Nicotine metabolism is a modifiable risk factor that is associated with several smoking-related outcomes, including smoking cessation rates and being a current smoker. Nicotine is primarily metabolized by the CYP2A6 liver enzyme. Medications that interact with nicotine by altering CYP2A6 activity may change how nicotine is metabolized and thus subsequent smoking outcomes. In this dissertation we study the effects of two CYP2A6 medications, namely efavirenz and nifedipine. In Chapter 2, we measured the changes in nicotine metabolism (represented as the nicotine metabolite ratio, NMR) after efavirenz (a CYP2A6 inducer) was discontinued in a virally suppressed cohort with HIV. The mean NMR difference was −0.24 (SD: 0.37, p<0.001), which is more than double a clinically significant change. In Chapter 3, we developed and validated several probabilistic models for smoking status based on cotinine lab assessments to facilitate future studies that require the identification of a smoking cohort. The best performing model was fit using logistic regression, which had acceptable discrimination (AUC= 0.77, 95%CI: 0.75-0.78) and calibration, and was found to be highly specific at many cutoff thresholds. In Chapter 4, we employed a new user, active comparator design to measure the change in the probability of being a current smoker, comparing nifedipine (a CYP2A6 substrate) to amlodipine (not a CYP2A6 substrate). Nifedipine users had slightly larger decreases in smoking status probability changes, with a difference in difference of -0.2% (95% CI: -0.3%, -0.2%). However, in a sub-analysis of individuals with a high probability of being a current smoker at baseline, no differences in the change of probabilities were between the study medications. The results of this dissertation advance the understanding of drug interactions with nicotine and generate tools to facilitate future smoking-related research in real-world data sources.