Sparsentan for Focal Segmental Glomerulosclerosis in the DUET Open-Label Extension: Long-term Efficacy and Safety
Kidney Medicine – 2024
Population Pharmacokinetic Analysis of Sparsentan in Healthy Volunteers and Patients with Focal Segmental Glomerulosclerosis
Journal article
Published on June 1, 2023
Contributors:
Wada R, Kleijn H-J, Zhang L et al.
Wada R, Kleijn H-J, Zhang L et al.
DOI:
10.1002/psp4.12996
10.1002/psp4.12996
Summary
Population pharmacokinetic (PK) analyses of sparsentan suggest dose adjustments for patients on concomitant moderate or strong CYP3A4 inhibitors1
Background
Focal segmental glomerulosclerosis (FSGS) is a rare, progressive kidney condition and the most common glomerular cause of end-stage kidney disease (ESKD) in children and adults in the US.2-4
Sparsentan is a novel, single-molecule Dual Endothelin Angiotensin Receptor Antagonist (DEARA) developed for the treatment of IgA nephropathy and in development for FSGS.1,5* Sparsentan is primarily metabolized by cytochrome P450, family 3, subfamily A (CYP3A) and has been shown to be a competitive inhibitor and inducer of CYP3A in vitro.1
Sparsentan has been investigated in Phase 1 healthy volunteer studies as well as in patients with primary or genetic FSGS in the Phase 2 DUET and Phase 3 DUPLEX studies.1,6,7
Aim
The objective of this population pharmacokinetic (PK) analysis was to characterize the PK of sparsentan in healthy volunteers and patients with FSGS.1 Additionally, the analysis evaluated the impact of FSGS disease characteristics and co-medications as covariates on sparsentan PK.1
Approach
A population PK analysis was conducted using data from nine clinical trials involving 446 participants, including1:
- 236 healthy subjects
- 16 patients with hepatic impairment
- 194 patients with primary/genetic FSGS
Population PK analysis was performed using non-linear mixed effects modeling.1
A total of 20 covariates were tested based on their clinical relevance to at least one population PK parameter, including1:
- Standard demographics
- Laboratory-based liver function markers
- Creatinine clearance
- Food status
- Formulation (capsule and tablet)
- Population (patients with FSGS and healthy volunteers)
- Concomitant medications (acid-reducing agent, CYP3A inducer and inhibitor, and P-glycoprotein)
Findings
Sparsentan PK model structure and performance
Sparsentan PKs were characterized by a two-compartment model with first-order absorption and lag time, dose-dependent bioavailability, and first-order elimination from the central compartment.1
The terminal half-life is 9.6 hours. To account for dose-dependent bioavailability, a non-linear relationship was used for doses above 200 mg.1
Covariate effects on exposure
Moderate and strong CYP3A4 inhibitors increased the area under the concentration-time curve (AUC) of sparsentan by 31% and 191%, respectively, suggesting that dose adjustments may be warranted.1
Creatinine clearance and alkaline phosphatase modestly affected sparsentan clearance (<20%).1 Sex and race affected volume or clearance but were not clinically significant.1 No dose adjustment was needed for food intake, age, sex, race, or mild/moderate renal impairment.1
Sparsentan exposures were generally comparable across various FSGS subpopulations.1
Key takeaway
This population PK model of sparsentan suggests that dose adjustments may be warranted for patients taking moderate and strong CYP3A4 inhibitors concomitantly, but no adjustments are needed across the range of other concomitant medications, patient characteristics, and disease characteristics.1
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Implications of Complete Proteinuria Remission at Any Time in Focal Segmental Glomerulosclerosis: Sparsentan DUET Trial
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Footnotes
*As of November 2025.
This study was funded by Travere Therapeutics, Inc. Please see the publication for the full list of disclosures.
AUC, area under the concentration-time curve; CYP3A, cytochrome P450, family 3, subfamily A; DEARA, Dual Endothelin Angiotensin Receptor Antagonist; ESKD, end-stage kidney disease; FSGS, focal segmental glomerulosclerosis; PK, pharmacokinetic; US, United States.
- Wada R, Kleijn HJ, Zhang L, Chen SC. CPT Pharmacometrics Syst Pharmacol. 2023;12:1080-1092.
- Fogo AB. Nat Rev Nephrol. 2015;11:76-87.
- Korbet SM. J Am Soc Nephrol. 2012;23:1769-1776.
- United States Renal Data System 2021 Annual data report: Epidemiologyof Kidney Disease in the United States, Volume 2, Chapter 8. 2021. Accessed 18 September 2025. https://www.usrds.org/media/1627/v2_c08_pedia tric_16.pdf
- Komers R, Plotkin H. Am J Physiol Regul Integr Comp Physiol. 2016;310:R877-R884.
- Komers R et al. Kidney Intl Reports. 2020;5:494-502.
- Trachtman H et al. J Am Soc Nephrol. 2018;29:2745-2754.
MA-SP-25-0093 | November 2025