Randomized clinical trials are considered as the gold standard to demonstrate causal relationships between a treatment and an outcome. However, if the analysis adjust for an intermediate variable that occurs between the treatment and the outcome, then randomization will break down. We apply and extend a causal inference technique called principal stratification to address concerns regarding two different types of intermediates that arise in clinical endpoint bioequivalence studies and pragmatic randomized clinical trials.