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Toward a Quantitative Understanding of Aficamten Clinical Pharmacology: Population Pharmacokinetic Modeling
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Toward a Quantitative Understanding of Aficamten Clinical Pharmacology: Population Pharmacokinetic Modeling
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Journal Article
Toward a Quantitative Understanding of Aficamten Clinical Pharmacology: Population Pharmacokinetic Modeling
2025
Overview
Aficamten is a next‐in‐class, cardiac myosin inhibitor in development as a potential chronic oral treatment for patients with hypertrophic cardiomyopathy (HCM). A population pharmacokinetic (PK) model was developed using data from nine clinical studies to characterize aficamten PK and identify covariates that may alter aficamten exposure. Aficamten PK was best described by a 2‐compartment model with linear elimination and first‐order absorption following a time lag (Tlag). Population parameter estimates for a typical male participant with obstructive HCM (oHCM) and weighing 80 kg were: apparent clearance (CL/F), 2.62 L/h; apparent volume of the central compartment (Vc/F), 18.1 L; apparent intercompartmental clearance (Q/F), 57.6 L/h; and apparent volume of the peripheral compartment (Vp/F), 295 L. Estimated interindividual variability on CL/F and overall residual error (includes within‐subject variability) was low; the coefficient of variation was 28.7% and 20.3%, respectively. Body weight on volume and clearance, population and sex on CL/F and Vp/F were identified as statistically significant covariates. A male patient with a baseline body weight of 56 kg (5th percentile of the population) exhibited a 23% higher AUCtau compared with a male patient with a typical body weight of 80 kg. Female patients demonstrated a 14.7% higher AUCtau than male patients of the same body weight. Healthy participants had a 23% lower AUCtau compared with participants with oHCM. This population PK analysis demonstrated that aficamten has a linear and predictable PK profile, with a favorable half‐life and time‐to‐steady state, and low interindividual variability on CL/F and overall residual error (includes within‐subject variability).
