Simulation modeling can be used to obtain cost-effectiveness information on drugs still in early development. OBJECTIVE: To construct a disease-based simulation model characterizing the current patterns of treatment of osteoporosis and their associated clinical and economic outcomes. The model can then be used to estimate the marginal value of each proposed clinical characteristic of a new drug for osteoporosis. METHODS: We performed a systematic literature review of the epidemiology, treatment guidelines and patterns of osteoporosis, as well as of previous economic models and cost-effectiveness literature in this area. Interviews with clinicians and epidemiologists were conducted to identify important parameters for inclusion in the model. Information from these sources was utilized to develop the model. RESULTS: A state transition model has been constructed. Twenty-five health states are used, with the inclusion of four fracture sites (hip, wrist, vertebral and other), and other diseases (i.e., breast cancer, coronary heart disease) that osteoporosis interventions may impact. Simulation duration, cohort size, patient age matrices and distribution of initial health states call all be varied, allowing a number of assumptions to be tested. Quality adjusted life year values and costs for the given year and subsequent years associated with each health state are included. The impact of relative risks associated with each intervention are incorporated into the model, together with start and rise times, fall and stop times. CONCLUSION: Through simulation modeling, data can be combined to estimate clinical outcomes and economic consequences of osteoporosis treatment early in the drug development process. Such information can then be used to establish the key clinical characteristics that will need to be obtained in order to achieve reimbursement.