Behind the scenes: A medical natural language processing project

•Multidisciplinary team (MDT) model ensured a two-year long medical text processing (NLP) project was clinically relevant and technically solvable.•An academic setting helped connect diverse experts in databases, statistics, epidemiology, machine learning, NLP, engineering and medicine.•Up-front and regular time investment in cross-disciplinary learning and aligning research goals helped the MDT collaborated more effectively.•Domain knowledge from NLP and clinical experts was required to optimize the data sampling, annotation strategies and algorithm development.•Dynamic leadership, regular meetings and updates, clear task delegation, and an open learning environment helped maintain motivation and momentum.