(T-110) PK/PD Modeling of Dexamethasone in Heart and Lung Tissues in an Animal Model of Cytokine Release Syndrome
Tuesday, October 21, 2025
7:00 AM - 1:45 PM MDT
Location: Colorado A
William Jusko – Department of Pharmaceutical Sciences – University at Buffalo; Wensi Wu – Department of Pharmaceutical Sciences – University at Buffalo; Nitheesh Yanamandala – Department of Pharmaceutical Sciences – University at Buffalo
Nitheesh Yanamandala: No financial relationships to disclose
Objectives: Cytokine release syndrome (CRS) is a life-threatening inflammatory condition caused by excessive release of cytokines, commonly triggered by infections such as COVID-19, cancer therapies including chimeric antigen receptor (CAR) T-cell therapy and Immune checkpoint inhibitors (ICI), or autoimmune disorders [1]. Dexamethasone (DEX), a long-acting corticosteroid, is clinically approved to manage CRS, particularly in COVID-19 patients [2]. Previous studies have focused on DEX disposition and anti-inflammatory effects in plasma [3]. Since the elevated proinflammatory mediators such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and nitric oxide (NO) in tissues may directly contribute to CRS complications such as cardiac inflammation in ICI-therapies and acute respiratory distress syndrome (ARDS) in severe COVID-19, understanding the tissue-specific effects of DEX is essential [4],[5]. This study investigates the pharmacokinetics (PK) and pharmacodynamics (PD) of DEX in heart and lung tissues of lipopolysaccharide (LPS)-challenged rats by quantifying DEX and biomarker concentrations. This study determines whether tissue biomarker responses provide additional mechanistic PK/PD insights beyond plasma measurements.
Methods: Male Wistar rats received 5 mg/kg LPS intraperitoneally to induce systemic inflammation and mimic CRS. DEX was dosed subcutaneously at 0 (control), 0.005, 0.025, and 0.225 mg/kg. Blood, heart, and lung samples were collected at various time points over 48 hours. DEX concentration in plasma and tissues was quantified via LC-MS, IL-6 and TNF-α via ELISA, and NO via chemical assay. PK/PD model fitting was performed using ADAPT5.
Results: The PK of DEX exhibited biexponential kinetics and showed dose-independent early-phase kinetics, dose-proportional AUC indicating linear systemic clearance, and terminal phase changes with dose suggesting nonlinear distribution. Tissue analysis showed high and nonlinear tissue-to-plasma biomarkers with the AUCs being about 10-fold higher in tissues than plasma. Surprisingly, DEX showed minimal suppression of IL-6, TNF-α, and NO in tissues. Plasma assessments confirmed previous studies demonstrating strong suppression of biomarkers following DEX [3].
Conclusions: The optimal PK model of DEX was a two-compartment model with nonlinear distribution clearance. Nonlinearity in DEX tissue partitioning (Kp) and an extended terminal phase are consistent with known binding of DEX to glucocorticoid receptors. Cytokine and NO measurements in plasma but not tissues confirm efficacy of DEX. These findings provide a foundation for comparative evaluation of other drugs and further translational modeling to optimize dosing strategies for treating CRS in humans [6].
Citations: [1] Shimabukuro-Vornhagen, A., et al., Cytokine release syndrome. J Immunother Cancer, 2018. 6(1): p. 56. [2] Romanou, V., et al., Dexamethasone in the Treatment of COVID-19: Primus Inter Pares? J Pers Med, 2021. 11(6). [3] Świerczek, A. and W.J. Jusko, Pharmacokinetic/Pharmacodynamic Modeling of Dexamethasone Anti-Inflammatory and Immunomodulatory Effects in LPS-Challenged Rats: A Model for Cytokine Release Syndrome. J Pharmacol Exp Ther, 2023. 384(3): p. 455-472. [4] Wu, Y., Y. Xu, and L. Xu, Drug therapy for myocarditis induced by immune checkpoint inhibitors. Front Pharmacol, 2023. 14: p. 1161243. [5] Montazersaheb, S., et al., COVID-19 infection: an overview on cytokine storm and related interventions. Virol J, 2022. 19(1): p. 92. [6] Świerczek, A. and W.J. Jusko, Anti-inflammatory effects of dexamethasone in COVID-19 patients: Translational population PK/PD modeling and simulation. Clin Transl Sci, 2023. 16(9): p. 1667-1679.