Population pharmacokinetic modeling and simulation of fremanezumab in healhy subjects and patients with migraine

Publication: Br J Clin Pharmacol
Division: Cognigen



Fremanezumab is a fully humanized IgG2 Δa/κ monoclonal antibody specific for calcitonin gene-related peptide developed and approved for the preventive treatment of migraine in adults. The population pharmacokinetics (PK) of fremanezumab were characterized in healthy subjects and patients with chronic migraine and episodic migraine, including the effects of intrinsic and extrinsic factors on PK variability.


Nonlinear mixed effects modelling was performed using NONMEM with data from 7 phase 1-3 clinical trials evaluating selected intravenous and subcutaneous dose regimens. The influence of covariates on fremanezumab PK was assessed and model evaluation was performed through visual predictive checks.


A 2-compartment model with first-order absorption and elimination described the PK data well. Typical values for fremanezumab central clearance (0.0902 L/d) and central distribution volume (1.88 L) for a 71-kg subject were consistent with previously reported values for IgG antibodies. Higher body weight was associated with increased central clearance and distribution volume. Effects of other covariates (age, albumin, renal function, sex, race, injection site, and acute, analgesic and preventive medication use for migraine) were not found to statistically significantly influence fremanezumab PK. There was no indication of reduced exposure in participants with positive anti-drug antibody status or with mild to moderate hepatic impairment. Absolute bioavailability was estimated at 0.658.


A comprehensive population PK model was developed for fremanezumab following intravenous and subcutaneous administration in healthy subjects and patients with chronic migraine or episodic migraine, which will be used to further evaluate exposure-response relationships for efficacy and safety endpoints.

By Jill B Fiedler-Kelly, Orit Cohen-Barak, Denise N Morris, Elizabeth Ludwig, Michele Rasamoelisolo, Honglue Shen, Micha Levi