Population PK/PD Modeling and Simulation to Predict the Comparative Long-Term Efficacy of Olokizumab in Rheumatoid...

Background/Objectives: Olokizumab (OKZ) is a humanized monoclonal antibody targeting interleukin-6 (IL-6). OKZ demonstrated efficacy in subjects with active rheumatoid arthritis (RA) in randomized controlled trials versus adalimumab (ADLM) and placebo over 24 weeks, with sustained efficacy confirmed through 106 weeks in an open-label single-arm extension study (OLE). This analysis aimed to predict 1-year efficacy of OKZ 64 mg administered every two weeks (q2w) and every four weeks (q4w) compared with ADLM and placebo through virtual clinical trial simulations based on population pharmacokinetic/pharmacodynamic (PK/PD) models. Methods: Nonlinear mixed-effects models were developed using pooled data from phase III studies. Turnover models with a maximum inhibition I_max-type relationship between OKZ concentrations and clinical scores were applied. Simulated clinical trials were performed to estimate 52-week response rates, defined as proportions of patients achieving low disease activity (DAS28-CRP ≤ 3.2) and remission (CDAI ≤ 2.8). The reliability of the simulated extrapolations was validated against published data. Results: Log-transformed C-reactive protein (CRP) baseline levels and region were identified as significant covariates, influencing the dynamics of RA activity scores. OKZ and ADLM showed comparable predicted efficacy profiles, with overlapping 95% prediction intervals, and both were superior to placebo. Model predictions showed strong agreement with published long-term data for ADLM and placebo and closely reproduced the actual 1-year response profiles from the OKZ OLE. Conclusions: The developed PK/PD models showed good agreement with observed long-term efficacy outcomes for OKZ, ADLM, and placebo in MTX-IR RA patients. Both OKZ dosing regimens sustained low disease activity and remission rates comparable with those for ADLM over 52 weeks, supporting their use as effective treatment options.