Genomics has profoundly changed biology by scaling data acquisition, which has provided researchers with the opportunity to interrogate biology in novel and creative ways. No longer constrained by low-throughput assays, researchers have developed hypothesis-generating approaches to understand the molecular basis of nature-both normal and pathological. The paradigm of hypothesis-generating research does not replace or undermine hypothesis-testing modes of research; instead, it complements them and has facilitated discoveries that may not have been possible with hypothesistesting research. The hypothesis-generating mode of research has been primarily practiced in basic science but has recently been extended to clinical-translational work as well. Just as in basic science, this approach to research can facilitate insights into human health and disease mechanisms and provide the crucially needed data set of the full spectrum of genotype-phenotype correlations. Finally, the paradigm of hypothesis-generating research is conceptually similar to the underpinning of predictive genomic medicine, which has the potential to shift medicine from a primarily population-or cohort-based activity to one that instead uses individual susceptibility, prognostic, and pharmacogenetic profiles to maximize the efficacy and minimize the iatrogenic effects of medical interventions.The goal of this article is to describe how recent technological changes provide opportunities to undertake novel approaches to biomedical research and to practice genomic preventive medicine. Massively parallel sequencing is the primary technology that will be addressed here (Mardis 2008), but the principles apply to many other technologies, such as proteomics, metabolomics, transcriptomics, etc. Readers of this journal are well aware of the precipitous fall of sequencing costs over the last several decades. The consequence of this fall is that we are no longer in a scientific and medical world where the throughput (and the costs) of testing is the key limiting factor around which these enterprises are organized. Once one is released from this limiting factor, one may ask whether these enterprises should be reorganized. Here I outline the principles of how these enterprises are organized, show how highthroughput biology can allow alternative organizations of these enterprises to be considered, and show how biology and medicine are in many ways similar. The discussion includes three categories of enterprises: basic research, clinical research, and medical practice.