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Endogenous biomarkers for assessing CYP3A4 and CYP2D6 activity: A critical review
Shambhavi Parab1, Imam H Shaik2, Raman Venkataramanan3
1Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania.
Abstract:
Cytochrome P450 (P450) enzymes play an important role in the biotransformation of both exogenous and endogenous compounds. Variability in P450 expression and activity impacts drug-metabolizing capacity and contributes to interindividual differences in drug exposure and therapeutic outcomes. Exogenous probe substrates have traditionally been used to assess the in vivo P450 enzyme activity. However, their application can be limited in vulnerable populations such as pregnancy, transplantation, pediatrics, and elderly. Endogenous biomarkers have emerged as minimally invasive potential alternatives that can reflect the P450 enzyme activity under different physiologic and clinical conditions. In this minireview, we critically examine various endogenous biomarkers that have been proposed to assess P450 activity, with specific emphasis on CYP3A4 and also discuss emerging endogenous biomarkers of CYP2D6 activity. We summarize mechanistic and translational applicability and regulatory guidelines in predicting drug-drug interactions and use of mathematical modeling and simulation approaches to validate the biomarkers. Additionally, we discuss the potential role of metabolomics in endogenous biomarker discovery and outline current limitations and future directions underscoring the utility of endogenous biomarkers in drug metabolism and drug disposition in patients. SIGNIFICANCE STATEMENT: Endogenous biomarkers offer a minimally invasive mechanistic approach for assessing in vivo P450 activity and complement traditional drug probe-based phenotyping strategies. This minireview evaluates the currently used endogenous biomarkers of CYP3A4 and emerging candidates for CYP2D6, highlighting their translational advances, limitations, and potential integration with metabolomics and model-informed drug development for drug disposition and interaction assessment.
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