title: The ethics of translating high-throughput science into clinical practice.
abstract: Biomedical research is increasingly data intensive and computational, and "big data science" is migrating into the clinical arena. Unfortunately, ethicists, regulators, and policy-makers have barely begun to explore the ethical, legal, and social issues raised by the variety of analytical and computational approaches in use and under development in biology and medicine. Most scholarship concerning big data bioscience has focused on privacy, a vitally important consideration but not the only one. Among the issues raised by new computational technologies are questions about safety and safety assessment, justice, and how to obtain proper informed consent. These technologies also raise a myriad of regulatory issues that could influence the probability of translating new assays or computational tools to the clinical or public health spheres.
authors.forename: Pilar N
authors.initials: PN
authors.lastname: Ossorio
mesh_terms: D035843:Biomedical Research / Q000941:ethics* / Q000458:organization & administration*; D003219:Confidentiality; D004059:Diffusion of Innovation; D005819:Genetic Markers / Q000941:ethics; D006801:Humans; D007258:Informed Consent
chemical_list: D005819:Genetic Markers