(M-117) Semi-mechanistic modeling to investigate differential dynamics of anti-citrullinated protein antibody (ACPA) IgG versus total IgG reduction following nipocalimab treatment
Principal Scientist J&J Innovative Medicine Philadelphia, Pennsylvania, United States
Disclosure(s):
Angelia F. Wang, PhD: No financial relationships to disclose
Objectives: Nipocalimab is a fully human, immunoglobulin G (IgG)-1 monoclonal antibody that blocks the IgG binding site on the neonatal Fc receptor (FcRn), preventing FcRn-mediated salvage of IgG and subsequently reducing circulating serum IgG. Nipocalimab’s therapeutic targets include anti-citrullinated protein antibodies (ACPA), a subset of IgG that are associated with pathophysiology in rheumatoid arthritis (RA).[1,2] In a phase 2a proof-of-concept study in RA patients (IRIS-RA; ClinicalTrials.gov Identifier: NCT04991753), nipocalimab-treated subjects experienced 50-60% sustained reduction of total IgG throughout the dosing period whereas ACPA exhibited a differential response: lesser maximal reduction and trend of tolerance and rebound.[3] The biological mechanisms underlying these responses are not well understood.
Methods: We extend a previous IgG PK-RO-PD mode[4] that was informed by FIH data[5] and a priori predicted IgG reduction in Phase 2a study IRIS-RA.[3] The extended model includes a mechanism of tolerance with feedback on ACPA synthesis rate and was simultaneously fit to individual-level total IgG and ACPA data (Monolix™, SimulationsPlus). Fitting results were directly compared with that of the original model (no tolerance mechanism) using quantitative goodness-of-fit metrics and visual assessment.
Results: Upon inclusion of tolerance mechanism, quantitative goodness-of-fit (OFV = 4342.18, AIC = 4368.18, BIC = 4393.79) improved, even after accounting for additional complexity from added parameters (base model: OFV 4359.46, AIC = 4381.46, BIC = 4403.13). Model-fitted profiles match well with individual trajectories of both total IgG and ACPA IgG, with simulations capturing observed tolerance and overshoot in ACPA. Moreover, model-estimated parameters imply either different endosomal uptake rate or different FcRn-mediated recycling efficiency of ACPA compared with total IgG, suggesting additional biological mechanisms that potentially alter FcRn-mediated ACPA recycling and response to FcRn-inhibiting therapies.
Conclusions: Model fits are consistent with the mechanistic hypothesis that compensatory autoantibody production or release can lead to tolerance and overshoot in ACPA IgG. There may be additional mechanisms that impact ACPA IgG recycling by FcRn, leading to a distinct pharmacodynamic profile of ACPA lowering compared with that of total IgG. Taken together, these modeling efforts contribute to the collective understanding of differential responses of disease-relevant autoantibodies to treatment.
Citations: [1] Rantapää-Dahlqvist, S. et al. Arthritis Rheum 10, 2741-9 (2003). [2] del Val Del Amo, N. et al. Clin Exp Rheumatol 24(3), 281-6 (2006). [3] Panchakshari, R. et al. ACR Convergence. Washington DC, United States (2023). [4] Sadik, J. et al ACoP. National Harbor, MD, United States (2023). [5] Ling, L.E. et al. Clin Pharmacol Ther 105, 1031-9 (2019).
