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Content archived on 2024-05-29

Identification and characterization of the factors involved in CYP3A4 inter-individual variability


The molecular basis that makes a therapeutic drug become toxic has an enormous clinical relevance: it has been estimated that the fatal adverse drug reactions are between the 4th and 6th leading cause of death in developed countries. In addition, the lack of therapeutic effect of a drug by a deficient formation of the active metabolite or by its fast elimination can also lead to death.

The cytochrome P450s (CYPs) are the most relevant enzymes catalysing the biotransformation of drugs, and many of the fatal adverse drug reactions, as well as a lack of therapeutic effect of drugs, are due to an abnormal CYP activity. In the human liver the most important enzyme catalysing the biotransformation of drugs is the cytochrome P450 3A4 (CYP3A4).

This CYP is involved in the metabolism of 50% of currently used therapeutic drugs. As a consequence, variations in CYP3A4 activity have a major impact on pharmacokinetics and metabolic fate of drugs, drug-drug interactions and toxicology. In the population there are great differences in CYP3A4 activity and the result is a great inter-individual variability in the susceptibility to toxics, optimal drug doses and adverse reactions.

Nowadays, CYP3A4 activity variability is unpredictable, since the molecular mechanisms responsible for it are still unknown. Several studies have shown that this variability is genetically determined, ruling out environmental factors. In this project we intend to identify the critical mechanisms regulating CYP3A4 expression and then investigate whether these mechanisms are susceptible of inter-individual variability.

In a first step, the obtained information (genetic markers) will be used in connection to cardiovascular diseases, trying to find an association between them and the pharmacological effect obtained with different drugs. Finally, we intent find a simple test, in connection with selected genetic markers, able to predict CYP3A4 activity.

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Sinesio Delgado, 6

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