We analyze key proteomic issues and cutting-edge technologies that will spearhead inroads into functional interpretations of human diseases and their therapeutic rectification, following the availability of the predicted human proteome. We contrast the distinctions between high quality data that are low throughput, (e.g., 3-D proteomic reconstructions in embryogenic and nervous system contexts, and multigenerational transgenic studies), versus automated data harvesting that is more distant from human disease phenotypes and currently fulfills a diagnostic role, (e.g., molecular portraits of human diseases via transcriptomic analyses). We examine the extent to which these approaches impinge upon a realistic understanding of human diseases, namely how close they come to revealing the causal events involved in the initiation of disease. While tissue sources from human embryogenesis, foetal development and the brain remain the absolute priority, the pragmatic approaches utilize judicious data integration from selected proteomic studies of model organisms. The role of genome-wide disease-related screens, "humanized" transgenic analyses, multigenerational gene interference methods, and analyses of post-translational modifications in epigenetic contexts from Drosophila will be crucial, since these avenues are far too slow and transgenically cumbersome in mammals. Finally, the implementation of multi compartment electrolyzers (MCE) and multi photon detection (MPD) systems will be pivotal for the proteomic profiling of human tissue samples.