The in vitro evaluation and mathematical modeling Recommended Approaches aim to ensure appropriate selection and consistent application of model systems to accurately extrapolate in vitro data for prediction of clinical outcome. A comprehensive literature review conducted by the Pharmacology Core summarizes available in vitro and clinical data to identify critical knowledge gaps. These knowledge gaps are included in a detailed statement of work that outlines the particular needs for natural product characterization including the plan for further in vitro and clinical studies needed to generate predictive static or dynamic interaction models. Modeling and simulation approaches are then used to translate in vitro data to predict the likelihood and magnitude of a clinical natural product-drug interaction. Interaction models are leveraged further to aid in the design and analysis of natural product-drug interaction clinical studies.