Contemporary clinical trials disregard the massive changes that may occur within an individual’s state of aggregation due to lifestyle including nutrition, environmental factors, subclinical infections etc. I.e. intra-individual variations may confound detection of minute changes indicative of disease development and drug response due to massive background noise. In addition, individual molecular phenotypes of disease may vary greatly despite similar symptoms of a given disease. I.e. most drugs work in limited subgroups which is indicative of molecular pathology driving disease. While these phenomena have found entrée in clinical trial design in cancer, where WGS Sequencing drives treatment decision as well as R&D, there is still uncertainty how next generation clinical trials should look for chronic debilitation non communicable diseases. We propose a new longitudinal, multi-omics and real-world data based approach, where an individual becomes his own control. Clinical response will be corroborated by closely monitoring personal omics profiles (PMP) and other appropriate technologies (imaging, sensors etc.), which will be analyzed with machine learning to identify responders early in the course of a treatment cycle.