Population pharmacokinetics and exposure-response modeling and simulation for evolocumab in healthy volunteers and patients with hypercholesterolemia

Abstract

Evolocumab, a novel human monoclonal antibody, inhibits proprotein convertase subtilisin/kexin type 9, a protein that targets low-density lipoprotein-cholesterol (LDL-C) receptors for the treatment of hyperlipidemia. The primary objective of this analysis was to characterize the population pharmacokinetics (popPK) and exposure-response relationship of evolocumab to assess if dose adjustment is needed across differing patient populations. Data were pooled for 5474 patients in 11 clinical studies who received evolocumab doses of 7-420 mg at various frequencies, either intravenously or subcutaneously. Evolocumab area under concentration-time curve from 8 to 12 weeks (AUCwk8-12) was simulated for individuals using the popPK model and was used to predict the LDL-C response in relation to AUCwk8-12. Evolocumab was eliminated through nonspecific (linear) and target-mediated (nonlinear) clearance. PopPK parameters and associated variabilities of evolocumab were similar to those of other monoclonal antibodies. The exposure-response model predicted a maximal 66% reduction in LDL-C from baseline to the mean of weeks 10 and 12 for doses of evolocumab 140 mg subcutaneously every 2 weeks or 420 mg subcutaneously once monthly. After inclusion of statistically significant covariates in an uncertainty-based simulation, LDL-C reduction from baseline at the mean of weeks 10 and 12 was predicted to be within 74% to 126% of the reference patient for all simulated patient groups. Evolocumab had nonlinear pharmacokinetics. The range of responses based on intrinsic and extrinsic factors was not predicted to be sufficiently different from the reference patient to warrant evolocumab dose adjustment.

Keywords: Evolocumab; Exposure–response; Hypercholesterolemia; Monoclonal antibody; PCSK9; Population pharmacokinetics.

Conflict of interest statement

Conflicts of interest

M. Kuchimanchi, S.M. Wasserman, and S. Doshi are employees of and stockholders in Amgen Inc. R. Somaratne and J.P. Gibbs are identified as inventors on at least one pending patent application owned by Amgen Inc. relating to evolocumab. S.M. Wasserman appears on a number of pending patents owned by Amgen Inc. relating to evolocumab and PCSK9 inhibition. J.P. Gibbs, A. Grover, and M.G. Emery were employees of and stockholders in Amgen at the time this work was completed. J.P. Gibbs is currently employed by AbbVie, Inc. A. Grover is currently employed by BioMarin Pharmaceutical Inc. M.G. Emery is currently employed by Seattle Genetics. R. Somaratne is a stockholder of Amgen, was employed by Amgen at the time this work was completed, and is currently employed by NGM Biopharmaceuticals.

Ethical approval

All studies were conducted in accordance with principles for human experimentation as defined in the Declaration of Helsinki and International Conference on Harmonization Good Clinical Practice guidelines, and approved by the relevant institutional review boards.

Informed consent

Informed consent was obtained from each study participant after they were told of the potential risks and benefits as well as the investigational nature of the study.

Figures

Fig. 1

Evolocumab pharmacokinetic and exposure–response model. a Pharmacokinetic model; ka absorption rate constant; kel elimination rate constant; km concentration of half-maximal nonlinear clearance; Vmax nonlinear clearance capacity. b Exposure–response model; Eff LDL-C lowering effect; Emax theoretical maximum evolocumab response for the average of weeks 10 and 12; EC50 ((µg/mL) * day) AUCwk8–12 (Q2W) to achieve half-maximal response; REG regimen effect on EC50 with an indicator variable, i, with values of 0 or 1 was used indicate Q2W or QM regimens

Fig. 2

Observed and model-predicted serum evolocumab concentrations. Solid line: line of unity; dashed line: locally weighted scatterplot smoothing (LOWESS); PRED population predicted concentration; IPRED individual predicted concentration

Fig. 3

PK and PD individual model fits for representative patients. Points: observations; solid line: population prediction (PRED); dashed line: individual prediction (IPRED)

Fig. 4

Time-course of model-predicted and observed serum evolocumab concentrations after doses of 140 mg SC Q2W (6 doses) and 420 mg SC QM (3 doses). Simulations were performed (number of trials = 100) on the entire dataset. Dots: observed evolocumab serum concentrations. Panels a, b, and c: blue shaded area: 90% prediction interval of simulated evolocumab serum concentration–time profile, and red line is predicted median, whereas black line is observed median. Panel d: The solid red lines represent the 95th (upper red line), 50th (middle red line), and 5th (lower red line) percentiles of the observed prediction-corrected serum concentration. The observed prediction-corrected plasma concentrations are represented by grey circles. The black lines (upper: 95th, middle: 50th, and lower: 5th) represent the simulation-based prediction, and the surrounding semitransparent blue field represents a simulation-based 90% prediction interval for the corresponding simulation-based prediction intervals. Q2W once every 2 weeks; QM once monthly; SC subcutaneous

Fig. 5

AUC week 8–12 versus body weight for all patients by sex

Fig. 6

Observed data and 90% prediction interval for week 10 and 12 mean calculated LDL-C for phase 2 studies by weeks 8–12 evolocumab-predicted AUC. Prediction of the mean week 10 and 12 calculated LDL-C concentration, in percentage change from baseline, 50th (solid line) and 5th and 95th (dashed lines) percentiles. Simulations were performed for n = 2000 patients. Points: observed individual mean of weeks 10 and 12 LDL-C measurements. Vertical line: mean observed AUCwk8–12 in phase 2. %CFB percentage change from baseline; AMG 145 evolocumab; AUC area under the concentration–time curve; LDL-C low-density lipoprotein-cholesterol; Q2W once every 2 weeks; QM once monthly

Fig. 7

Forest plots of covariate effects with 95% CI for evolocumab AUCwk8–12 for 140 mg SC Q2W and 420 mg SC QM. The statin covariate represents patients only taking a statin and no other concomitant medication. The statin + Ezet covariate includes all patients on Ezet, regardless of concomitant medications. For patients in the pharmacokinetics model, 93% of those taking Ezet were also taking a statin; thus, the Ezet covariate most generally represents a combination (statin + Ezet) therapy covariate. AUC area under the time-concentration curve; CI confidence interval; Ezet ezetimibe; PCSK9 BL proprotein convertase subtilisin/kexin type 9 baseline (low, 4.8 nM [355 ng/mL]; high, 8.1 nM [599 ng/mL]); Q2W once every 2 weeks; QM once monthly; SC subcutaneous

Fig. 8

Forest plots of covariate effects with 95% CI for evolocumab week 10 and 12 mean calculated LDL-C lowering for 140 mg SC Q2W and 420 mg SC QM. CI confidence interval; Ezet ezetimibe; HeFH heterozygous familial hypercholesterolemia; LDL-C low-density lipoprotein-cholesterol; PCSK9 BL proprotein convertase subtilisin/kexin type 9 baseline (low, 4.8 nM [355 ng/mL]; high, 8.1 nM [599 ng/mL]); Q2W once every 2 weeks; QM once monthly; SC subcutaneous