In recent years, the usage of high-throughput technologies in the fields of genomics, transcriptomics, proteomics and metabolomics for biomarker discovery has expanded enormously. Biomarkers can be applied for many purposes, including diagnosis, prognosis, staging and selecting appropriate patient therapy. In addition, biomarkers can provide information on disease mechanism or progression. Biomarker development for clinical application encompasses phases for their discovery and characterization, assay development and, finally, implementation using automated platforms employed in clinical laboratories. However, translation from bench to bedside outside a research-oriented environment has proven to be more difficult. This is reflected by only few new biomarkers being integrated into clinical application in the last years. This article reviews currently used high-throughput technologies for the identification of biomarkers, as well as present approaches to increase the percentage of biomarkers that pass the barriers for clinical application.