(T1030-05-29) Population Pharmacokinetic Modeling of Rezpegaldesleukin after Subcutaneous Dosing to Account for Variability Across Multiple Patient Populations with Autoimmune Diseases

Purpose: Rezpegaldesleukin (REZPEG) is an IL-2 receptor (IL2R) pathway agonist designed to stimulate the expansion and function of regulatory T cells (Tregs). REZPEG utilizes the approved recombinant human IL-2 (rhIL-2) aldesleukin sequence with stable, covalently attached polyethylene glycol (PEG) moieties which extend the half-life and confer a selectivity for Treg stimulation over conventional T cells (Tcons) compared with rhIL-2 [Silverberg et al]. As compared to unPEGylated rhIL-2, REZPEG has reduced binding affinity for IL-2Rβ, resulting in a different binding selectivity for cells expressing IL-2Rβ versus IL-2Rα. This design property renders Tregs with high-affinity (IL-2Rαβγ) receptors more sensitive than Tcons to activation by REZPEG [Fanton et al]. Tregs hold a pivotal role in orchestrating immune homeostasis through their ability to modulate the activity of T helper cell subsets, but are impaired in many autoimmune and chronic inflammatory diseases including systemic lupus erythematosus (SLE), ulcerative colitis, psoriasis (PsO) and atopic dermatitis (AD) [Silverberg et all. Nektar Therapeutics is developing REZPEG as a potential treatment for inflammatory diseases by therapeutic restoration of the Treg compartment. and is currently being evaluated in Phase 2b clinical trials for moderate-to-severe AD (NCT06136741) and severe alopecia areata (NCT06340360). The objective of this work is to: 1) characterize the clinical PK of REZPEG after subcutaneous administration and identify sources of variability; 2) quantify the relationships between relevant covariates and REZPEG exposure across multiple therapeutic indications; and 3) use the model to perform exposure simulations in patient subgroups of special interest.

Methods: Individual-subject level PK and clinical data were obtained from five Phase 1 and Phase 2 studies in healthy subjects and patients with autoimmune and inflammatory diseases including SLE, AD, or ulcerative colitis. A population PK model was developed by evaluating various structural models, including one-compartment and two-compartment models. Covariate analysis was performed using a forward addition and backward elimination procedure. A prediction-corrected visual predictive check (pcVPC) was conducted to evaluate the performance of the population PK model. The quantification of parameter uncertainty in the current population model was assessed using nonparametric bootstrap analysis. Covariates evaluated were disease condition, formulation, subcutaneous injection site locations and injection volume, age, sex, race/ethnicity, body weight, and renal and hepatic function biomarkers. For the current population model, simulations were performed to quantify the impact of the selected covariates on REZPEG exposures. Population PK analysis was performed using the nonlinear mixed effects modeling methodology as implemented in the NONMEM® program version 7.4.4. All simulations were performed with parameter uncertainty (1000 sets of typical values with a sampling of parameters from the NONMEM variance-covariance matrix of estimates). Data post-processing was performed using R (version 3.6.1 or higher).

Results: The PK of REZPEG was adequately described by a one-compartment model with first-order absorption and elimination process. Population estimates of CL/F and Vc/F in an adult of 75 kg were 0.42 L/day and 6.15 L, respectively. Inter-individual variability estimates on CL/F and Vc/F were 33.3% and 32.4%, respectively. Body weight was a significant predictor of both apparent clearance and volume of distribution in the model and contributed significantly to the PK variability of REZPEG in the simulation. Weight-based dosing is expected to reduce the variability in drug exposure across the patients. Creatinine clearance (CRCL) was a predictor of apparent clearance CL/F. The lower CRCL limits of 60, 30 and 15 mL/min were then used in the simulation to explore the effects of mild, moderate and severe renal impairment, respectively. The model estimated an increase of 13%, 28% and 46% for C_max, and an increase of 15%, 34% and 55% for AUC, in patients with mild, moderate and severe impairment, relative to patients with normal renal function (CRCL=114 mL/min), respectively. These results supported the plan to conduct a dedicated renal impairment study with REZPEG in future development. No effects of disease condition, formulation, subcutaneous injection site locations or injection volume, age, gender, race/ethnicity or the biomarkers of hepatic function were found to impact the PK of REZPEG.

Conclusion: The current population PK model adequately described the PK of REZPEG following subcutaneous administration in multiple patient populations. The model used covariates consistently across indications and accounts for PK differences between populations. The integrated population PK model supports the weight-based dose levels and regimens currently being evaluated in the phase 2b studies of REZPEG in atopic dermatitis and alopecia areata.

References: Fanton C et al, Selective expansion of regulatory T cells by NKTR-358 in healthy volunteers and patients with systemic lupus erythematosus, J Transl Autoimmun 2022 Mar 28:5:100152. doi: 10.1016/j.jtauto.2022.100152.
Silverberg JI et al, The regulatory T cell-selective interleukin-2 receptor agonist rezpegaldesleukin in the treatment of inflammatory skin diseases: two randomized, double-blind, placebocontrolled phase 1b trials. Nat Commun. 2024 Oct 25;15(1):9230. doi: 10.1038/s41467-024-53384-1.