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  • Title: Multiplex Phenotyping for Systems Medicine: A One-Point Optimized Practical Sampling Strategy for Simultaneous Estimation of CYP1A2, CYP2C9, CYP2C19, and CYP2D6 Activities Using a Cocktail Approach.
    Author: de Andrés F, Terán S, Bovera M, Fariñas H, Terán E, LLerena A.
    Journal: OMICS; 2016 Feb; 20(2):88-96. PubMed ID: 26600202.
    Abstract:
    Phenotyping of the CYP450 enzyme activities contributes to personalized medicine, but the past phenotyping approaches have followed a piecemeal strategy measuring single enzyme activities in vivo. A barrier to phenotyping of populations in rural and remote areas is the limited time and resources for sample collection. The CEIBA cocktail approach allows metabolic capacity estimation of multiple CYP450 enzymes in a single sample analysis, but the attendant sample collection schemes for applications in diverse global settings are yet to be optimized. The present study aimed to select an optimal matrix to simultaneously analyze CYP450 enzyme activities so as to simplify the sampling schemes in the phenotyping protocol to enhance its throughput and feasibility in native populations or in remote and underserviced geographies and social contexts. We evaluated 13 Ecuadorian healthy volunteers for CYP1A2, CYP2C9, CYP2C19, and CYP2D6 genotypes and their metabolic phenotypes, including CYP3A4, in plasma and urine after administering one reduced dose of caffeine, losartan, omeprazole, and dextromethorphan. Pharmacokinetic analyses were performed, and the correlation between AUC parent/AUC metabolite and the ratio between concentrations of probe drugs and their corresponding metabolites at timepoints ranging from 0 to 12 hours post-dose were analyzed. A single sampling timepoint, 4 hours post-dose in plasma, was identified as optimal to reflect the metabolic activity of the attendant CYP450 enzymes. This study optimizes the CEIBA multiplexed phenotyping approach and offers new ways forward for integrated drug metabolism analyses, in the pursuit of global personalized medicine applications in resource-limited regions, be they in developed or developing countries.
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