Healthcare is becoming more proactive and data-rich than anything before possible – and will increasingly focus on maintaining and enhancing wellness more than just reacting to disease. Lee Hood and I have recently launched a large-scale data-rich wellness project that integrates genomics, proteomics, metabolomics, microbiomes, clinical chemistries and wearable devices of the quantified self to monitor wellness and disease. The resulting dense, dynamic personal data clouds enable the creation of a field we term Scientific Wellness that aims to help individuals take informed actions to enhance their wellness and help reduce their risk for disease. Analyses of these data — individually and in aggregate — will enable us to identify scientifically-validated metrics for wellness, see early warning signs of disease, and develop approaches to reverse disease in its early stages (such as can currently be done for e.g. pre-diabetes). I will present results from our proof-of-concept pilot study in a set of 108 individuals (the Pioneer 100 study), showing how the interpretation of these data led to actionable findings for individuals to improve health and reduce risk drivers of disease — and well as give big picture views of how this endeavor relates to the future of health.