Abstract

BackgroundFinerenone (BAY 94-8862) is a potent non-steroidal, selective mineralocorticoid receptor antagonist being developed for the treatment of patients with type 2 diabetes and chronic kidney disease.MethodsWe present the population pharmacokinetics and pharmacodynamics (PD) analysis for efficacy and safety markers based on data from two clinical phase IIb studies: ARTS-DN (NCT01874431) and ARTS-DN Japan (NCT01968668).ResultsThe pharmacokinetics of finerenone were adequately characterized, with estimated glomerular filtration rate (eGFR) and body weight as influencing covariates. The area under the plasma concentration–time curve in Japanese patients did not differ from that in the global population, and the investigated pharmacokinetics were dose- and time-linear. In addition, the pharmacokinetic model provided robust individual exposure estimates to study exposure–response. The concentration–effect relationship over time for the efficacy marker urinary albumin:creatinine ratio (UACR) was well-characterized by a maximum effect model indicating saturation at high exposures. For the safety markers, a log-linear model and a power model were identified for serum potassium concentration and eGFR, respectively, indicating attenuation of effect gains at high exposures. There was no apparent ethnic effect on the investigated pharmacokinetic–pharmacodynamic relationships. The model-predicted times to reach the full (99%) steady-state drug effect on UACR, serum potassium, and eGFR were 138, 20, and 85 days, respectively, while the pharmacokinetic half-life was 2–3 h and steady state was achieved after 2 days, indicating timescale separation.ConclusionOur dose–exposure–response modeling and simulation indicates effects were largely saturated at finerenone 20 mg and doses of both 10 and 20 mg once daily appear safe and efficacious at reducing albuminuria.Electronic supplementary materialThe online version of this article (10.1007/s40262-019-00820-x) contains supplementary material, which is available to authorized users.

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