Targeted but Troubling: CYP450 Inhibition by Kinase and PARP Inhibitors and Its Clinical Implications - Martin Kondža; Josipa Bukić; Ivan Ćavar; Biljana Tubić (Drugs and Drug Candidates, 2025)
Cytochrome P450 (CYP450) enzymes are pivotal in the metabolism of numerous anticancer agents, with CYP3A4 being the predominant isoform involved. Inhibition of CYP450 enzymes is a major mechanism underlying clinically significant drug-drug interactions (DDIs), particularly in oncology, where polypharmacy is frequent. This review aims to provide a comprehensive and critical overview of CYP450 enzyme inhibition, focusing specifically on the impact of kinase inhibitors (KIs) and poly adenosine diphosphate-ribose polymerase (PARP) inhibitors. A systematic review of the current literature was conducted, focusing on the molecular mechanisms of CYP450 inhibition, including reversible, time-dependent, mechanism-based, and pseudo-irreversible inhibition. Specific attention was given to the inhibitory profiles of clinically relevant KIs and PARP inhibitors, with analysis of pharmacokinetic consequences and regulatory considerations. Many KIs, such as abemaciclib and ibrutinib, demonstrate time-dependent or quasi-irreversible inhibition of CYP3A4, while PARP inhibitors like olaparib and rucaparib exhibit moderate reversible and time-dependent CYP3A4 inhibition. These inhibitory activities can significantly alter the pharmacokinetics of co-administered drugs, leading to increased risk of toxicity or therapeutic failure. Regulatory guidelines now recommend early identification of time-dependent and mechanism-based inhibition using physiologically based pharmacokinetic) (PBPK) modeling. CYP450 inhibition by KIs and PARP inhibitors represents a critical but often underappreciated challenge in oncology pharmacotherapy. Understanding the mechanistic basis of these interactions is essential for optimizing treatment regimens, improving patient safety, and supporting personalized oncology care. Greater clinical vigilance and the integration of predictive modeling tools are necessary to mitigate the risks associated with CYP-mediated DDIs.