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Precision medicine promises to develop diagnoses and treatments that take individual variability into account. According to most specialists, turning this promise into reality will require adapting the established framework of clinical research ethics, and paying more attention to participants' attitudes towards sharing genotypic, phenotypic, lifestyle data and health records, and ultimately to their desire to be engaged as active partners in medical research.Notions such as participation, engagement and partnership have been introduced in bioethics debates concerning genetics and large-scale biobanking to broaden the focus of discussion beyond individual choice and individuals' moral interests. The uptake of those concepts in precision medicine is to be welcomed. However, as data and medical information from research participants in precision medicine cohorts will be collected on an individual basis, translating a participatory approach in this emerging area may prove cumbersome. Therefore, drawing on Joseph Raz's perfectionism, we propose a principle of respect for autonomous agents that, we reckon, can address many of the concerns driving recent scholarship on partnership and public participation, while avoiding some of the limitations these concept have in the context of precision medicine. Our approach offers a normative clarification to how becoming partners in precision is compatible with retaining autonomy.Realigning the value of autonomy with ideals of direct engagement, we show, can provide adequate normative orientation to precision medicine; it can do justice to the idea of moral pluralism by stressing the value of moral self-determination: and, finally, it can reconcile the notion of autonomy with other more communitarian values such as participation and solidarity.

AbstractBackgroundMethodsResultsConclusionsThere are intense discussions about the ethical and societal implications of biomedical engineering, but little data to suggest how scientists think about the ethics of their work. The aim of this study is to describe how scientists frame the ethics of their research, with a focus on the field of molecular systems engineering.Semi-structured qualitative interviews were conducted during 2021–2022, as part of a larger study. This analysis includes a broad question about how participants view ethics as related to their work, with follow up probes about the topics they consider most important. Interviews were transcribed, inductively coded by two researchers to consensus, and analyzed thematically.Twenty-four scientists participated in the study. Interviewees hold positions as professors, principal investigators, and senior staff researchers in universities or research institutes in the United States and Europe. Among those scientists who reported reflecting on ethical considerations in their work, many equated ethics with research ethics topics (e.g., safety, replicability), or with regulation and guidelines. Participants expressed the view that ethical issues are primarily relevant for clinical trials of bioengineered products, or for those working with animal or human subjects. Scientists described their research as “too early” or “not examining anything living” with regard to ethical reflection. Finally, many felt that ethics is seen as territory for experts and therefore beyond scientists’ competencies.Molecular systems engineering scientists currently focus on regulatory aspects as the framework for their ethical analyses. They describe using a framework to define when life arises, as a means to determine when further ethical engagement is warranted. Further research is needed to investigate how scientists relate to the ethics of their scientific work, and build consensus around concepts of life, autonomous behavior, and physiological relevance of bioengineered systems. [ABSTRACT FROM AUTHOR]

The article focuses on the challenges in finding a suitable expression in French to refer to CRISPR-Cas9, referencing the article ""Editing" genes: A case study about how language matters in bioethics" by M. O'Keefe and colleagues within the issue. Topics mentioned include how adopting the English wording would oppose a national language being a civic asset, the principle of dialogic responsibility, and the use of the expression targeted genome engineering to refer to CRISPR-Cas9 in general.

The article talks about informed consent of the participants in medical research and the disclosure of clinical results to the participants. Topics discussed include the field of genomic research, the patients undergoing genome sequencing and seeking information on the incidental findings, and the concept of the disclosure of results being a right of the patients.

Since the first successful application of the gene editing method based on the CRISPR/Cas-system, the technology has demonstrated great potential but also sparked a series of ethical concerns. Some of the issues are already known from earlier gene editing debates. However, the possibility of CRISPR to target genes with high accuracy and the easy application that allows a biohacker to experiment with a simple toolkit ordered online have introduced new ethical challenges. Further, thanks to preprint servers such as bioRxiv, biomedical research results are more and more accessible with little delay after an experiment was conducted. This enables researchers all over the world to participate and conduct their own experiments, making it a global endeavour. Not only does this make it difficult to monitor and regulate the technology but also speeds up the technological development significantly.CRISPR is only one of many examples of recent advancements with potentially high consequences for society at large. We think it is therefore paramount to identify new issues, understand their nature and assess their impact in a timely manner. In this paper, we propose the integration of digital methods into the toolbox of modern empirical bioethics and demonstrate their potential with two examples: We used 1) crawling and network analysis for hypothesis building, and 2) sentiment analysis to assess the public's attitudes towards CRISPR on Twitter over a six and a half years period. [ABSTRACT FROM AUTHOR]

Background: Explainability is one of the most heavily debated topics when it comes to the application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have been shown to outperform humans in certain analytical tasks, the lack of explainability continues to spark criticism. Yet, explainability is not a purely technological issue, instead it invokes a host of medical, legal, ethical, and societal questions that require thorough exploration. This paper provides a comprehensive assessment of the role of explainability in medical AI and makes an ethical evaluation of what explainability means for the adoption of AI-driven tools into clinical practice.Methods: Taking AI-based clinical decision support systems as a case in point, we adopted a multidisciplinary approach to analyze the relevance of explainability for medical AI from the technological, legal, medical, and patient perspectives. Drawing on the findings of this conceptual analysis, we then conducted an ethical assessment using the "Principles of Biomedical Ethics" by Beauchamp and Childress (autonomy, beneficence, nonmaleficence, and justice) as an analytical framework to determine the need for explainability in medical AI.Results: Each of the domains highlights a different set of core considerations and values that are relevant for understanding the role of explainability in clinical practice. From the technological point of view, explainability has to be considered both in terms how it can be achieved and what is beneficial from a development perspective. When looking at the legal perspective we identified informed consent, certification and approval as medical devices, and liability as core touchpoints for explainability. Both the medical and patient perspectives emphasize the importance of considering the interplay between human actors and medical AI. We conclude that omitting explainability in clinical decision support systems poses a threat to core ethical values in medicine and may have detrimental consequences for individual and public health.Conclusions: To ensure that medical AI lives up to its promises, there is a need to sensitize developers, healthcare professionals, and legislators to the challenges and limitations of opaque algorithms in medical AI and to foster multidisciplinary collaboration moving forward. [ABSTRACT FROM AUTHOR]