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Updated: Oct 25, 2025

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
Published on: November 10, 2023
OpenCYP: An open source database exploring human variability in activities and frequencies of polymophisms for major
Susanna Vichi1, Franca Maria Buratti1, Emma Di Consiglio1
1Istituto Superiore di Sanità, Environment & Health Department, Viale Regina Elena 299, Roma, Italy.
Abstract:
The open source database "OpenCYP database" has been developed based on the results of extensive literature searches from the peer-reviewed literature. OpenCYP provides data on human variability on baseline of activities and polymophism frequencies for selected cytochrome P-450 isoforms (CYP1A2, CYP2A6, CYP2D6, CYP3A4/3A5 and CYP3A7) in healthy adult populations from world populations. CYP enzymatic activities were generally expressed as the metabolic ratio (MR) between an unchanged probe drug and its metabolite(s) in urine or plasma measured in healthy adults. Data on other age groups were very limited and fragmented, constituting an important data gap. Quantitative comparisons were often hampered by the different experimental conditions used. However, variability was quite limited for CYP1A2, using caffeine as a probe substrate, with a symmetrical distribution of metabolic activity values. For CYP3A4, human variability was dependent on the probe substrate itself with low variability when data considering the dextromethorphan/demethilathed metabolite MR were used and large variability when the urinary 6β-hydroxycortisol/cortisol ratio was used. The largest variability in CYP activity was shown for CYP2D6 activity, after oral dosing of dextromethorphan, for which genetic polymorphisms are well characterised and constitute a significant source of variability. It is foreseen that the OpenCYP database can contribute to promising tools to support the further development of QIVIVE and PBK models for human risk assessment of chemicals particularly when combined with information on isoform-specific content in cells using proteomic approaches.
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