DESCRIPTION (provided by applicant): There are multiple efficacious pharmacotherapies for tobacco dependence, yet we still do not know: which medications work best, how best to match individuals to medications, how to combine medications, and how medications achieve their effects. These knowledge gaps are due, in part, to a lack of head-to-head comparisons of pharmacotherapies, including newer pharmacotherapies (e.g., the nicotine lozenge) and combinations of pharmacotherapies. In addition, clinicians and smokers have no scientifically based algorithms to guide the use of these medications because of the limited knowledge about which medications are most efficacious in particular populations of smokers. Also lacking are data that reveal how pharmacotherapies work, making it difficult to develop new pharmacotherapies on a rational basis. Participants (n = 1,520) will be randomly assigned to one of five medication conditions: nicotine patch, nicotine lozenge, bupropion, nicotine patch + nicotine lozenge, and bupropion + nicotine lozenge (n= 264/condition) and a placebo control condition (n=200). An extensive set of assessments will be collected from participants including: genotypes, personality, psychiatric symptoms and diagnoses, physiologic and medical status, diet, alcohol use/abuse, social relations, quality of life, exercise, smoking, withdrawal symptoms, stress, and nicotine dependence. These constructs will be assessed using psychometrically sound questionnaires, structured interviews, physical tests, and ecological momentary assessment (EMA). Assessments wilt serve three vital purposes: 1) to measure treatment outcomes (e.g., abstinence, withdrawal symptoms, weight gain); 2) to develop treatment matching algorithms based on individual differences (e.g., gender, level of dependence); and 3) to assess mechanisms of treatment effects (e.g., withdrawal suppression), tn sum, Project I will produce the best evidence to date on relative efficacies and mechanisms of action of cessation pharmacotherapies, and will provide algorithms to guide medication use.