Kosuke Doki1, Keisuke Kuga2, Kazutaka Aonuma2, Masaki Ieda2, Masato Homma3. 1. Department of Pharmaceutical Sciences, Faculty of Medicine, University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki, 305-8575, Japan. k-doki@md.tsukuba.ac.jp. 2. Department of Cardiology, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan. 3. Department of Pharmaceutical Sciences, Faculty of Medicine, University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki, 305-8575, Japan.
Abstract
PURPOSE: Higher drug concentrations in complex clinical scenarios in which multiple factors such as drug-drug interactions (DDIs) and comorbidities are simultaneously present are not necessarily rationalized in prospective clinical studies. Physiologically based pharmacokinetic (PBPK) modeling and simulation of the anti-arrhythmic drug flecainide, as an example, were utilized to quantitatively rationalize the higher flecainide concentration in a complex clinical case involving end-stage renal disease (ESRD), cirrhosis, and the co-administration of mexiletine, a CYP1A2 inhibitor. METHODS: The developed flecainide PBPK model was used to evaluate the DDI effect (as measured by AUC ratio before and after inhibition) of mexiletine and the combined disease effects of ESRD and cirrhosis on flecainide exposure. RESULTS: The predicted DDI effect of mexiletine was negligible or weak in anuric hemodialysis with cirrhosis population (mean [5th/95th percentiles], 1.23 [0.97-1.67]), although it was negligible in healthy volunteers (1.03 [1.02-1.05]). The predicted flecainide concentrations after multiple flecainide doses (50 mg BID) in the anuric hemodialysis with cirrhosis population were comparable with the observed value (3602 ng/mL), which fell between the predicted concentrations in the absence and presence of mexiletine (3043 [718-8499] and 5914 [880-20,624] ng/mL, respectively). CONCLUSIONS: The PBPK simulation proposed a likely explanation that the observed higher flecainide concentration could be attributed to the combined effects of ESRD, cirrhosis, and a potential DDI with mexiletine. This approach provides quantitative insight into theoretically conceivable extremes in drug exposure occurring in complex clinical situations even if uncommon.
PURPOSE: Higher drug concentrations in complex clinical scenarios in which multiple factors such as drug-drug interactions (DDIs) and comorbidities are simultaneously present are not necessarily rationalized in prospective clinical studies. Physiologically based pharmacokinetic (PBPK) modeling and simulation of the anti-arrhythmic drug flecainide, as an example, were utilized to quantitatively rationalize the higher flecainide concentration in a complex clinical case involving end-stage renal disease (ESRD), cirrhosis, and the co-administration of mexiletine, a CYP1A2 inhibitor. METHODS: The developed flecainide PBPK model was used to evaluate the DDI effect (as measured by AUC ratio before and after inhibition) of mexiletine and the combined disease effects of ESRD and cirrhosis on flecainide exposure. RESULTS: The predicted DDI effect of mexiletine was negligible or weak in anuric hemodialysis with cirrhosis population (mean [5th/95th percentiles], 1.23 [0.97-1.67]), although it was negligible in healthy volunteers (1.03 [1.02-1.05]). The predicted flecainide concentrations after multiple flecainide doses (50 mg BID) in the anuric hemodialysis with cirrhosis population were comparable with the observed value (3602 ng/mL), which fell between the predicted concentrations in the absence and presence of mexiletine (3043 [718-8499] and 5914 [880-20,624] ng/mL, respectively). CONCLUSIONS: The PBPK simulation proposed a likely explanation that the observed higher flecainide concentration could be attributed to the combined effects of ESRD, cirrhosis, and a potential DDI with mexiletine. This approach provides quantitative insight into theoretically conceivable extremes in drug exposure occurring in complex clinical situations even if uncommon.