PII-097 - MECHANISTIC INSIGHTS INTO CYTOKINE ANTAGONIST-DRUG INTERACTIONS: A PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODELING APPROACH WITH TOCILIZUMAB AS A CASE STUDY

X. Pan¹, F. Stader², C. Liu¹, A. Derbalah¹, M. Jamei¹, I. Gardner¹; ¹Certara, Sheffield, England, United Kingdom, ²Certara UK, Sheffield, United Kingdom.

Background: Understanding interactions between cytokine antagonists and drugs is essential for effective medication management in inflammatory conditions. Recent FDA and ICH guidelines highlight a systematic, risk-based approach to evaluating these interactions, emphasising the need for a comprehensive mechanistic understanding. Cytokines like interleukin-6 (IL-6) suppress cytochrome P450 (CYP) enzymes, reducing the metabolism of drugs that are CYP substrates. Cytokine antagonists can counteract this, restoring CYP activity and reducing drug exposure.

Methods: A physiologically-based pharmacokinetic (PBPK) model was developed to simultaneously simulate interactions between cytokine antagonists and small molecule drugs, investigating their interaction liability. An established therapeutic protein (TP) PBPK model was expanded to include competition between cytokine antagonists and endogenous cytokines for cytokine receptors. This competition alters the cytokine-cytokine receptor complex levels, influencing CYP activity and affecting the metabolism of CYP substrates.

Results: Tocilizumab, an IL-6 receptor antagonist, treats several inflammatory conditions associated with elevated IL-6 levels. Using prior in vitro and in vivo data, we developed the TP PBPK model to describe the PK of tocilizumab and its interactions with endogenous IL-6 and IL-6 receptors in liver and gut. The model accurately predicted the concentration-time profile of tocilizumab and captured clinically observed changes in simvastatin exposure before and after tocilizumab treatment in patients with active rheumatoid arthritis, with observed data within a 1.5-fold prediction error. Notably, simvastatin AUC decreased by 2.3-fold one week post-treatment, diminishing to 1.67-fold after five weeks. These clinical findings were successfully simulated in our model (2.3-fold after 1 week, 1.45-fold after 5 weeks). The model was further used to explore interaction liability between tocilizumab and other CYP substrates.

Conclusion: In conclusion, this study demonstrates the utility of PBPK models in providing a mechanistic understanding of cytokine antagonist-drug interactions, supporting enhanced therapeutic decision-making and optimising patient care by enabling more precise medication management in inflammatory conditions.