In a recent study, we created and analyzed a novel dataset of US biologics manufacturing patents held by nine leading firms that produce originator therapeutic proteins. Here, we expand our data and analysis to encompass not simply US patents but also their family members, with the total set constituting a substantially broader group of patents held internationally. Our wider focus allows us to compare firm strategies in the USA and other jurisdictions. We also contrast the strategies of US-based firms with those headquartered in Europe. Unlike prior comparative studies, which focus primarily on litigated patents, we assess a broader competitive landscape. Our analysis yields several findings. First, all nine firms accumulate many more biologics patents in the USA than in jurisdictions like Europe and Japan. They do so in part by accumulating large numbers of patents with claims of varying scope over a long time period within a given US family. Second, we show distinct patterns of patent accumulation based on firm type. US-based firms with origins in biologics research and development (R&D) that continue to have internally focused R&D efforts dominate patent accumulation not only in the USA but also in Europe and Japan. In contrast, firms that make small molecules in addition to biologics secure fewer patents, regardless of their location. As a detailed illustration of patent practice, we provide a case study of Regeneron's Eylea. Overall, our findings indicate a substantial notice challenge for biosimilar entry and provide support for reform that increases transparency and information flow regarding biologics patents generally, and manufacturing process patents specifically. Our results also support mechanisms for reducing the anti-competitive impact of large patent families, such as limitations on the number of late-filed patents within a family that can be asserted against biosimilar firms.
Large language models (LLMs) such as Claude and ChatGPT are the most powerful artificial intelligence (AI) systems ever created, and they are being used to diagnose and treat patients. But LLMs have been shown to be unreliable, unpredictable, and unsafe on occasion. New AI guidelines recommend hundreds of standards, such as 'transparency', 'trustworthiness', and 'safety'. But there is deep uncertainty whether these are sufficient. The literature focuses mostly on which standards best suit AI models, not on how to transmute standards into law. This article does that by considering AI guidelines as a starting point, then evaluating whether existing frameworks for ensuring quality in medicine might form the basis for AI governance. Along the way, the article identifies emerging areas of consensus, lingering questions, and lessons from other areas of law. This article suggests that we should not only treat LLMs like nascent medical professionals who must meet minimum standards of competence and responsibility, but also subject them to measurable, product-like standards of safety and performance. When paired with reimbursement incentives and legal liability, LLMs will be treated on par with others who diagnose and treat US patients. This article offers a path to genuine oversight of LLMs in medicine.
Large language models (LLMs) such as Claude and ChatGPT are the most powerful artificial intelligence (AI) systems ever created, and they are being used to diagnose and treat patients. But LLMs have been shown to be unreliable, unpredictable, and unsafe on occasion. New AI guidelines recommend hundreds of standards, such as 'transparency', 'trustworthiness', and 'safety'. But there is deep uncertainty whether these are sufficient. The literature focuses mostly on which standards best suit AI models, not on how to transmute standards into law. This article does that by considering AI guidelines as a starting point, then evaluating whether existing frameworks for ensuring quality in medicine might form the basis for AI governance. Along the way, the article identifies emerging areas of consensus, lingering questions, and lessons from other areas of law. This article suggests that we should not only treat LLMs like nascent medical professionals who must meet minimum standards of competence and responsibility, but also subject them to measurable, product-like standards of safety and performance. When paired with reimbursement incentives and legal liability, LLMs will be treated on par with others who diagnose and treat US patients. This article offers a path to genuine oversight of LLMs in medicine.
This article explores the legal, social, and ethical challenges faced by intersex individuals in China, a population estimated to number in the millions but still largely invisible in national laws and public discourse. Drawing on recent international human rights developments and comparative legal analysis, the paper critically examines China's legal and medical frameworks through the lens of intersex rights. It highlights how entrenched binary conceptions of sex and gender deeply rooted in Confucian traditions, and reflected in Chinese administrative, medical, and legal systems, lead to widespread discrimination, non-consensual medical interventions, and structural exclusion of intersex individuals. The authors argue that despite generic constitutional and civil guarantees of equality, bodily integrity, and informed consent, intersex persons remain insufficiently protected due to the absence of targeted legislation and interpretive guidance. The article proposes incremental yet concrete reforms such as deferring non-urgent medical interventions, improving psychosocial support, introducing neutral terminology, and developing best-practice medical guidelines as viable steps toward greater inclusion. By examining relevant international and regional practices, including developments in Malta, Australia, and Hong Kong, the paper advocates for a post-binary legal approach that affirms intersex individuals' dignity, autonomy, and right to recognition in Chinese law and society.
Genetic discrimination (GD) involves an individual or a group being negatively treated, unfairly profiled, or harmed, relative to the rest of the population, because of genetic characteristics. Research has examined GD mainly in insurance and employment, with growing attention to immigration, finance, forensics, and education. China, as a major biotechnology actor, has expanded genetic testing and supported rapid growth in gene-sequencing enterprises. These developments have also heightened concerns about GD, particularly in employment contexts. Since 2009, five employment-related GD cases have been reported in China. Two proceeded through judicial processes, while three became discussed social incidents. These cases share several features: all involved individuals carrying thalassemia-related gene mutations; all occurred in southern China, where populations exhibit genetic adaptations to hot, humid climates; and none reached a satisfactory resolution. Notably, all incidents arose within public-sector or quasi-governmental institutions that operate as extensions of state governance. China's legal framework contains significant gaps in addressing employment-related GD, creating risks of systemic exclusion for individuals with certain genetic traits. Because these cases occurred in the public sector, such exclusion restricts political representation. We recommend reviewing sector-specific labor and administrative regulations, classifying genetic information as sensitive personal data, and strengthening mechanisms to ensure employment opportunities.
The SNP Consortium ('TSC') was a nonprofit research collaboration formed in 1999 to identify, map, and publicly release human genomic markers known as 'single nucleotide polymorphisms' (SNPs). The project was funded by a group of pharmaceutical, biotechnology, and information technology companies, together with the Wellcome Trust, which collectively contributed $53 million to the project. TSC was the rare scientific undertaking that completed its work ahead of schedule, under budget, and with far more results than planned. This essay describes TSC, its background, legal structure, and novel 'protective' patent strategy, which have served as models for later research collaborations in a range of scientific fields.
This study examines the complex and often ambiguous conceptualization of consent in European health research, focusing on the relationship between informed consent to participate in research and consent as a legal basis for personal data processing. Differences between these two forms of consent may lead to inconsistent procedures and requirements, thereby generating legal and practical challenges for researchers, ethics committees, data protection authorities, and other oversight bodies. Drawing on two use cases involving observational retrospective studies, the paper compares consent requirements and oversight practices in Belgium, the Czech Republic, Finland, France, Germany, Italy, Poland, and Spain, highlighting persistent fragmentation and uneven institutional coordination across national research governance systems. The paper also distinguishes between 'monist' conceptions of consent, which view research and data protection consent as expressions of a single normative concept, and 'dualist' conceptions, which treat them as distinct forms of authorization grounded in different ethical and legal rationales. The paper concludes by reflecting on the implications of the upcoming European Health Data Space Regulation, arguing that its approach to secondary data use may further accentuate existing tensions and highlighting the need for greater conceptual clarity and institutional coordination in European health research governance.
The Genetic Information Nondiscrimination Act (GINA) became law almost two decades ago, when genomic medicine was still in its infancy. One reason for its passage was to ensure that individuals and society would reap the benefits of emerging advances in genetic medicine, and would be able to benefit from genetic testing and research without fear of employment or health insurance discrimination. Since then, genomics has matured into a complex probabilistic science that increasingly allows for individualized estimates of genetic risk derived from large-scale population studies. Polygenic risk scores (PGSs), which provide genome-wide estimates of disease liability and may help indicate effective preventive care for an individual, raise new benefits but also concerns. PGS testing may become common in clinical practice, particularly to mitigate common complex diseases such as cardiac conditions and cancer. But are existing antidiscrimination protections adequate for a world where polygenic risk scoring is the norm? In this paper, we consider how existing laws apply and whether new legal and policy approaches are needed to support widespread, beneficial clinical use of PGSs. We also propose avenues for potential action by policymakers.
Whether life insurers should be able to consider genetic information during underwriting is a long-standing debate often characterized by strong opinions on both sides. Insurers push for full access to applicants' genetic information, and consumer advocates often call for a ban on insurer use of the information. Both sides employ concepts of fairness and discrimination in supporting their position. This article considers the concept of actuarial fairness, where individuals are expected to pay for the risks they bring to an insurance pool. Currently, law and policy adopting this standard most often take a deferential approach, allowing insurers to utilize genetic information with wide latitude. This article takes seriously a middle-ground approach, broadly labeled as actuarial utility. Building from prior literature examining this issue, this article proposes a framework US policy can adopt to assist in the assessment of the actuarial utility of genetic information with a particular focus on emerging genetic technologies.
The convergence of neurotechnologies and disability raises urgent questions about autonomy, mental integrity, and legal capacity for persons with disabilities. This article examines the human rights implications of emerging neurotechnologies-from brain-computer interfaces to cognitive monitoring tools-through the lens of the United Nations Convention on the Rights of Persons with Disabilities (CRPD). Drawing on historical abuses under the medical model of disability, it argues that the uncritical deployment of neurotechnologies risks replicating patterns of coercion, paternalism, and exclusion. By advancing a normative framework rooted in the CRPD and the social model of disability, the article proposes legal and ethical safeguards to protect mental privacy, ensure informed consent, and affirm supported decision-making. It calls for regulatory and design paradigms that shift from enhancement and correction to inclusion and empowerment. Ultimately, the article contends that disability rights must be at the center of neurotechnologies governance to prevent ableist harms and foster equitable innovation.
Genetic testing fraud schemes are widespread, impacting patients, healthcare providers, and the US government. Fueled by rapid innovations in genetic testing capabilities and expansion of telehealth services following the pandemic, fraudsters are thriving. The Department of Justice (DOJ) and the Department of Health and Human Services (HHS) enhanced scrutiny of such fraud schemes over a decade ago, and in September 2019, targeted enforcement began with the indictment of 35 individuals on allegations of genetic testing fraud activities totaling $2.1 billion (https://www.justice.gov/archives/opa/pr/federal-law-enforcement-action-involving-fraudulent-genetic-testing-results-charges-against). By the end of 2024, the DOJ and HHS had initiated hundreds of investigations, with litigation across multiple legal jurisdictions involving physicians, telemedicine companies, marketing companies, and genetic testing laboratories. This article investigates the nature and scope of genetic testing fraud and describes the concerted government activity to thwart the proliferation of these schemes. While the actual mechanisms to carry out genetic testing fraud, such as kickbacks and inappropriate coding, are not new, there are multiple characteristics that make this type of healthcare fraud distinctive. We describe three genetic testing features that make genetic testing fraud unique and heighten the potential for fraud on the government: widespread interest in test content; test complexity; and associated billing challenges. The article further contributes to the literature by assessing genetic testing fraud schemes and discussing implications for physicians and the healthcare system, including recommendations to prevent future genetic testing fraud.
An invisible wall separates the U.S. Food and Drug Administration (FDA) from the U.S. Patent and Trademark Office (PTO). This wall blocks inter-agency communication, depriving the PTO of information relevant to patent applications and depriving the FDA of information relevant to drug-approval applications. Consequently, it is too easy for a drug company to tell the PTO 'our drug is new' (in hopes of speeding a patent grant) while telling the FDA 'our drug is not new' (in hopes of speeding drug approval). Better communication between the FDA and PTO would increase agency accuracy by preventing inconsistent representations, and would increase agency efficiency by avoiding informational asymmetry and duplication of effort. Presidents Obama and Trump created enhanced mechanisms that allow the PTO to receive information from counterparts in foreign countries and from industry about what is truly innovative. It would also be helpful for the PTO to enjoy the expertise of its own sister agency, located down the road. Despite scholarly and governmental proposals to mandate cooperation between the FDA and the PTO, such coordination remains limited in practice. This article proposes to break through the invisible wall between the FDA and the PTO, and to open pathways for communication between the two agencies.
The rapid expansion of synthetic biology has transformed research and innovation but has also created profound biosecurity challenges. Synthetic nucleic acid (SNA) technologies, which allow genetic material to be synthetically created, enable scientific progress but also lower the barriers to constructing or enhancing dangerous pathogens. This article argues that the governance of SNA should be grounded in a transnational new governance approach that combines binding international obligations with harmonized technical standards. It assesses the fitness of current regimes-the International Health Regulations, the Biological Weapons Convention (BWC), UN Security Council Resolution (UNSCR) 1540, and national biosecurity laws-and finds that while these instruments already impose binding obligations to prevent misuse of biological agents, their terms remain outdated and their application fragmented. Most states lack explicit SNA order screening requirements, and voluntary private standards such as those of the International Gene Synthesis Consortium and ISO 20688-2 remain inadequate for managing this global risk. The article recommends modernizing international law by clarifying that existing treaties cover synthetic biology, developing harmonized global screening standards, and updating national legislation to mandate and incentivize SNA order screening. It further proposes leveraging market access and funding power to drive global practice. Ultimately, safeguarding innovation in the age of SNA requires aligning law to manage the risks of emerging biotechnologies.
In February 2024 the Alabama Supreme Court held that the destruction of frozen embryos stored at an in vitro fertilization (IVF) center could be the basis of a wrongful death suit by the prospective parents under Alabama law. The opinion caused a bipartisan uproar that led to its effective overturning by the Alabama legislature and governor 19 days after it was issued. The Alabama Supreme Court's unexpected intervention in IVF shows the surprising ways a mishap in a clinic can trigger a collision of originalist jurisprudence, judicial rhetoric, political mobilization, and media amplification in our post-Dobbs world. A closer look reminds us of how variable court systems and laws are across the USA, as well as the complex motivations of patients and others involved in assisted reproduction. It also shows how state court decisions, perhaps through intentional provocations, can reverberate in the national debate, leading to overreactions, some far beyond their jurisdictions' borders. Plus, in context, beyond the online quips, the political soundbites, and the media articles, it is a fascinating tale and all of that from a case that could easily have been decided, in either direction, as a low-key interpretation of a unique Alabama statute, without broad consequences.
Generative artificial intelligence (AI) now participates in tasks constitutive of invention-problem framing, hypothesis generation, and design-yet patent doctrine remains anchored to a natural-person rule that offers limited guidance for AI-intensive workflows. This Article advances augmented inventorship, a conservative but operationally modern attribution doctrine that preserves human inventorship while making AI's generative role legible and auditable at the moment of conception. Drawing on an analogy to augmented immunology, the framework identifies two design criteria-directability (independent and substantive human intellectual judgment steering model behavior or selection) and traceability (a reviewable, claim-centered record linking human reasons to claim elements)-and translates them into a proportionate evidentiary practice: a Computational Traceability Report and a Human-Machine Contribution Statement. These instruments are content-rich but code-light. They support enablement and sufficiency, clarify claim drafting and construction, reduce prosecution and litigation error costs, and balance evidentiary transparency with trade-secret sensitivity through proportional disclosure. Situated within-and distinguished from-the growing literature on AI inventorship and disclosure, the doctrine aligns with existing law (US conception and significant-contribution standards; the UK's 'actual deviser'; EPC sufficiency) and is compatible with TRIPS disclosure norms. Rather than demanding 'more disclosure' in the abstract, augmented inventorship supplies an administrable grammar for human accountability in AI-assisted research.
This essay examines how Canadian copyright law treats neurodata generated for neuroprediction and further probes if copyright or similar protections would offer mechanisms to safeguard individuals who produce those data. Using a hypothetical fact pattern, we apply the conditions for subsistence of copyright to neurodata created by a research participant and processed by a researcher. The results of the analysis indicate that both parties can credibly argue that copyright subsists in the neurodata, although such an outcome is neither established nor guaranteed under current law. We then explore the policy significance of this legal analysis from a neuroethics perspective. Drawing together literatures on data justice, political economy, and neurotechnology governance, we argue that when people produce neurodata, legal systems should appropriately honor their contributions. This could be accomplished through protections of the integrity of neurodata from harmful misuse, akin to what moral rightsholders can accomplish under Canadian moral rights doctrine. We further highlight the need to protect individual autonomy over brain data, whether via copyright or another mechanism. We conclude that the Canadian approach to copyright law and moral rights offers a model for policy and governance as neurodata find their way into legally and socially consequential technologies.
Since 2003, US federal funders' scientific data-sharing policies have encouraged open sharing of weakly de-identified medical and genomic data. This sharing fueled important scientific advances but, as this article explains, was of dubious legality, and recent regulations have removed any doubt: open access to medical data is a dying concept if not already dead. The future of medical data sharing lies with controlled access data repositories, which replicate many of the scientific benefits of data sharing but provide stronger privacy and data security protections. The drawback is that meaningful data protections cost money, forcing controlled access repositories to explore new private funding models to sustain data availability over the long haul after federal funding expires. Unless carefully crafted, transactions to finance controlled access repositories (such as charging user fees or receiving discounts on cloud storage from information technology service providers) can violate federal laws this article explores. Going forward, the law of medical privacy boils down to how much privacy those who share and use our data can realistically and lawfully finance. That is how much privacy we, the public, can expect.
In recent decades, neurotechnological cognitive enhancers (NCEs), including neurofeedback systems and neurostimulation devices, have attracted increasing attention due to their potential to enhance human cognition. Developments in this field of technology raise significant ethical challenges that warrant careful reflection from a human rights perspective. Currently, human rights experts and international institutions are actively examining how neurotechnological interventions affecting mental states, capacities, and processes impact human rights and fundamental freedoms. Within these efforts, however, greater attention must be paid to the positive dimension of human rights, examining whether and to what extent human rights frameworks support individuals' freedom to use neurotechnologies to enhance their mental capacities. This article addresses that question by first outlining the concept of cognitive enhancement and assessing the current and anticipated development of NCEs. It then explores the tension between empowerment and constraint, analysing how human rights both support the use of NCEs and potentially justify limitations on that freedom. In doing so, it examines the existence and scope of a right to mental self-determination, the role of human dignity, and the conditions under which restrictions on NCE may be justified.
The aim of this article is to provide an overview and analyze the implications of the provisions on dataset quality and bias in the AI Act (AIA). The AIA requires providers of AI systems to take measures to identify, prevent, and mitigate biases as part of the data governance practices. The AIA also explicitly prescribes certain characteristics required of training, validation, and testing datasets. These include notions widely considered as best practice such as representativeness as well as consideration of characteristics particular to the "geographical, contextual, behavioural or functional setting" which might expand the scope of considerations already common among AI developers. The AIA also aims to address the legal limitations on access to sensitive data by introducing the so called "debiasing exception," which under certain conditions permits the processing of sensitive data for debiasing purposes. To ensure enforcement of the data governance provisions, the AIA grants notified bodies and enforcement authorities access to training, validation, and testing datasets; however, further efforts may be needed to reconcile data protection concerns with these enforcement powers. The AIA's requirements will likely help mitigate bias in medical AI systems. Associated soft law instruments should contribute to the effective implementation of these requirements.
Lawyers and law professors are increasingly involved in interdisciplinary scientific teams and grant research to answer ethical, legal and policy questions related to biomedical topics. Yet, the methods that lawyers use to conduct legal research and analysis are not always familiar to scientists and social scientists conducting peer review of a proposed project with legal aims or a publication reporting a legal study. To better facilitate interdisciplinary ethical, legal, and social implications collaboration, there is a need to better explain how legal research methodologies can provide robust tools to address a range of nuanced biomedical questions. This paper explores legal research and analysis methodologies relevant to federally funded research and scientific inquiry. It sets out different ways that legal research and analysis can advance and support biomedical, bioethics, and health law research and then demonstrates how these benefits can be realized using case studies from existing literature.
