Under the leadership of Drs. Leng and Pajewski, the WF OAIC Biostatistics and Research Information Systems Core (BIC) will build on its long-term success in biostatistical collaboration and expand statistics/informatics tools tailored to research in aging. The proposed Core is comprised of a team of highly qualified investigators and staff with the full range of expertise relevant to the WF OAIC mission, including design and management of observational studies and randomized trials, centralized data entry and processing, centralized and decentralized data management, statistical analysis of data from complex study designs and data sources and development of novel statistical methods. The BIC has added additional expertise in machine learning and analysis considerations for pragmatic studies leveraging the electronic health record. The BIC members are committed to the WF OAIC’s programmatic aims to: 1) discover new pathways contributing to age-related declines in physical function and disability risk; 2) develop, evaluate, and refine strategies for disability prevention and treatment; 3) translate proven strategies beyond the traditional research environments; and 4) train the next generation of research leaders focused on disability treatment and prevention. In close collaboration with all other OAIC cores, we propose four Specific Aims: 1. To participate as investigators for WF OAIC projects including: 4 Pilot Studies, 2 Developmental Projects, and 8 Externally-funded Projects related to WF OAIC aims and themes. As co-investigators, BIC members are actively involved in study design and conduct. Their roles include recruitment monitoring, randomization, and safety monitoring; sample size determination; data management; statistical analysis and interpretation; and presentation/publication of results. 2. To play an integral role in training OAIC-supported scholars in the design, planning, conduct, and analysis and interpretation of aging-related research projects. The BIC will also extend its strong record of innovative discovery and evaluation through Specific Aims 3 and 4, which are to: 3. Develop novel statistical applications & methods development for analytical issues associated with aging research. 4. Develop unique research information systems to facilitate biomarker initiatives for aging studies. To accommodate the growing scope and constant evolution of aging-relevant biomarkers, during Years 1-2, we will build a novel, flexible, structured approach to storage and sharing of biomarker data within our time-tested, state-of-the-art data management system.