Journal of Law and the Biosciences最新文献

A growing body of literature examines the ethico-legal challenges resulting from novel forms of assisted gestation like uterus transplantation and artificial placentas (also known as 'artificial wombs'). However, there has not yet been consideration of reproductive rights organizations/advocates' understandings of novel forms of assisted gestation and their challenges. These perspectives provide critical insight into how novel procreative practices are understood and the problems and pressures that might arise from their use. This is the first legal article to engage with reproductive rights organizations/advocates and thus it provides important contextual grounding to existing scholarship about assisted gestation. Focus group discussion epitomized the need for legal reform in key areas surrounding reproduction. Themes were constructed that exemplify what participants highlighted as critical: the need to re-evaluate the fundamentals of legal parenthood, consideration of how novel technologies could further enable the policing of gestation, and the space and time needed for law-making.

Innovations in neurotechnologies have ignited conversations about ethics around the world, with implications for researchers, policymakers, and the private sector. The human rights impacts of neurotechnologies have drawn the attention of United Nations bodies; nearly 40 states are tasked with implementing the Organization for Economic Co-operation and Development's principles for responsible innovation in neurotechnology; and the United States is considering placing export controls on brain-computer interfaces. Against this backdrop, we offer the first review and analysis of neuroethics guidance documents recently issued by prominent government, private, and academic groups, focusing on commonalities and divergences in articulated goals; envisioned roles and responsibilities of different stakeholder groups; and the suggested role of the public. Drawing on lessons from the governance of other emerging technologies, we suggest implementation and evaluation strategies to guide practitioners and policymakers in operationalizing these ethical norms in research, business, and policy settings.

Artificial intelligence (AI) enables a medical device to optimize its performance through machine learning (ML), including the ability to learn from past experiences. In healthcare, ML is currently applied within controlled settings in devices to diagnose conditions like diabetic retinopathy without clinician input, for instance. In order to allow AI-based medical devices (AIMDs) to adapt actively to its data environment through ML, the current risk-based regulatory approaches are inadequate in facilitating this technological progression. Recent and innovative regulatory changes introduced to regulate AIMDs as a software, or 'software as a medical device' (SaMD), and the adoption of a total device/product-specific lifecycle approach (rather than one that is point-in-time) reflect a shift away from the strictly risk-based approach to one that is more collaborative and participatory in nature, and anticipatory in character. These features are better explained by a rights-based approach and consistent with the human right to science (HRS). With reference to the recent explication of the normative content of HRS by the Committee on Economic, Social and Cultural Rights of the United Nations, this paper explains why a rights-based approach that is centred on HRS could be a more effective response to the regulatory challenges posed by AIMDs. The paper also considers how such a rights-based approach could be implemented in the form of a regulatory network that draws on a 'common fund of knowledges' to formulate anticipatory responses to adaptive AIMDs. In essence, the HRS provides both the mandate and the obligation for states to ensure that regulatory governance of high connectivity AIMDs become increasingly collaborative and participatory in approach and pluralistic in substance.

In both the EU and USA, genetic data are recognized as a special category of data that requires heightened privacy protection. Identifiability and sensitivity are central pillars of the regulatory framework in both jurisdictions: the privacy concerns stem from the assumption that genetic data are capable of identifying the individual and reveals sensitive information about them. But not all genetic data are identifiable and sensitive, nor are genetic data necessarily different from other types of big data in terms of these issues. This article argues that a more nuanced approach is needed to assess the threat to privacy interests posed by uses of genetic data. The privacy interests involved should be distinguished in terms of proposed use, the amount of data in question, and its uniqueness and informational content. When these factors are disaggregated, it is clear that both regulatory schemes could better achieve their goals by focusing more on the ways genetic data can be used rather than on their status as a special category of data.

The open science (OS) movement has garnered increasing support in academia alongside continued financial and reputational incentives to obtain intellectual property (IP) protections over research outputs. Here, we explore stakeholder perspectives about intersections between OS and IP to inform the development of institutional OS guidelines for the neurosciences in Canada. We held six focus groups and three interviews with 29 faculty members from a major research and clinical center in Canada. The semi-structured interview guide probed perspectives on the respective roles of patents and OS in neuroscience-related research. We applied thematic content analysis to the transcript data, and extracted 12 major themes and 30 subthemes. Participants perceived a conflict between OS ideologies and the inherently restrictive nature of patents, and highlighted the importance of autonomy, justice, and respectful, culturally safe research practices in any future adoption of OS. Overall, the data suggest that a hybrid OS-IP policy model supported by local expertise may be best suited to meet the priorities and values of the community while mitigating perceived threats. This model includes expanded education about patenting, incentivized data sharing and collaboration, and tangible resources to support implementation of OS that includes skilled support in digital research infrastructures.

Much of the academic literature criticizes the inclusion of patent term extensions (PTE) and test data protection into the pharmaceutical provisions and/or intellectual property (IP) chapters of free trade agreements (FTAs), with many arguing that such provisions will increase the cost of pharmaceuticals for the implementing government. Such arguments are often backed by studies conducted prior to the conclusion of the relevant FTA. This is problematic for several reasons, most notably that the studies make assumptions that subsequently turn out not to be false and that the claims are not revisited and supported with empirical data following implementation. This article reviews the experience of two jurisdictions - Canada and Australia - in order to provide an analysis of legislative and judicial practices with a focus on implications and the cost of FTAs. The article examines how Canada and Australia have implemented their FTA obligations domestically and on the hereto ignored but important role of courts. One key finding is how courts in both countries are vigilant in narrowing the scope of obligations under FTAs to accommodate the need of the domestic market. The article ultimately concludes by calling on governments to conduct a detailed analysis of PTE and test data protection so as to better inform and prepare policymakers and, ultimately, improved FTA provisions and health outcomes.

In this article, the right to terminate pregnancy is discussed comparatively in terms of the situation in Turkey and the rest of the world. We have concluded that certain minimum conditions must be met to be able to talk about the full recognition of this right. Recognizing that pregnancy can be terminated voluntarily is the most important of these conditions. Just as the period in which this right can be exercised should not be kept short, it should also be accepted that it can only be used based on the will of a pregnant person who has the power of discernment. In addition, certain obligations must be avoided, such as receiving counseling services before the termination of pregnancy and then waiting for a certain period of time to pass. In cases where pregnancy can be terminated because of an anomaly, a disease, or a crime, it is important to make clear arrangements that will not make practitioners, especially physicians, hesitate to perform such a procedure. Finally, the State must never forget that it is obliged to organize services for the termination of pregnancies in a way that is easily accessible to everyone who may need this procedure.

Germline genetic testing for inherited cancer risk has shifted to multi-gene panel tests (MGPTs). While MGPTs detect more pathogenic variants, they also detect more variants of uncertain significance (VUSs) that increase the possibility of harms such as unnecessary surgery. Data sharing by laboratories is critical to addressing the VUS problem. However, barriers to sharing and an absence of incentives have limited laboratory contributions to the ClinVar database. Payers can play a crucial role in the expansion of knowledge and effectiveness of genetic testing. Current policies affecting MGPT reimbursement are complex and create perverse incentives. Trends in utilization and coverage for private payers and Medicare illustrate opportunities and challenges for data sharing to close knowledge gaps and improve clinical utility. Policy options include making data sharing (i) a condition of payment, and (ii) a metric of laboratory quality in payment contracts, yielding preferred coverage or enhanced reimbursement. Mandating data sharing sufficient to verify interpretations and resolve discordance among labs under Medicare and federal health programs is an option for the US Congress. Such policies can reduce the current waste of valuable data needed for precision oncology and improved patient outcomes, enabling a learning health system.

Sharing cancer gene variant and relevant clinical data could accelerate progress in cancer genomics. However, data sharing is currently impeded by issues related to financial sustainability, equity, incentives, privacy and security, and data quality. Evidence-based policy options to facilitate data sharing in these domains, and ultimately improve interpretation of cancer-associated genomic variants, are therefore needed. We conducted a modified policy Delphi with expert stakeholders that involved generating, evaluating, and ranking potential policy options to address these issues, with a focus on the US context. We found policy options in the financial sustainability domain were highly ranked, particularly stable funding for trusted entities. However, some Delphi panelists noted that the culture of public research funding has favored short-term grants. Panelists favored policy options focused on action by funders, which had the highest overall total scores that combined effectiveness and feasibility ratings and priority ranking within domains. Panelists also endorsed some policy options connected to actors such as journals, but they were more skeptical of policy options connected to legislative actors and data resources. These findings are critical inputs for policy makers as they consider policies to enable sharing of cancer gene variant data to improve health.