Missing data for key efficacy and safety endpoints in clinical trials have the potential to undermine the scientific integrity of the study and prevent definitive conclusions regarding the safety and efficacy of an experimental product. Much of the missing data is the result of poor protocol design and a lack of agreement in the scientific community regarding the collection of study data after treatment discontinuation instead of an inability to collect the data. Rather than dealing with the fundamental causes of missing data, the statistical community has traditionally attempted to explicitly impute the missing data based upon observed data or more recently through the use of statistical models that implicitly impute the missing data. In this article, the causes for missing data are described and a number of approaches to maintain the integrity of the studies are described.