SOURCE-LINKED INTELLIGENCE
Target mining for the development of therapeutics against pathogen-induced cancers
ical gap in the development of precise and preventive treatments. TagTIC addresses this challenge through a systems medicine approach that integrates microbiology, cancer biology, drug discovery, and artificial intelligence. By using innovative preclinical organoid model systems that closely resemble patient conditions, TagTIC aims to decipher complex host-pathogen interactions at single-cell and spatial resolution and to address them therapeutically. Research will focus on: (i) identifying vulnerable molecular nodes involved in pathogen-associated cancers; (ii) developing novel strategies for lead discovery and treatment; (iii) generating and analyzing innovative ex vivo models using 2D/3D cultures, patient-derived organoids, and organ-on-chip technologies. The network will train eleven Doctoral Candidates (DCs) towards translational leaders, capable of analyzing and solving complex biomedical needs with innovative strategies and approaches. DCs will follow a structured training program combining basic and translational science with cross-sectoral exposure to academia and industry.
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 4281579.84
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T05:31:32.981Z. This is not the publication date.