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XENObiotic-based PREDiction platform of inter-individual differences in drug metabolism

Objective

Inter-individual variability in drug metabolism remains a major barrier to clinical practice and drug development, often leading to adverse reactions, therapeutic inefficacy, and costly trial failures. While genetics explain only part of this variability, the contribution of the gut microbiome remains largely underestimated. The ERC-StG PREDICT-CARE project has shown that dietary (poly)phenols, a large family of plant xenobiotics metabolised through pathways that partly overlap with those involved in the metabolism of several drugs, give rise to reproducible metabolic phenotypes, defined by consistent inter-individual differences in the production of circulating phenolic metabolites and shaped by host genetics and gut microbial activity. These metabolic profiles may therefore represent a functional readout of individual xenobiotic-metabolising capacity and could potentially be used to help predict inter-individual differences in drug metabolism.

XENOPRED will investigate whether these findings can be translated into a multi-omics predictive platform designed to estimate individual drug metabolism profiles by integrating (1) PREDICT-CARE derived metabolic signatures, (2) polygenic risk scores reflecting human enzymatic capacity, and (3) microbiome-derived scores capturing microbial enzymatic potential. It will focus on two clinically relevant phenolic drugs, ibuprofen and paracetamol, to assess the predictive accuracy, feasibility, and
translational potential of this approach. Generalisability will be explored across other phenolic drugs, including irinotecan (cancer), levothyroxine (thyroid), and chlorpromazine (psychosis), for which evidence on colonic metabolism and inter-individual variability remains limited.

The project aims to develop and validate an integration-ready computational module for pharmaceutical R&D workflows and future clinical decision-support tools. By testing a safe, scalable, and cost-effective approach to stratifying individuals according to their metabolic capacity, XENOPRED aims to support safer prescribing, reduce development costs, and accelerate the uptake of personalised health solutions.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

(opens in new window) ERC-2026-POC

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Host institution

UNIVERSITA' DEGLI STUDI DI PARMA
Net EU contribution
€ 150 000,00
Address
VIA UNIVERSITA' 12
43121 PARMA
Italy
Region
Nord-Est Emilia-Romagna Parma
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Beneficiaries (1)