Evidence-based medicine has considerably advanced the treatment of coronary heart disease (CHD), and its implementation was driven by multicenter interventional trials. However, most large‐scale clinical trials and therapies did not relevantly reduce the residual risk. Therefore, innovative approaches to foster individualized pharmacotherapy in CHD are urgently needed. The objective of MATCH is the identification of a biomarker signature, which associates with beneficial outcome on specific lipid therapy. We will take an interdisciplinary approach integrating knowledge from various disciplines. Bioinformatics analyses will generate a molecular biomarker signature of responders (subjects with no clinical events during follow-up) versus non-responders (subjects with multiple events during follow-up) across cardiovascular lipid trials. This signature will be optimized in human cohorts and atherosclerosis-prone mouse models and validated in a second subset of patients. Finally, the signature shall be translated in an imaging-based OCT- (optical coherence tomography) trial longitudinally assessing the progress of coronary atherosclerosis in subjects with CHD.