Physiologically Based Pharmacokinetic Modeling To Predict Drug- Biologic Interactions with Cytokine Modulators: Are These Relevant and Is Interleukin-6 Enough?

Abstract

Drugs that modulate cytokine levels are often used for the treatment of cancer as well as inflammatory or immunologic disorders. Pharmacokinetic drug-biologic interactions (DBIs) may arise from suppression or elevation of cytochrome P450 (P450) enzymes caused by the increase or decrease in cytokine levels after administration of these therapies. There is in vitro and in vivo evidence that demonstrates a clear link between raised interleukin (IL)-6 levels and P450 suppression, in particular CYP3A4. However, despite this, the changes in IL-6 levels in vivo rarely lead to significant drug interactions (area under the curve and Cmax ratios < 2-fold). The clinical significance of such interactions therefore remains questionable and is dependent on the therapeutic index of the small molecule therapy. Physiologically based pharmacokinetic (PBPK) modeling has been used successfully to predict the impact of raised IL-6 on P450 activities. Beyond IL-6, published data show little evidence that IL-8, IL-10, and IL-17 suppress P450 enzymes. In vitro data suggest that IL-1b, IL-2, tumor necrosis factor (TNF)-a, and interferon (IFN)-g can cause suppression of P450 enzymes. Despite in vivo there being a link between IL-6 levels and P450 suppression, the evidence to support a direct effect of IL-2, IL-8, IL-10, IL-17, IFN-g, TNF-a, or vascular endothelial growth factor on P450 activity is inconclusive. This commentary will discuss the relevance of such drug-biologic interactions and whether current PBPKmodels considering only IL-6 are sufficient.