Kenneth Koh1, Sheng Yuan Chin1, James Chun Yip Chan1,2
1Singapore Institute of Food and Biotechnology Innovation (SIFBI), Agency for Science, Technology and Research (A*STAR), 2A*STAR Skin Research Labs (A*SRL), A*STAR, Singapore
Introduction: Interleukin-6 (IL-6) is one of the major proinflammatory cytokines that is elevated in several cancer sub-types [1]. Studies have demonstrated that IL-6 possesses suppressive effect on CYP3A4 enzyme activity with the half maximal inhibition concentration (EC50) ranging from 3.2 pg/mL to 213.5 pg/mL and a maximal suppression value ranging from 58.3% to100% [2-4]. Tyrosine kinase inhibitor (TKI) is an antineoplastic class of drugs that blocks tyrosine kinase-mediated signal transduction cascades thereby disrupting cell signalling and growth and are primarily used in anti-cancer treatments [5]. Virtually all TKIs are principally metabolized by cytochrome P450 (CYP) enzyme CYP3A4, but heterogeneity in systems physiology (such as IL-6 levels) within the cancer populations can lead to variability in drug efficacy [6-7]. While physiologically-based pharmacokinetic (PBPK) modelling were developed for numerous TKIs for assessing drug response and PK, they do not account for the suppressive effect of IL-6 on CYP3A4 activity in cancer, and existing PBPK models of IL-6 suppression on CYP activity were developed for probe substrates such as caffeine, omeprazole and midazolam rather than disease-specific drugs. Objectives: Our objective is to utilize PBPK modelling to assess the suppressive effect of high IL-6 levels on CYP3A4-metabolizing anti-cancer agents and to accurately predict their PK in cancer populations. Methods: A whole-body PBPK model for midazolam was constructed using the Simbiology module in MATLAB. The midazolam model was developed to validate the IL-6 suppression on CYP3A4 activity by modelling midazolam PK in both healthy and cancer populations. Acalabrutinib and erlotinib PBPK models were subsequently constructed to evaluate the effect of elevated IL-6 levels on each TKIs exposure in chronic lymphocytic leukemia (CLL) and non-small cell lung cancer (NSCLC) patients respectively. In addition to IL-6 levels, cancer-specific systems physiology data including differences in body height and weight, hematocrit and albumin levels were also implemented into the cancer models. Results: Both the area-under-the-curve between time 0 to t h (AUC0-t) and total clearance (CL) reported in the observed clinical data in a healthy population were more than two times higher versus the cancer populations demonstrating a marked difference in midazolam PK between the two populations [8-11]. By implementing IL-6 levels with inter-subject variability as reported for healthy and cancer subjects, alongside its suppressive effect on CYP3A4 activity within our cancer models [12-14], the degree of CYP3A4 suppression ranged from 14.61% and up to 40.1% in our midazolam simulations for cancer populations. The midazolam PBPK model was able to accurately predict the PK profiles for all simulations (one healthy, one NSCLC and two groups with several cancer types) with excellent fitting to observed concentration points and all simulated AUC0-t were within 1.2-fold of the observed clinical data. Sensitivity analysis confirmed that changes in blood-to-plasma ratio and fraction unbound of midazolam due to reduction in hematocrit and albumin levels observed in cancer patients led to minimal changes in PK profiles, and differences in midazolam PK profiles were primarily attributed to CYP3A4 suppression by IL-6. Likewise for the two TKIs, both AUC0-t and CL in the observed clinical data were significantly different between the healthy and cancer populations. The simulated AUC0-t and CL were all within 2.0-fold and 1.2-fold of the observed clinical data for both the acalabrutinib CLL and erlotinib NSCLC model respectively with good fitting to observed clinical datapoints. Conclusions: Our findings indicate that IL-6 exerts considerable impact on the pharmacokinetic profile of CYP3A4-dependent substrates in cancer populations with elevated IL-6. Importantly, this was demonstrated using drugs used clinically for cancer treatment, rather than relying only on probe substrate pharmacokinetics. Our work provides an extension to existing cancer models to improve dosing regimens in cancer populations and possibly in other proinflammatory conditions with elevated IL-6 levels.
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Reference: PAGE 33 (2025) Abstr 11508 [www.page-meeting.org/?abstract=11508]
Poster: Drug/Disease Modelling - Oncology