Medication errors are a major problem for patient’s safety, causing harm (2M lives globally) and economic burden (€4,5B-€21,8B, depending on the country). ICTs such as Clinical Decision Support Systems can help reduce them, but they lack accuracy because they are unable to identify risky situations that are not covered by their fixed alarm systems. MedAS incorporates data form different sources and uses big data analytics and machine learning algorithms to identify previously undetectable prescription errors. In order to bring MedAS to TRL9 and commercialize it in the European market, we aim to improve its accuracy and patient surveillance capacities, as well as to extend its ability to detect new types of patients and the adjustment of MedAS to the markets we aim to reach. We will launch MedAS in Q1 2020, first in those countries that have higher rates of EHR adoption (Germany, UK and Italy) and then with others that advanced in health technologies application, reaching a global market share of 6,14% by Q4 20204.