Cytokine Dynamics in Action: A Mechanistic Approach to Assess Interleukin 6 Related Therapeutic Protein-Drug-Disease Interactions

Abstract

Understanding cytokine-related therapeutic protein-drug interactions (TP-DI) is crucial for effective medication management in conditions characterized by elevated inflammatory responses. Recent FDA and ICH guidelines highlight a systematic, risk-based approach for evaluating these interactions, emphasizing the need for a thorough mechanistic understanding of TP-DIs. This study integrates the physiologically based pharmacokinetic (PBPK) model for TP (specifically interleukin-6, IL-6) with small-molecule drug PBPK models to elucidate cytokine-related TP-DI mechanistically. The integrated model successfully predicted TP-DIs across a broad range of both constant and fluctuating IL-6 levels, as observed in patients with rheumatoid arthritis, Crohn's disease, HIV-infection, and those undergoing hip-surgery or bone marrow transplantation (all simulated AUC and Cmax ratios were within a twofold error of the observed data). Constant IL-6 levels that would be associated with mild, moderate, and strong inhibitory interactions were estimated. The time-course and extent of TP-DI potential were also assessed in cytokine storm triggered by SARS-CoV-2 infection (COVID-19) and T-cell engager therapies (blinatumomab, mosunetuzumab, and epcoritamab). Additionally, scenarios involving concurrent CYP enzyme suppression by IL-6 and induction by rifampicin were assessed for the magnitude of drug interaction. By providing a robust mechanistic framework for understanding cytokine-drug interactions and establishing reliable exposure-response relationships, this study enhances predictive accuracy and informs human dosing strategies. It demonstrates the potential of PBPK models to improve therapeutic decision making and patient care, particularly in inflammatory conditions.