Precision medicine aims at delivering the right treatment at the right time to the right person. This goes hand in hand with a deeper genetic understanding of a patient’s disease. An important milestone is the recent approval of an anti-cancer drug, that was granted by the FDA based solely on a tumor’s biomarker and not on where in the body the tumor started. How can statistics and machine learning help to identify a patient’s best treatment option? I will walk you through a typical Phase II clinical trial in order to discuss the challenge it poses to predict a patient’s response to a treatment that she has not yet received, demonstrate the opportunity of analysing a large set of biomarkers in a clinical trial with relatively few patients, as well as to point out the need to define concrete patient subgroups.