Background FDA is considering to establish a product standard to reduce nicotine in cigarettes to make them “minimally addictive or nonaddictive.” FDA has funded many clinical studies where smokers are switched to smoking low nicotine cigarettes to determine a nicotine ceiling that is appropriate for the protection of the public health. Unlike typical clinical trials involving pharmaceuticals or medical devices, ambulatory studies with low nicotine cigarettes face a unique challenge in that conventional nicotine non-study cigarettes are readily available to participants when protocols require them to exclusively use study cigarettes. As a consequence, protocol deviation in non-study product use is a major limitation common in such ambulatory studies, with up to 80 percent of participants using non-study cigarettes during the study. There is no published method for estimating the magnitude of such protocol deviation, i.e., the number of non-study cigarettes smoked by participants, in such studies.Methods We present a method for estimating the magnitude of noncompliance based on the proposition that the level of biomarker of exposure to a smoke constituent is proportional to the amount of the constituent per cigarette and the number of cigarettes smoked by participants. The method estimates the number of non-study cigarettes smoked by participants based on the discrepancies between the yield of smoke constituents (e.g., nicotine) and the level of the corresponding biomarkers measured in a study.Results Data from a confined study confirmed the validity of this method. Under-reporting on the magnitude of non-study cigarette use is widespread across studies using different low nicotine cigarettes. Participants in one of the largest published studies under-reported the number of non-study cigarette used by 79-90%.Conclusions Controlling and accurately estimating non-study cigarette use is critical for ambulatory low nicotine cigarette switching studies to ensure the resulting data can be appropriately evaluated to support science-based regulatory decision-making. In planning future studies, researchers should consider incorporating specific biomarkers that would enable objective assessment of both the prevalence and the magnitude of non-study cigarette use.