The LUCIA project, funded under the European Commission's Mission on Cancer as part of Horizon Europe aims to address critical challenges in lung cancer diagnosis and prevention
Early detection is essential for improving outcomes and reducing mortality, yet current methods, such Low-Dose Computed Tomography (LDCT), often lack precision due in part to an incomplete understanding of the risk factors and cellular processes associated with lung cancer. While the high-risk link between tobacco smoking and lung cancer is well established, additional factors including age, environmental pollutants, multi-morbidities, genetic predispositions, and differences in biological pathways, remain underexplored.
LUCIA focuses on identifying these diverse risk factors developing effective diagnostic methods tailored to lung cancer and its subtypes. The key aim of LUCIA is to create a comprehensive toolbox for discovering and understanding new risk factors that contribute to lung cancer development. The toolbox encompasses the analysis of three interrelated aspects:
- Personal risk factors: These include exposure to chemical pollutants and behavioural and lifestyle factors.
- External risk factors: This encompasses urban and built environments, transportation systems, social aspects, and climate influences.
- Cellular processes: This includes genetic, epigenetic, metabolic, and age-related changes.
LUCIA will validate the impact of these risk factors and the associated biological responses through three clinical use cases: general population risk assessment and screening, precision screening of high-risk populations, and digital diagnostics. The resulting evidence will be translated into policymaking recommendations, to implement them in a screening program for lung cancer.
The LUCIA consortium includes experts in lung cancer research, diagnostic technologies, AI ethics and legal frameworks, and EU policy, including four clinical partner hospitals across Europe. Ulster is leading activities on risk factor analysis of environmental and sociodemographic geospatial data using state-of-the-art geospatial-AI.