialysis, respectively. Exploratory HCA indicated that using both CYP3A4 and OATP activity parameters at pre- and post-hemodialysis best identifies heterogeneous patients. This is the first study to use the iPBPK-R approach to simultaneously estimate multiple in vivo nonrenal elimination pathways in individual patients with kidney disease and to assess the effect of hemodialysis.

Dose Optimization in Kidney Disease: Opportunities for PBPK Modeling and Simulation

Kidney disease affects pharmacokinetic (PK) profiles of not only renally cleared drugs but also nonrenally cleared drugs. The impact of kidney disease on drug disposition has not been fully elucidated, but describing the extent of such impact is essential for conducting dose optimization in kidney disease. Accurate evaluation of kidney function has been a clinical interest for dose optimization, and more scientists pay attention and conduct research for clarifying the role of drug transporters, metabolic enzymes, and their interplay in drug disposition as kidney disease progresses. Physiologically based pharmacokinetic (PBPK) modeling and simulation can provide valuable insights for dose optimization in kidney disease. It is a powerful tool to integrate discrete knowledge from preclinical and clinical research and mechanistically investigate system- and drug-dependent factors that may contribute to the changes in PK profiles. PBPK-based prediction of drug exposures may be used a priori to adjust dosing regimens and thereby minimize the likelihood of drug-related toxicity. With real-time clinical studies, parameter estimation may be performed with PBPK approaches that can facilitate identification of sources of interindividual variability. PBPK modeling may also facilitate biomarker research that aids dose optimization in kidney disease. U.S. Food and Drug Administration guidances related to conduction of PK studies in kidney impairment and PBPK documentation provide the foundation for facilitating model-based dose-finding research in kidney disease.