학술논문

Physiologically‐based pharmacokinetic model of sparsentan to evaluate drug–drug interaction potential
Document Type
Report
Source
CPT: Pharmacometrics & Systems Pharmacology. February 2024, Vol. 13 Issue 2, p317, 13 p.
Subject
Complications and side effects
Analysis
Models
Drug interactions -- Models -- Analysis
Efavirenz -- Complications and side effects
Simulation -- Analysis -- Models
Itraconazole -- Complications and side effects
Angiotensin II -- Complications and side effects
Permeability -- Analysis -- Models
Immunoglobulin A -- Analysis -- Models
Enzymes -- Models -- Analysis
Kidney diseases -- Complications and side effects
Simulation methods -- Analysis -- Models
Language
English
Abstract
Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Sparsentan is a novel dual endothelin‐angiotensin receptor antagonist for the treatment of proteinuria in patients with IgA nephropathy. In vitro [...]
: Sparsentan is a dual endothelin/angiotensin II receptor antagonist indicated to reduce proteinuria in patients with primary IgA nephropathy at high risk of disease progression. In vitro data indicate that sparsentan is likely to inhibit or induce various CYP enzymes at therapeutic concentrations. Sparsentan as a victim and perpetrator of CYP3A4 mediated drug–drug interactions (DDIs) has been assessed clinically. A mechanistic, bottom‐up, physiologically‐based pharmacokinetic (PK) model for sparsentan was developed based on in vitro data of drug solubility, formulation dissolution and particle size, drug permeability, inhibition and induction of metabolic enzymes, and P‐glycoprotein (P‐gp) driven efflux. The model was verified using clinical PK data from healthy adult volunteers administered single and multiple doses in the fasted and fed states for a wide range of sparsentan doses. The model was also verified by simulation of clinically observed DDIs. The verified model was then used to test various DDI simulations of sparsentan as a perpetrator and victim of CYP3A4 using an expanded set of inducers and inhibitors with varying potency. Additional perpetrator and victim DDI simulations were performed using probes for CYP2C9 and CYP2C19. Simulations were conducted to predict the effect of complete inhibition of P‐gp inhibition on sparsentan absorption and clearance. The predictive simulations indicated that exposure of sparsentan could increase greater than two‐fold if co‐administered with a strong CYP3A4 inhibitor, such as itraconazole. Other potential DDI interactions as victim or perpetrator were all within two‐fold of control. The effect of complete P‐gp inhibition on sparsentan PK was negligible.