Kirill Zhudenkov 1, Ivan Azarov 1, Yuri Kosinsky 1, Kirill Peskov 1, Sergey Grishin 1, Alina Egorova 1, Maria Lemak 1, Mikhail Samsonov 1
1 M&S Decisions FZ-LLC, Dubai, UAE (Dubai, UAE)
Objectives:
Olokizumab (OKZ) is a humanized monoclonal antibody developed as an antagonist of interleukin-6 and used for the treatment of rheumatoid arthritis (RA). OKZ PK was investigated in prior research in dedicated subject populations [1-3]. The objectives of this analysis were to (i) perform a comprehensive population PK evaluation of OKZ using pooled data from Phase I–III clinical studies in healthy volunteers and adults with rheumatoid arthritis (RA); (ii) evaluate the influence of intrinsic and extrinsic covariates on PK parameters and selected exposure metrics.
Methods:
Pooled PK data were compiled from eight clinical studies of OKZ encompassing Phase I–III trials (RA0001, RA0010, RA0074, RA0056, RA0083, CREDO 1, CREDO 2, CREDO 3)[4-11]. A total of 1115 subjects contributed PK observations, with dosing administered via both subcutaneous (s.c.) injection and intravenous (i.v.) infusion.
PK concentrations were analyzed using nonlinear mixed-effects modeling. Evaluation of models was conducted using objective function value (OFV), Akaike Information Criterion (AIC), shrinkage diagnostics, precision of parameter estimates (RSE <51%), and goodness-of-fit plots. Inter-individual variability (IIV) terms were assessed for all parameters; flexibility in covariance structures was explored as well. For handling concentrations below the limit of quantification, the M3 method was applied [12]. Covariate selection employed a stepwise forward inclusion (p <0.05) and backward elimination (p <0.01) procedure. Correlated or biologically implausible covariates were excluded prior to selection [13].
Graphical evaluation included visual inspection of diagnostic plots (DV vs PRED/IPRED, PWRES/IWRES), η-shrinkage, and prediction-corrected VPCs. Selected metrics were simulated over 200 replicate parameter sets to quantify covariate impacts at the 5th–95th percentile range of each covariate. Models were developed in Monolix 2020 R1 controlled in SimuRg environment allowing for automatic model building, covariate search and unified graphical and table diagnostics.
Results:
The final population PK model was selected from the list of more than 150 candidates. It represented a two-compartment model with first order absorption for s.c. administration, first order elimination, and a combined residual error. Inter-individual variability (IIV) was retained on CL and Vc, with a positive correlation between them (cor = 0.2). Typical population PK parameter estimates were: ka = 0.22 day⁻¹, CL = 0.18 L/day, Vc = 4.1 L, Q = 0.59 L/day, and Vp = 2.33 L. IIV estimates were ωCL = 0.42 and ωVc = 0.73, with η shrinkage < 51% for both parameters. Residual error parameters were a = 0.091 µg/mL (additive) and b = 0.23 (proportional). Bioavailability (F) differed between early phase studies and CREDO Phase III studies: Fnon_CREDO = 0.73 and FCREDO = 0.88, improving model performance. Parameter values were consistent with the outcomes of the prior research.
Five baseline covariates were included in the model: log-transformed serum albumin, high-density lipoprotein cholesterol and body weight (BWT) for CL; log-transformed alanine aminotransferase and BWT for Vc. BWT had the greatest effect on both model parameters and was the primary driver of exposure variability. Simulations showed that although covariates influenced exposure metrics (AUC, Cmax, Cmin after first dose and at steady state), they did not produce a clinically meaningful effect requiring dose adjustment within observed ranges. VPC diagnostics demonstrated adequate model performance.
Conclusions:
A robust two compartment population PK model for olokizumab was developed based on a pooled dataset from Phase I–III trials. The model adequately described the PK across i.v. and s.c. administration routes. Crucially, body weight was the dominant covariate, but its magnitude of effect did not justify dose adjustment. The analysis supports the appropriateness of the Q4W 64 mg s.c. regimen for adults with moderate to severe RA, consistent with comparable exposure and effectiveness relative to Q2W dosing. In further research, the developed model can be effectively used for long-term OKZ efficacy assessment and prediction.
References:
1. Tavlueva EV, Zernova EV, Kutepova MP, Kostina NE, Lesina VS, Mould DR, et al. Characteristics of olokizumab pharmacokinetics in patients with novel coronavirus infection COVID-19. Pharmacy & Pharmacology. 2022;10(5).
2. Kretsos K, Jullion A, Zamacona M, Harari O, Shaw S, Boulanger B, et al. Model-based optimal design and execution of the first-in-patient trial of the anti-IL-6 olokizumab. CPT Pharmacometrics Syst Pharmacol. 2014;3:e119.
3. Kretsos K, Golor G, Jullion A, Hickling M, McCabe S, Shaw S, et al. Safety and pharmacokinetics of olokizumab, an anti-IL-6 monoclonal antibody, administered to healthy male volunteers: A randomized phase I study. Clin Pharmacol Drug Dev. 2016;5:388–395.
4. ClinicalTrials.gov. A Study of RA0001 in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT01276119.
5. ClinicalTrials.gov. A Study of RA0010 in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT01009242.
6. ClinicalTrials.gov. A Study of RA0074 in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT01262794.
7. ClinicalTrials.gov. A Study of RA0056 in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT01296711.
8. ClinicalTrials.gov. Study in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT01463059.
9. ClinicalTrials.gov. CREDO 1: Olokizumab in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT02760368.
10. ClinicalTrials.gov. CREDO Study of Olokizumab in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT02760407.
11. ClinicalTrials.gov. CREDO Study of Olokizumab in Subjects With Rheumatoid Arthritis. Bethesda (MD): National Library of Medicine; Identifier NCT02760433.
12. Ette EI, Williams PJ. Population pharmacokinetics I: background, concepts, and models. Ann Pharmacother. 2004;38:1702–1706.
13. U.S. Food and Drug Administration. Population Pharmacokinetics: Guidance for Industry. Silver Spring (MD): FDA; 2022.
Reference: PAGE 34 (2026) Abstr 12131 [www.page-meeting.org/?abstract=12131]
Poster: Drug/Disease Modelling - Endocrine