Law Commons^™

Biobanks As Innovation Infrastructure For Translational Medicine, W. Nicholson Price Ii

Book Chapters

Biobanks represent an opportunity for the use of big data to drive translational medicine. Precision medicine demands data to shape treatments to individual patient characteristics; large datasets can also suggest new uses for old drugs or relationships between previously unlinked conditions. But these tasks can be stymied when data are siloed in different datasets, smaller biobanks, or completely proprietary private resources. This hampers not only analysis of the data themselves, but also efforts to translate data-based insights into actionable recommendations and to transfer the discovered technology into a commercialization pipeline. Cross-project technological innovation, development, and validation are all more difficult …

Privacy In The Age Of Medical Big Data, W. Nicholson Price Ii, I. Glenn Cohen

Articles

Big data has become the ubiquitous watch word of medical innovation. The rapid development of machine-learning techniques and artificial intelligence in particular has promised to revolutionize medical practice from the allocation of resources to the diagnosis of complex diseases. But with big data comes big risks and challenges, among them significant questions about patient privacy. Here, we outline the legal and ethical challenges big data brings to patient privacy. We discuss, among other topics, how best to conceive of health privacy; the importance of equity, consent, and patient governance in data collection; discrimination in data uses; and how to handle …

Outcome Prediction In The Practice Of Law, Mark K. Osbeck, Michael Gilliland

Articles

Business forecasters typically use time-series models to predict future demands, the forecasts informing management decision making and guiding organizational planning. But this type of forecasting is merely a subset of the broader field of predictive analytics, models used by data scientists in all manner of applications, including credit approvals, fraud detection, product-purchase and music-listening recommendations, and even the real-time decisions made by self-driving vehicles. The practice of law requires decisions that must be based on predictions of future legal outcomes, and data scientists are now developing forecasting methods to support the process. In this article, Mark Osbeck and Mike Gilliland …

Big Data In Finance: Highlights From The Big Data In Finance Conference Hosted At The University Of Michigan October 27-28, 2016, Michael S. Barr, Brian Koziara, Mark D. Flood, Alfred Hero, H. V. Jagadish

Law & Economics Working Papers

How can financial data be made more accessible and more secure, as well as more useful to regulators, market participants, and the public? As new data sets are created, opportunities emerge. Vast quantities of financial data may help identify emerging risks, enable market participants and regulators to see and better understand financial networks and interconnections, enhance financial stability, bolster consumer protection, and increase access to the underserved. Data can also increase transparency in the financial system for market participants, regulators and the public. These data sets, however, can raise significant questions about security and privacy; ensuring data quality; protecting against …

Medical Malpractice And Black-Box Medicine, W. Nicholson Price Ii

Book Chapters

The explosive proliferation of health data has combined with the rapid development of machine-learning algorithms to enable a new form of medicine: “black-box medicine.” In this phenomenon, algorithms troll through tremendous databases of health data to find patterns that can be used to guide care, whether by predicting unknown patient risks, selecting the right drug, suggesting a new use of an old drug, or triaging patients to preserve health resources. These decisions differ from previous data-based decisions because black-box medicine is, by its nature, opaque; that is, the bases for black-box decisions are unknown and unknowable.

Black-box medicine raises a …

Big Data, Patents, And The Future Of Medicine, W. Nicholson Price Ii

Articles

Big data has tremendous potential to improve health care. Unfortunately, intellectual property law isn’t ready to support that leap. In the next wave of data- driven medicine, black-box medicine, researchers use sophisticated algorithms to examine huge troves of health data, finding complex, implicit relationships and making individualized assessments for patients. Black-box medicine offers potentially immense benefits, but also requires substantial high investment. Firms must develop new datasets, models, and validations, which are all nonrivalrous information goods with significant spillovers, requiring incentives for welfare-optimizing investment. Current intellectual property law fails to provide adequate incentives for black- box medicine. The Supreme Court …