The pharmaceutical industry is in a state of fundamental transition. New drug approvals have slowed, patents on blockbuster drugs are expiring, and costs associated with developing new drugs are escalating and yielding fewer viable drug candidates. As a result, pharmaceutical firms have turned to a number of alternative strategies for growth. One of these strategies is “drug repurposing”—finding new ways to deploy approved drugs or abandoned clinical candidates in new disease areas. Despite the efficiency advantages of repurposing drugs, there is broad agreement that there is insufficient repurposing activity because of numerous intellectual property protection and market failures. This Article examines the system that surrounds drug repurposing, including serendipitous discovery, the application of “big data” methods to prioritize promising repurposing candidates, the unorthodoxly regulated off-label prescription practices of providers, and related prohibitions on pharmaceutical firms’ off-label marketing. The Article argues that there is a complex ecosystem in place and that additional or disruptive IP or market exclusivity incentives may harm as much as help in promoting repurposing activity. To illustrate this threat, the Article traces the trajectory of metformin, a common diabetes drug that shows promise for conditions ranging from polycystic ovary syndrome to breast cancer. From the initial reasons for Bristol-Myers Squibb to refuse to invest in promising alternative uses, to the institutions, researchers, and regulators who identified possibilities for metformin treatment, this Article aims to map the role of intellectual property protection, market exclusivity, and search for capital that led to metformin’s ascent as a repurposed drug. The Article contributes a concrete understanding to an important problem in pharmaceutical law and policy, one for which scholars have quickly suggested more powerful patent and market exclusivity protection when doing so may undermine the very processes now leading to effective alternative uses for existing drugs.
The First Amendment’s prohibition on prior restraints on speech is generally understood to be near-absolute. The doctrine permits prior restraints in only a handful of circumstances, and tends to require compelling evidence of their necessity. The focus of this Article is the source of an unexpected but important challenge to this doctrine: government surveillance in the digital age. Recent litigation about the constitutionality of the Stored Communications Act (SCA) highlights that challenge. The SCA authorizes the government both to obtain a person’s stored internet communications from a service provider and to seek a gag order preventing the provider from even notifying the person of that fact. Though the government did not ultimately prevail in the litigation, the case provides a renewed opportunity to consider the tension between prior restraint doctrine and the government’s digital surveillance efforts.
As artificial intelligence and big data analytics increasingly replace human decision making, questions about algorithmic ethics become more pressing. Many are concerned that an algorithmic society is too opaque to be accountable for its behavior. We set out to test the limits of transparency around governmental deployment of big data analytics, contributing to the literature on algorithmic accountability with a thorough study of the opacity of governmental predictive algorithms. Using open records processes, we focused our investigation on local and state government deployment of predictive algorithms.
This Article explores the implications for medical care of a debate that is more familiar in the law and ethics of human subjects research: whether people should be paid to receive or decline medical interventions, or to reach certain health objectives. It examines the legal and ethical issues such payments raise, and considers various actors who might make such payments, including governments, employers, insurers, care providers, and private parties. It argues for two interrelated conclusions: first, that these payments should not be subject to blanket normative condemnation, and, second, that payments made in different settings and contexts frequently share underlying commonalities, which suggests categorizing them according to these commonalities. We should move from a “siloed” legal and normative landscape, where discussions of payments to patients in one context are isolated from similar discussions in other contexts, to a landscape where payments are evaluated and categorized more systematically. The categories along which payments should be evaluated include who the payer is, what purpose the payment serves, and who the payment affects.