Application of a physiologically based pharmacokinetic model for the prediction of mirabegron plasma concentrations in a population with severe renal impairment

Abstract

We previously verified a physiologically based pharmacokinetic (PBPK) model for mirabegron in healthy subjects using the Simcyp Simulator by incorporating data on the inhibitory effect on cytochrome P450 (CYP) 2D6 and a multi‐elimination pathway mediated by CYP3A4, uridine 5′‐diphosphate‐glucuronosyltransferase (UGT) 2B7 and butyrylcholinesterase (BChE). The aim of this study was to use this PBPK model to assess the magnitude of drug–drug interactions (DDIs) in an elderly population with severe renal impairment (sRI), which has not been evaluated in clinical trials. We first determined the system parameters, and meta‐analyses of literature data suggested that the abundance of UGT2B7 and the BChE activity in an elderly population with sRI was almost equivalent to and 20% lower than that in healthy young subjects, respectively. Other parameters, such as the CYP3A4 abundance, for an sRI population were used according to those built into the Simcyp Simulator. Second, we confirmed that the PBPK model reproduced the plasma concentration–time profile for mirabegron in an sRI population (simulated area under the plasma concentration–time curve (AUC) was within 1.5‐times that of the observed value). Finally, we applied the PBPK model to simulate DDIs in an sRI population. The PBPK model predicted that the AUC for mirabegron with itraconazole (a CYP3A4 inhibitor) was 4.12‐times that in healthy elderly subjects administered mirabegron alone, and predicted that the proportional change in AUC for desipramine (a CYP2D6 substrate) with mirabegron was greater than that in healthy subjects. In conclusion, the PBPK model was verified for the purpose of DDI assessment in an elderly population with sRI.

Improved Pharmacokinetic Feasibilities of Mirabegron-1,2-Ethanedisulfonic Acid, Mirabegron-1,5-Naphthalenedisulfonic Acid, and Mirabegron-L-Pyroglutamic Acid as Co-Amorphous Dispersions in Rats and Mice

“…After the absorption phase, various factors, such as distribution, metabolism, and excretion, can contribute to the low F of MBR. MBR is extensively metabolized via cytochrome P450 (CYP) enzymes, including CYP2D6 and CYP3A4, as well as uridine 5′-diphospho-glucuronosyltransferases (UGTs), such as UGT2B7, which further contributes to the first-pass effect and low F of MBR [ 7 , 46 , 51 ]. MBR and its metabolites formed via hepatic or intestinal metabolism are eliminated through kidneys and bile [ 46 , 52 ].…”

Understanding Statin‐Roxadustat Drug–Drug‐Disease Interaction Using Physiologically‐Based Pharmacokinetic Modeling

“…This may be explained by a similar reason of the reduced activities of the most critical interaction pathways of hepatic BCRP and/or OATP1B1/3 mediated transport in these patients compared with that in HVs. Recent studies have addressed the potential difference in DDI magnitude between healthy and renally impaired when the DDIs were mediated by renal active transport and hepatic metabolism pathways 1,41–43 . In some cases, higher DDI risk was predicted in renal impairment whereas in others the DDI risk was predicted to be similar to healthy persons.…”

“…Recent studies have addressed the potential difference in DDI magnitude between healthy and renally impaired when the DDIs were mediated by renal active transport and hepatic metabolism pathways. 1,[41][42][43] In some cases, higher DDI risk was predicted in renal impairment whereas in others the DDI risk was predicted to be similar to healthy persons. These results highlight the importance of understanding the disease factors implicated in the complex DDDI, as the difference between healthy and disease stage will be dependent on the pathway(s) involved in each case.…”