Evaluation of Itacitinib Impact on TNFα Levels Following Immune Effector Cell (IEC) Therapy Using PKPD Modeling and Simulation Approaches
Authors: Ivanova Olga , Pratta Michael , Azarov Ivan , Zhudenkov Kirill , Kosinsky Yuri , Peskov Kirill , Chen Xuejun , Sheng Jennifer 
Published: December 2024

Introduction:
Itacitinib (INCB039110), a novel, selective oral Janus kinase 1 (JAK1) inhibitor, was evaluated as monotherapy in a phase 2 study (Study INCB039110-211: NCT04071366) for the prevention of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome in response to chimeric antigen receptor T-cell (CAR-T) infusion. Systemic cytokines, including tumor necrosis factor alpha (TNFα) have been proposed as surrogate pharmacodynamic (PD) biomarkers for the inflammatory response correlating with CRS. Pharmacokinetic (PK) and PD modeling was applied to describe the inhibition of itacitinib on TNFα levels following CAR-T infusion.
Objectives:
The primary aim of the PKPD modeling analysis was to develop a mechanistic model to evaluate itacitinib anti-inflammatory action on systemic levels of TNFα following CAR-T therapy and itacitinib once-daily (QD) and twice-daily (BID) dosing regimens.
Methods:
The phase 2 study PKPD-evaluable population included 63 patients receiving CAR-T (axicabtagene ciloleucel) therapy for hematologic malignancies incorporating Part 1 (open-label; itacitinib 200 mg QD) and Part 2 (randomized, double-blind; itacitinib 200 mg BID vs placebo). Patients were administered itacitinib from Day -3 through Day -1 (pre-IEC) and continued post-infusion from Day 0 through Day 26 (itacitinib treatment period). The observation time was up to 90 days (Frigault MJ et al, Blood 2023 142 (Supplement 1):356).
The integrated PKPD analysis incorporated the longitudinal PK CAR-T levels, PD TNFα levels before initiation and during IEC therapy, and the previously developed population PK (PopPK) model predictions for itacitinib (Ivanova O, et al. Accepted at ACoP 2024).
A stepwise PKPD model development framework was applied for the analysis. Analysis was based on the aggregated PK and PD data due to the high variability in individual kinetics data for CAR-T and TNFα. The approach included 4 sequential steps: Validate CAR-T kinetics model on Study 211 data (based on a 3-phase model by A. Stein (Stein AM, et al. CPT Pharmacometrics Syst Pharmacol. 2019;8(5):285-295)Establish PKPD relationship for stimulatory CAR-T effect on TNFα levels; placebo data (CAR-T therapy without itacitinib) were used for estimation of model parametersGenerate aggregated itacitinib PK profile for a typical subject using the integrated PopPK model for itacitinib previously developed (Ivanova O, et al. Accepted at ACoP 2024)Integrate CAR-T PK, aggregated itacitinib PK and TNFα PD readouts into a joint PKPD model
Direct and indirect response models were tested to represent effect of CAR-T and itacitinib on TNFα. The impact of itacitinib was tested via plasma concentration or daily exposure (area under the concentration curve [AUC]). Models were evaluated towards minimization of Akaike Information Criterion value, relative standard errors of model parameters &lt;50%, and the goodness-of-fit plots.
Results:
Indirect (turnover) models for TNFα were found to best describe the PD data, with its half-life being 1.82 h-1 (Larsson J, et al. Eur J Pharm Sci. 2021;165;105937). Several different structural models were tested to describe the CAR-T effect on TNFα from Study 211 data. The CAR-T therapy stimulatory effect was optimally described using linear effect within turnover model, while itacitinib-induced inhibition implied a nonlinear effect with saturation based on a Hill equation for a daily AUC of the investigated drug. Infusion of CAR-Ts resulted in the increase in systemic TNFα levels and this response was further inhibited by the presence of itacitinib (kin parameter was affected).
Final model output was quantified using the AUC between the typical TNFα profiles for the placebo arm and active treatment arms (BID or QD administration of itacitinib) as a metric of PD response. The simulated BID regimen suppressed TNFα more effectively than QD, based on AUC metrics: 4391 pg∙hours/mL vs 2905 pg∙hours/mL.
Conclusions:
Aggregated TNFα profiles were adequately described by the integrated PKPD model incorporating CAR-T stimulatory dynamics with linear effect coupled with nonlinear inhibitory effect by the daily exposure of itacitinib. The itacitinib BID dosing regimen was associated with improved TNFα suppression to levels not exceeding the baseline (placebo) during the observation time.