The Controversy over Maltby’s Hong Kong Dispatch

The recent release of the full text of Major-General CM. Maltby’s Official Dispatch as the General Officer Commanding at Hong Kong (Public Record Office WO 106/240113) prompted British and Canadian newspapers to run sensational stories quoting Maltby’s criticisms of the discipline and battlefield performance of the Canadian battalions. Maltby’s statements, which were censored when the Dispatch was initially released, require a detailed examination and will be discussed in a future issue of CMH. In addition, the Spring 1994 issue will carry an article by Paul Dickson on “Crerar and the Decision to Garrison Hong Kong.” For the present we are publishing an exchange of correspondence, dated January 1948, between Lieutenant-Colonel G.W.L. Nicholson, then Deputy Director of the Army Historical Section, and Brigadier John H. Price who was second-in-command of the Royal Rifles of Canada in Hong Kong. Brigadier Price was asked to comment, not on the censored Dispatch, but on extracts from a draft report prepared by the Historical Section of the British Cabinet Office. This report contained the substance of the most serious charges Maltby made about the conduct of the Royal Rifles. For the information of the reader, other officers mentioned in the exchange include Brigadier C. Wallis, Indian Army, commander of the East Brigade (to which the Royal Rifles belonged), Lieutenant-Colonel W.J. Home, commander of the Royal Rifles, Lieutenant-Colonel J.L.R. Sutcliffe, Commanding Officer, Winnipeg Grenadiers, Brigadier J.K. Lawson, Commanding Officer, “C” Force (as the Canadian contingent was known) and Colonel P. Hennessy, Lawson’s second-in-command

Privacy and Accountability in Black-Box Medicine

Black-box medicine—the use of big data and sophisticated machine learning techniques for health-care applications—could be the future of personalized medicine. Black-box medicine promises to make it easier to diagnose rare diseases and conditions, identify the most promising treatments, and allocate scarce resources among different patients. But to succeed, it must overcome two separate, but related, problems: patient privacy and algorithmic accountability. Privacy is a problem because researchers need access to huge amounts of patient health information to generate useful medical predictions. And accountability is a problem because black-box algorithms must be verified by outsiders to ensure they are accurate and unbiased, but this means giving outsiders access to this health information. This article examines the tension between the twin goals of privacy and accountability and develops a framework for balancing that tension. It proposes three pillars for an effective system of privacy-preserving accountability: substantive limitations on the collection, use, and disclosure of patient information; independent gatekeepers regulating information sharing between those developing and verifying black-box algorithms; and information-security requirements to prevent unintentional disclosures of patient information. The article examines and draws on a similar debate in the field of clinical trials, where disclosing information from past trials can lead to new treatments but also threatens patient privacy

Manufacturing Barriers to Biologics Competition and Innovation

As finding breakthrough small-molecule drugs gets harder, drug companies are increasingly turning to “large molecule” biologics. Although biologics represent many of the most promising new therapies for previously intractable diseases, they are extremely expensive. Moreover, the pathway for generic-type competition set up by Congress in 2010 is unlikely to yield significant cost savings. In this Article, we provide a fresh diagnosis of, and prescription for, this major public policy problem. We argue that the key cause is pervasive trade secrecy in the complex area of biologics manufacturing. Under the current regime, this trade secrecy, combined with certain features of FDA regulation, not only creates high barriers to entry of indefinite duration but also undermines efforts to advance fundamental knowledge. In sharp contrast, offering incentives for information disclosure to originator manufacturers would leverage the existing interaction of trade secrecy and the regulatory state in a positive direction. Although trade secrecy, particularly in complex areas like biologics manufacturing, often involves tacit knowledge that is difficult to codify and thus transfer, in this case regulatory requirements that originator manufacturers submit manufacturing details have already codified the relevant tacit knowledge. Incentivizing disclosure of these regulatory submissions would not only spur competition but it would provide a rich source of information upon which additional research, including fundamental research into the science of manufacturing, could build. In addition to provide fresh diagnosis and prescription in the specific area of biologics, the Article contributes to more general scholarship on trade secrecy and tacit knowledge. Prior scholarship has neglected the extent to which regulation can turn tacit knowledge not only into codified knowledge but into precisely the type of codified knowledge that is most likely to be useful and accurate. The Article also draws a link to the literature on adaptive regulation, arguing that greater regulatory flexibility is necessary and that more fundamental knowledge should spur flexibility. A vastly shortened version of the central argument that manufacturing trade secrecy hampers biosimilar development was published at 348 Science 188 (2015), available online

Nudging the FDA

[Excerpt] The FDA’s regulation of drugs is frequently the subject of policy debate, with arguments falling into two camps. On the one hand, a libertarian view of patients and the health care system holds high the value of consumer choice. Patients should get all the information and the drugs they want; the FDA should do what it can to enforce some basic standards but should otherwise get out of the way. On the other hand, a paternalist view values the FDA’s role as an expert agency standing between patients and a set of potentially dangerous drugs and potentially unscrupulous or at least insufficiently careful drug companies. We lay out here some of the ways the FDA regulates drugs, including some normally left out of the debate, and suggest a middle ground between libertarian and paternalistic approaches focused on correcting information asymmetry and aligning incentives.

Problems of Innovation-Deficient Pharmaceutical Manufacturing

Physicians are usually focused on which drug to prescribe, but recent developments suggest that they should be looking at something they have long taken for granted: that their chosen drug is available, high quality, and free from contamination. Unfortunately, the pharmaceutical industry has for decades lagged behind other industries, such as consumer goods, electronics, and food, in developing modern manufacturing processes, and today their processes are expensive, inefficient, and riddled with problems. This innovation deficiency has major negative impacts for patients, providers, the pharmaceutical industry, and the health care system as a whole. It also creates significant opportunities for firms willing to address technical and regulatory hurdles, although large-scale change will most likely demand legal and regulatory solutions

Am I My Son? Human Clones and the Modern Family

As increasingly complex assisted reproductive technologies (ART) become available, legal and social conceptions of family become ambiguous and sometimes misaligned. The as-yet unrealized technology of cloning provides the clearest example of this confusion: is the legal parent of a clone the individual cloned, or are that individual‘s parents also the parents of the clone? These issues have been generally obscured by the debates around the deployment of ART, especially cloning; far less consideration has been given to the way these new technologies impact the way we think about and develop law on the relationships between genetic, social, gestational, and legal parenthood. This article considers these issues in depth, looking at competing common-law frameworks for determining parentage, the statutory framework of parentage, and deeper theoretical concerns underlying the area. The article concludes that an intent-based framework, with at least some external limitations, most accurately matches law to social views of parents using new forms of ART

Trust, Trustworthiness, and Misinformation Shared by the Government

Where does trusted information come from? In a world of misinformation, where everyone is skeptical of everything, at least we can rely on expert, authoritative government agencies like the Environmental Protection Agency, the Centers for Disease Control, the Patent Office, and the Food and Drug Administration, right? Right

Grants

Innovation is a primary source of economic growth and is accordingly the target of substantial academic and government attention. Grants are a key tool in the government’s arsenal to promote innovation, but legal academic studies of that arsenal have given them short shrift. Although patents, prizes, and regulator-enforced exclusivity are each the subject of substantial literature, grants are typically addressed briefly, if at all. According to the conventional story, grants may be the only feasible tool to drive basic research, as opposed to applied research, but they are a blunt tool for that task. Three critiques of grants underlie this narrative: grants are allocated by government bureaucrats who lack much of the relevant information for optimal decision-making; grants are purely ex ante funding mechanisms and therefore lack accountability; and grants misallocate risk by saddling the government all the downside risk and giving the innovator all the upside. These critiques are largely wrong. Focusing on grants awarded by the National Institutes of Health (NIH), the largest public funder of biomedical research, this Article delves deeply into how grants actually work. It shows that—at least at the NIH—grants are awarded not by uninformed bureaucrats, but by panels of knowledgeable peer scientists with the benefit of extensive disclosures from applicants. It finds that grants provide accountability through repeated interactions over time. And it argues that the upside of grant-investments to the government is much greater than the lack of direct profits would suggest. Grants also have two marked comparative strengths as innovation levers: they can support innovation where social value exceeds appropriable market value, and they can directly support innovation enablers—the people, institutions, processes, and infrastructure that shape and generate innovation. Where markets undervalue some socially important innovations, like cures for diseases of the poor, grants can help. Grants can also enable innovation by supporting its inputs: young or exceptional scientists, new institutions, research networks, and large datasets. Taken as a whole, grants do not form a monolithic, blunt innovation lever; instead, they provide a varied and nuanced set of policy options. Innovation scholars and policymakers should recognize and develop the usefulness of grants in promoting major social goals

Describing Black-Box Medicine

Personalized medicine is a touchstone of modern medical science, and is increasingly addressed in the legal literature. In personalized medicine, treatments are chosen and tailored based on the characteristics of the individual patient. However, personalized medicine today is largely limited to those relatively simple relationships that can be explicitly characterized and validated through the scientific process and through clinical trial

Risks and Remedies for Artificial Intelligence in Healthcare

Artificial intelligence (AI) is rapidly entering health care and serving major roles, from automating drudgery and routine tasks in medical practice to managing patients and medical resources. As developers create AI systems to take on these tasks, several risks and challenges emerge, including the risk of injuries to patients from AI system errors, the risk to patient privacy of data acquisition and AI inference, and more. Potential solutions are complex but involve investment in infrastructure for high-quality, representative data; collaborative oversight by both the Food and Drug Administration and other health-care actors; and changes to medical education that will prepare providers for shifting roles in an evolving system