European journal of clinical pharmacology · 2026
Population pharmacokinetic modeling of amisulpride drug interactions and a transporter binding analysis.
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Gan Tongying, Liu Chang, Wu Bixuan
Аннотация
PURPOSE: The combination of amisulpride and metformin is common in schizophrenia, but their potential drug-drug interaction has been largely overlooked, despite both drugs being prototypical substrates for renal elimination and potentially subject to transport by OCT2 and MATE1.
METHODS: In this study, we employed population pharmacokinetic modeling to quantify the impact of renal function and metformin on amisulpride pharmacokinetics, and complemented it with molecular docking to predict binding modes on key renal transporters, thereby exploring potential transporters mediating the interaction.
RESULTS: We identified CLcr, assessed by the Cockcroft-Gault formula, as the dominant covariate. A 10% decrease in CLcr was associated with a 3.8% decrease in CL/F, while metformin significantly reduced clearance by 23.2%, leading to an at least 41% increase in amisulpride steady‑state trough concentration. Molecular docking generated a structural hypothesis that amisulpride and metformin may share overlapping binding sites on OCT2 and MATE1.
CONCLUSION: This study provides the first clinical indication of a potential drug-drug interaction between amisulpride and metformin. We provide model‑informed dosing references stratified by CLcr, along with recommendations for dose reduction and heightened vigilance for interaction-related adverse effects in patients receiving combination therapy. Molecular docking offers a structural hypothesis regarding binding at OCT2 and MATE1 to support further mechanistic investigation.
METHODS: In this study, we employed population pharmacokinetic modeling to quantify the impact of renal function and metformin on amisulpride pharmacokinetics, and complemented it with molecular docking to predict binding modes on key renal transporters, thereby exploring potential transporters mediating the interaction.
RESULTS: We identified CLcr, assessed by the Cockcroft-Gault formula, as the dominant covariate. A 10% decrease in CLcr was associated with a 3.8% decrease in CL/F, while metformin significantly reduced clearance by 23.2%, leading to an at least 41% increase in amisulpride steady‑state trough concentration. Molecular docking generated a structural hypothesis that amisulpride and metformin may share overlapping binding sites on OCT2 and MATE1.
CONCLUSION: This study provides the first clinical indication of a potential drug-drug interaction between amisulpride and metformin. We provide model‑informed dosing references stratified by CLcr, along with recommendations for dose reduction and heightened vigilance for interaction-related adverse effects in patients receiving combination therapy. Molecular docking offers a structural hypothesis regarding binding at OCT2 and MATE1 to support further mechanistic investigation.