The inability of pre-clinical studies to predict clinical efficacy is a major bottleneck in drug development. In severe asthma this bottleneck results from: a lack of useful and validated biomarkers, underperforming pre-clinical models, inadequate and incomplete sub-phenotyping, and insufficient disease understanding. The use of biomarker profiles comprised of various types of high-dimensional data, integrated with an innovative systems biology approach into distinct phenotype handprints, will enable significantly better prediction of therapeutic efficacy than single or even clustered biomarkers of one data type and will identify novel targets.