Faculty Bibliography
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Congressional and presidential records reveal a consistent pattern of political intercession with the regulatory authority of the Food and Drug Administration (FDA) over the approval and labeling of mifepristone (RU-486). This pattern is unlikely to abate any time soon. It is against this backdrop that we examine herein the ongoing legislative and legal disputes over mifepristone at a point in time which is just beyond the 20th anniversary of its approval by the FDA “for the medical termination of intrauterine pregnancy.”
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For a third year in a row, we followed up with authors of several recent Comments and Perspectives in Nature Machine Intelligence about what happened after their article was published: how did the topic they wrote about develop, did they gain new insights, and what are their hopes and expectations for AI in 2022?
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Regulators have been more permissive for medical devices compared to their drug and biologic counterparts. While innovative products can thereby reach consumers more quickly, this approach raises serious public health and safety concerns. Additionally, the nature of medical devices is rapidly changing, as software has become as important as hardware. Regulation must keep pace with the current developments and controversies of this technology. This volume provides a multidisciplinary evaluation of the ethical, legal, and regulatory concerns surrounding medical devices in the US and EU. For medical providers, policymakers, and other stakeholders, the book offers a framework for the opportunities and challenges on the horizon for medical device regulation. Readers will gain a nuanced overview of the latest developments in patient privacy and safety, innovation, and new regulatory laws. This book is also available as Open Access on Cambridge Core.
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On January 3, 2019, U.S. District Judge Theodore D. Chuang of the U.S. District Court of the District of Maryland took a crucial first step in redressing one of the worst human subjects research ethics violations in U.S. history.
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Psychedelics have shown great promise in treating mental-health conditions, but their use is severely limited by legal obstacles, which could be overcome.
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For the average person, genetic testing has two very different faces. The rise of genetic testing is often promoted as the democratization of genetics by enabling individuals to gain insights into their unique makeup. At the same time, many have raised concerns that genetic testing and sequencing reveal intensely personal and private information. As these technologies become increasingly available as consumer products, the ethical, legal, and regulatory challenges presented by genomics are ever looming. Assembling multidisciplinary experts, this volume evaluates the different models used to deliver consumer genetics and considers a number of key questions: How should we mediate privacy and other ethical concerns around genetic databases? Does aggregating data from genetic testing turn people into products by commercializing their data? How might this data reduce or exacerbate existing healthcare disparities? Contributing authors also provide guidance on protecting consumer privacy and safety while promoting innovation.
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A judge’s framing of the controversy as a free-speech issue fits a troubling pattern.
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It is an exciting time to be in reproductive health research. Building on decades of research and new technologies, the opportunities for human reproductive medicine have never been greater. However, reproductive health is a field with additional debates that go beyond research and medicine. To complement the scientific articles in this special issue, Trends in Molecular Medicine discussed ethical questions and societal implications with Eli Y. Adashi, Professor of Medical Science at Brown University (left), and I. Glenn Cohen, Professor of Law at Harvard Law School (right), and talked about the challenges and opportunities that lie ahead for reproductive health research and medicine.
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Diagnostic mobile medical apps call for increased regulatory intervention, even if they do not dispense advice or treatment.
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The existing liability system in the United States and other countries can’t handle the risks relation to AI. That’s a problem because it will slow AI innovation and adoption. The answer is to revamp the system, which involves revising standards of care, changing who compensates parties when inevitable accidents occur via insurance and indemnity; changing default liability options; creating new adjudicators; and revamping regulations to prevent mistakes and exempt certain kinds of liability.
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This essay discusses the new report, Heritable Human Genome Editing, by the National Academy of Medicine, the National Academy of Sciences, and the Royal Society. After summarizing the report, we argue that the report takes four quite bold steps away from prior reports, namely (1) rejecting an omnibus approach to heritable human genome editing (HHGE) in favor of a case-by-case analysis of possible uses of HHGE, accepting that HHGE is acceptable in some cases; (2) recognizing that the interest in having children who are genetically related to both would-be rearing parents is one that the regulation of HHGE should honor; (3) patterning a regulatory model for HHGE on the United Kingdom's approach to regulating mitochondrial replacement techniques; and (4) conveying skepticism that international regulation is possible while showing a strong preference for a default into national regulatory regimes for HHGE.
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Direct-to-consumer medical artificial intelligence/machine learning applications are increasingly used for a variety of diagnostic assessments, and the emphasis on telemedicine and home healthcare during the COVID-19 pandemic may further stimulate their adoption. In this Perspective, we argue that the artificial intelligence/machine learning regulatory landscape should operate differently when a system is designed for clinicians/doctors as opposed to when it is designed for personal use. Direct-to-consumer applications raise unique concerns due to the nature of consumer users, who tend to be limited in their statistical and medical literacy and risk averse about their health outcomes. This creates an environment where false alarms can proliferate and burden public healthcare systems and medical insurers. While similar situations exist elsewhere in medicine, the ease and frequency with which artificial intelligence/machine learning apps can be used, and their increasing prevalence in the consumer market, calls for careful reflection on how to effectively regulate them. We suggest regulators should strive to better understand how consumers interact with direct-to-consumer medical artificial intelligence/machine learning apps, particularly diagnostic ones, and this requires more than a focus on the system’s technical specifications. We further argue that the best regulatory review would also consider such technologies’ social costs under widespread use.
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We take two professions — police officers and doctors — and place their experiences with big data in dialogue. Policing and medicine, while naturally different in some obvious respects, actually both need to grapple with a lot of the same moral, social, and legal questions that come with adopting big data programs. This because, as we discuss below, both professions generally possess a monopoly over an acute societal vulnerability, be it safety or health, and have accordingly developed a set of settled internal norms to shape individual discretion in service of each respective function. We place the professions side-by-side and try to distill certain insights from the perspective of three key stakeholders — practitioners, policymakers, and the polity.
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The current SARS-CoV-2 pandemic has killed thousands across the world. SARS-CoV-2 is the latest but surely not the last such global pandemic we will face. The biomedical response to such pandemics includes treatment, vaccination, and so on. In this paper, though, we argue that it is time to consider an additional strategy: the somatic (non-heritable) enhancement of human immunity. We argue for this approach and consider bioethics objections we believe can be overcome.
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To tackle the challenge of how to distribute organs, vaccines, and other kinds of health care, organizations are relying on AI and analytics. But many of them treat ethical considerations as an afterthought. This is a mistake. Such factors should be taken into the account at the outset of the effort to create the AI algorithm or analytics model.
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In the view of many, heritable human genome editing (HHGE) harbors the remedial potential of ridding the world of deadly genetic diseases. A Hippocratic obligation, if there ever was one, HHGE is widely viewed as a life-sustaining proposition. The national go/no-go decision regarding the implementation of HHGE, however, must not, in the collective view of the authors, proceed absent thorough public engagement. A comparable call for an “extensive societal dialogue” was recently issued by the International Commission on the Clinical Use of Human Germline Genome Editing. In this communication, the authors lay out the foundational principles undergirding the formation, modification, and evaluation of public opinion. It is against this backdrop that the societal decision to warrant or enjoin the clinical conduct of HHGE will doubtlessly transpire.
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Same-sex couples, not unlike their heterosexual counterparts, would prefer having a genetically related child.However, assisted same-sex human reproduction has heretofore been deemed infeasible absent haploid cellularanalogs of human gametes. Recent developments, however, may have overcome this limitation through thederivation of haploid embryonic stem cells (hapESCs). Undifferentiated, pluripotent, self-renewing, and stablyhaploid, hESCs have also displayed germline competence. It is in this capacity that murine hESCs, doubling upas de facto gametes, gave rise to bimaternal and bipaternal progeny. Herein we argue that assisted same-sexhuman reproduction, although potentially attainable at this time, is still years away from the clinic. In support ofthis perspective, we note the significant technical, regulatory, statutory, and societal hurdles that stand in theway of near-term implementation.