Abstract
Objectives: The objective of this study was to establish physiologically based pharmacokinetic (PBPK) models of tramadol and its active metabolite O-desmethyltramadol (M1) and to explore the influence of CYP2D6 gene polymorphism on the pharmacokinetics of tramadol and M1. Furthermore, we used PBPK modeling to prospectively predict the extent of drug-drug interactions (DDIs) in the presence of genetic polymorphisms when tramadol was co-administered with the CYP2D6 inhibitors duloxetine and paroxetine.
Methods: Plasma concentrations of tramadol and M1 were used to adjust the turnover frequency (Kcat ) of CYP2D6 for phenotype populations with different CYP2D6 genotypes. PBPK models were developed to capture the pharmacokinetics between CYP2D6 extensive metabolizers (EMs), intermediate metabolizers (IMs), poor metabolizers (PMs), and ultra-rapid metabolizers (UMs). The validated models were then used to support dose adjustment in different CYP2D6 phenotypes and to predict the extent of CYP2D6-mediated DDIs when tramadol was co-administered with paroxetine or duloxetine.
Results: The PBPK models we built accurately describe tramadol and M1 exposure in the population with different CYP2D6 phenotypes. In our prediction, the area under the concentration-time curve (AUCinf-tDlast ) of M1 is 70% lower in PMs than in EMs, 27% lower in IMs, and 15% higher in UMs. Based on the models we built, we suggest that the oral dose of tramadol should be 50% higher for IMs and 25% lower for UMs to achieve an approximately equivalent plasma exposure of M1 as in EMs. When tramadol was co-administered with paroxetine or duloxetine, the magnitude of the inhibitor-substrate interaction was lowest in EMs (0.45), secondary in IMs (0.39), and highest in PMs (0.18) in terms of M1.
Conclusion: The current example uses the PBPK model to guide dose adjustment of tramadol and to predict the effect of CYP2D6 genetic polymorphisms on DDIs for rational clinical use of tramadol in the future.
Keywords: CYP2D6; PBPK; dosing regimen; drug interactions; genetic polymorphism; tramadol.
AndreDlm
commented
1 year ago
https://pubmed.ncbi.nlm.nih.gov/33316842/ Pharmacotherapy. 2020 Dec 14. Miao Xu, Liang Zheng, Jin Zeng, Wenwen Xu, Xuehua Jiang, Ling Wang
Abstract Objectives: The objective of this study was to establish physiologically based pharmacokinetic (PBPK) models of tramadol and its active metabolite O-desmethyltramadol (M1) and to explore the influence of CYP2D6 gene polymorphism on the pharmacokinetics of tramadol and M1. Furthermore, we used PBPK modeling to prospectively predict the extent of drug-drug interactions (DDIs) in the presence of genetic polymorphisms when tramadol was co-administered with the CYP2D6 inhibitors duloxetine and paroxetine.
Methods: Plasma concentrations of tramadol and M1 were used to adjust the turnover frequency (Kcat ) of CYP2D6 for phenotype populations with different CYP2D6 genotypes. PBPK models were developed to capture the pharmacokinetics between CYP2D6 extensive metabolizers (EMs), intermediate metabolizers (IMs), poor metabolizers (PMs), and ultra-rapid metabolizers (UMs). The validated models were then used to support dose adjustment in different CYP2D6 phenotypes and to predict the extent of CYP2D6-mediated DDIs when tramadol was co-administered with paroxetine or duloxetine.
Results: The PBPK models we built accurately describe tramadol and M1 exposure in the population with different CYP2D6 phenotypes. In our prediction, the area under the concentration-time curve (AUCinf-tDlast ) of M1 is 70% lower in PMs than in EMs, 27% lower in IMs, and 15% higher in UMs. Based on the models we built, we suggest that the oral dose of tramadol should be 50% higher for IMs and 25% lower for UMs to achieve an approximately equivalent plasma exposure of M1 as in EMs. When tramadol was co-administered with paroxetine or duloxetine, the magnitude of the inhibitor-substrate interaction was lowest in EMs (0.45), secondary in IMs (0.39), and highest in PMs (0.18) in terms of M1.
Conclusion: The current example uses the PBPK model to guide dose adjustment of tramadol and to predict the effect of CYP2D6 genetic polymorphisms on DDIs for rational clinical use of tramadol in the future.
Keywords: CYP2D6; PBPK; dosing regimen; drug interactions; genetic polymorphism; tramadol.