Defining The Balance Of Risk And Benefit In The Era Of Genomics And Proteomics

Abstract
The ability to measure the function of genes and proteins has spawned the construct of personalized medicine, in which patients’ own risks and preferences are used to choose diagnostic and therapeutic strategies. The complexity of clinical data required to guide personalized medicine calls for improvements in our system of clinical research, including (1) overhauling it to produce networks that can do adequate-size pragmatic trials; (2) synchronization of regulatory and payment systems to encourage adequate studies; and (3) an investment in education of providers and patients to improve the understanding of the probabilistic predictions forming the basis of personalized medicine.