Lung cancer remains the leading cause of cancer-related mortality in Taiwan and globally, with increasing incidence and the highest healthcare cost burden among cancers in Taiwan. Despite the widespread use of low-dose computed tomography (LDCT) for screening smokers, over half of lung cancer cases in Taiwan occur in never-smokers, highlighting the need for improved risk stratification. Current national LDCT screening programs do not collect comprehensive risk-related data, limiting their predictive accuracy. This project proposes a five-year, multi-center initiative to establish an integrated biospecimen and clinical data collection system. In its first year, a feasibility pilot will be conducted, followed by recruitment of 12,000 participants. Data collection will include biospecimens (blood, urine, tissue), genomic and proteomic analyses, imaging, and detailed questionnaires covering lifestyle, environmental, and occupational exposures. The project will also develop and validate lung cancer prediction models incorporating epidemiologic, biomarker, air pollution, and imaging data. A Common Data Model (CDM) will be implemented to ensure cross-institutional data standardization and support future international collaboration.