Imagine the liver as a complex city where cancer is like a hidden intruder. This project maps out exactly where the intruder hides and who they talk to, using high-tech cameras to see individual cells. By creating tiny 'mini-livers' in the lab, researchers can test new medicines on a mirror image of the patient's disease before ever giving it to the person.
Liver cancer has a high mortality rate and poor treatment response, particularly in advanced HCC where median survival is under 2 years. There is a critical lack of precision tools to identify at-risk populations and predict which patients will respond to expensive immunotherapies.
A preclinical drug testing platform consisting of mouse models and patient-derived organoids, and an AI-driven cellular map (atlas) of liver cancer.
If you are a drug developer dealing with high failure rates in liver cancer trials — this project developed preclinical platforms using mice and organoids that allow for the discovery or repurposing of affordable therapies. This reduces risk by testing against a detailed human liver cancer blueprint before clinical stages.
If you are a diagnostic company dealing with the lack of precision oncology tools — this project developed AI-based molecular markers to identify treatment response. This allows for the creation of software that predicts which of the 1 million annual liver cancer patients will respond to specific therapies.
If you are a biotech firm dealing with the difficulty of identifying high-risk pediatric patients — this project identified that 17% of children with hepatoblastoma show specific genetic alterations at the 11p15.5 locus. This provides a concrete molecular target for developing early-detection screening kits.
Based on available project data, specific pricing for the tools is not mentioned, although the project aims to develop 'affordable treatments'.
The project utilizes 15 patient cohorts and 6,700 samples to build its atlas, providing a significant data foundation for industrial scaling of AI markers.
Based on available project data, the project is in the research and development phase (2023-2028), and specific licensing terms have not yet been disclosed.
The project intends to deliver accessible and reusable data and tools to support the UNCAN.eu platform and inform healthcare professionals.
The project period runs from December 1, 2023, to November 30, 2028, suggesting that final validated tools will be available toward the end of 2028.
The consortium is heavily weighted toward research and academia, with 14 partners across 9 countries. While 5 universities and 5 research institutes drive the science, the inclusion of 1 SME and 1 industry partner (7% industry ratio) indicates a focus on translational research rather than immediate commercial product launch. The presence of hospitals and patient associations ensures high-quality access to the 6,700 samples required for validation.
Contact Fundacio de Recerca Clinica Barcelona-Institut d'Investigacions Biomediques August Pi i Sunyer
Contact us to explore licensing opportunities for the liver cancer AI markers and organoid platforms.
