Several successful applications of machine learning in various stages of the drug development pipeline in pharmaceutical companies have been published. However, within each data domain, there are still challenges related to the standard of data quality and data quantity needed to capitalize on the full potential of these methods for discovery. ADME, absorption, distribution, metabolism and excretion.