Background: Cytochrome P450 (CYP) enzymes play a pivotal role in the metabolism of many drugs, and their inhibition can lead to significant drug-drug interactions (DDIs). Understanding the biochemical pathways involved in CYP inhibition is essential for improving drug safety and efficacy. This review explores the mechanisms of CYP inhibition, reaction phenotyping, and predictive models used to assess drug interactions, with a focus on high-throughput screening, probe assays, and modeling approaches.

Aim: This review aims to provide a comprehensive understanding of CYP inhibition mechanisms, with an emphasis on assessing and predicting drug-drug interactions. It examines in vitro methods, the implications of CYP inhibition in clinical practice, and the use of predictive models to identify potential drug interactions early in the drug development process.

Methods: We conducted a literature review on current methodologies for assessing CYP inhibition, including early high-throughput screening using fluorescent and luminescent assays, probe assays with human liver microsomes (HLM), and model-based approaches. Emphasis was placed on the validation of these methods, limitations associated with each approach, and their predictive capabilities. The use of CYP inhibition assays in combination with predictive modeling techniques, such as ligand- and structure-based models, was also explored.

Results: The review highlighted several methods for assessing CYP inhibition, including the use of cocktail assays, recombinant enzymes, and high-throughput screening. Despite the advantages of these techniques, challenges remain in ensuring substrate selectivity and overcoming limitations such as metabolic pathway complexity and the potential for non-specific inhibition. The application of predictive models, using databases and structural simulations, was found to offer promising tools for early DDI prediction and risk assessment.

Conclusion: Understanding CYP inhibition mechanisms is crucial for optimizing drug safety and efficacy. High-throughput screening, probe assays, and predictive modeling techniques provide valuable insights into potential DDIs. However, challenges remain in refining these methods to enhance their predictive accuracy and applicability in clinical settings. Continued advancements in these areas are essential for improving drug development processes and minimizing adverse drug interactions.