Population pharmacokinetic modelling and simulation of tafamidis in healthy subjects and patients with transthyretin amyloidosis. Issue 9 (1st March 2021) - Huh, Yeamin; Riley, Steve; Harnisch, Lutz; Nicholas, Timothy
Abstract : Aims: Since the first approval for transthyretin amyloid polyneuropathy patients, new formulations and different strength of tafamidis have been developed and tested in a different population (transthyretin amyloid cardiomyopathy). The objective of this analysis was to develop a unified population pharmacokinetic (PK) model of tafamidis, which can describe the PK of various different formulations in healthy subjects as well as patients with TTR amyloidosis, and to understand effects of intrinsic and extrinsic factors on the PK variability. Methods: Pooled data from 23 clinical studies (17 Phase 1 and 6 Phase 2/3 studies) were used for the analysis. The plasma concentration–time data were analysed using a nonlinear mixed effects modelling methodology. Covariate analysis was performed using a stepwise covariate model building procedure. Results: The final model was a 2‐compartment model with first‐order absorption and elimination coupled with an absorption lag time for nonsolution formations. Body weight, food and tafamidis formulations were incorporated as structural covariates on PK parameters. Covariate analysis further identified age ≥65 years (14.5% decrease) and moderate hepatic impairment effects (57.6% increase) on apparent clearance and transthyretin amyloid polyneuropathy effect (17.3% decrease) on F. However, model‐based clinical trial simulation results indicated that tafamidis steady‐state exposure changes were not clinically meaningful under the tested conditions. Conclusions: The unified population PK model of tafamidis was developed based on 23 studies. Subsequent clinical trial simulations indicated that no significant changes in tafamidis exposure necessitating a dose modification are expected due to either extrinsic or intrinsic factors. The model was used to support labelling statements for dose recommendations in special populations.