BACKGROUND: Colorectal cancer (CRC) screening in Spain uses a fecal-occult blood test (FOBT) for screening and colonoscopy as diagnostic tool. Adenomas constitute the most frequent findings of this colonoscopy, and the removal of these premalignant lesions is considered the main contributor to the reduction of mortality and incidence of CRC. There is no clear agreement regarding the risk classification of adenomas as well as the optimal surveillance strategy for each degree of risk. Genomics may contribute to further delineate individual risk, and its characterization is crucial for improving the effectiveness of surveillance strategies by targeting individuals who would benefit the most. OBJECTIVE: To optimize, within a CRC screening program, surveillance of premalignant lesions using individual risk-based strategies, based on genetic analysis, that take into account benefits, harms and costs. METHODS: A discrete-event simulation model that reproduces the process of screening and takes into account the costs at every stage, from invitation to screening to surveillance of findings will be upgraded. The natural history of the disease will be included, with special emphasis on the events after adenoma detection at screening colonoscopy. Based on the results of a study aimed at identifying common genetic variants associated with an increased susceptibility to develop colorectal adenomas, the risk of developing cancer or recurrent adenomas according to the clinical characteristics of the patients will be included in the model. The interval between surveillance colonoscopies will be optimized with the objective of minimizing the number of colonoscopies while keeping the same level of effectiveness, defined as the impact on incidence of advanced adenomas and cancer over time. IMPLICATIONS: Simulation models can help in the design of personalized screening strategies. Personalizing CRC screening through surveillance strategies may improve allocation of resources under cost constraints, minimize harms and maximize benefits of population-based programs, affecting millions of people.