From Research to Policy: Unveiling Dementia Prevention Efforts in Switzerland.

Recent research has challenged the notion that dementia is an inevitable outcome of age-related cognitive decline, highlighting the possibility of preventing or delaying onset by addressing specific risk factors. This paradigm shift suggests that prevention through lifestyle modifications and early interventions is possible, potentially averting millions of cases worldwide. This study explores the translation of scientific evidence on dementia prevention into public health policy in Switzerland. Combining the analysis of official policy documents and qualitative interviews with stakeholders, the study explores potential barriers and challenges to implementing preventive intervenions or programs, as well as opportunities for improvement. Results indicate a significant gap in incorporating emerging scientific evidence on dementia prevention into health policies and disseminating information to the public in Switzerland. This study underscores the need for a collaborative and coordinated approach to address these barriers and effectively translate scientific findings into preventive policies and campaigns. These insights can inform policy and targeted programs in Switzerland both at the federal and the cantonal level, eventually serving as a model for other countries seeking to translate evidence-based dementia prevention strategies into public health policies. By bridging the gap between research and policy, significant progress can be made in preventing or delaying the onset of dementia, providing significant benefits to individuals, families, and society.

Digital bioethics: introducing new methods for the study of bioethical issues.

The online space has become a digital public square, where individuals interact and share ideas on the most trivial to the most serious of matters, including discussions of controversial ethical issues in science, technology and medicine. In the last decade, new disciplines like computational social science and social data science have created methods to collect and analyse such data that have considerably expanded the scope of social science research. Empirical bioethics can benefit from the integration of such digital methods to investigate novel digital phenomena and trace how bioethical issues take shape online.Here, using concrete examples, we demonstrate how novel methods based on digital approaches in the social sciences can be used effectively in the domain of bioethics. We show that a digital turn in bioethics research aligns with the established aims of empirical bioethics, integrating with normative analysis and expanding the scope of the discipline, thus offering ways to reinforce the capacity of bioethics to tackle the increasing complexity of present-day ethical issues in science and technology. We propose to call this domain of research in bioethics digital bioethics.

Accelerated drug approval: Meeting the ethical yardstick.

Drugs addressing unmet medical needs can change the lives of millions. Developing and validating new drugs can, however, take many years. To streamline the assessment of new drugs, regulatory agencies have long established shortened review pathways. Among these programs, Accelerated Approval (AA) has recently come under scrutiny due to the U.S. Food and Drug Administration's decision to authorize Aducanumab, the first Alzheimer's disease drug. This decision attracted fierce criticism due to the allegedly insufficient evidence about the safety and efficacy of the drug. While considerable scholarly attention has been devoted to this case, the ethical aspects of the AA regulatory pathway have so far remained relatively unexplored. In this paper, we set out to fill this gap. We illustrate six conditions that should be met for AA to be ethically acceptable: moral solicitude, evidence, risk mitigation, impartiality, sustainability, and transparency. We discuss such conditions and suggest practical steps to implement them in regulatory and oversight processes. Taken together, our six conditions represent a benchmark for assessing the ethical validity of AA processes and decisions.

Ethics review of big data research: What should stay and what should be reformed?

BACKGROUND: Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts. MAIN TEXT: In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science. CONCLUSIONS: We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

The plasticity of ageing and the rediscovery of ground-state prevention.

In this paper, I present an emerging explanatory framework about ageing and care. In particular, I focus on how, in contrast to most classical accounts of ageing, biomedicine today construes the ageing process as a modifiable trajectory. This framing turns ageing from a stage of inexorable decline into the focus of preventive strategies, harnessing the functional plasticity of the ageing organism. I illustrate this shift by focusing on studies of the demographic dynamics in human population, observations of ageing as an intraspecifically heterogenous phenotype, and the experimental manipulation of longevity, in both model organisms and humans. I suggest that such an explanatory framework about ageing creates the epistemological conditions for the rise of a peculiar form of prevention that does not aim to address a specific condition. Rather it seeks to stall the age-related accumulation of molecular damage and functional deficits, boosting individual resilience against age-related decline. I call this preventive paradigm "ground-state prevention." While new, ground-state prevention bears conceptual resemblance to forms of medical wisdom prominent in classic Galenic medicine, as well as in the Renaissance period.

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective.

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.

Machine learning in medicine: Addressing ethical challenges.

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.

Elements of Trust in Digital Health Systems: Scoping Review.

BACKGROUND: Information and communication technologies have long become prominent components of health systems. Rapid advances in digital technologies and data science over the last few years are predicted to have a vast impact on health care services, configuring a paradigm shift into what is now commonly referred to as digital health. Forecasted to curb rising health costs as well as to improve health system efficiency and safety, digital health success heavily relies on trust from professional end users, administrators, and patients. Yet, what counts as the building blocks of trust in digital health systems has so far remained underexplored. OBJECTIVE: The objective of this study was to analyze what relevant stakeholders consider as enablers and impediments of trust in digital health. METHODS: We performed a scoping review to map out trust in digital health. To identify relevant digital health studies, we searched 5 electronic databases. Using keywords and Medical Subject Headings, we targeted all relevant studies and set no boundaries for publication year to allow a broad range of studies to be identified. The studies were screened by 2 reviewers after which a predefined data extraction strategy was employed and relevant themes documented. RESULTS: Overall, 278 qualitative, quantitative, mixed-methods, and intervention studies in English, published between 1998 and 2017 and conducted in 40 countries were included in this review. Patients and health care professionals were the two most prominent stakeholders of trust in digital health; a third-health administrators-was substantially less prominent. Our analysis identified cross-cutting personal, institutional, and technological elements of trust that broadly cluster into 16 enablers (altruism, fair data access, ease of use, self-efficacy, sociodemographic factors, recommendation by other users, usefulness, customizable design features, interoperability, privacy, initial face-to-face contact, guidelines for standardized use, stakeholder engagement, improved communication, decreased workloads, and service provider reputation) and 10 impediments (excessive costs, limited accessibility, sociodemographic factors, fear of data exploitation, insufficient training, defective technology, poor information quality, inadequate publicity, time-consuming, and service provider reputation) to trust in digital health. CONCLUSIONS: Trust in digital health technologies and services depends on the interplay of a complex set of enablers and impediments. This study is a contribution to ongoing efforts to understand what determines trust in digital health according to different stakeholders. Therefore, it offers valuable points of reference for the implementation of innovative digital health services. Building on insights from this study, actionable metrics can be developed to assess the trustworthiness of digital technologies in health care.

Physical frailty, sarcopenia, and the enablement of autonomy: philosophical issues in geriatric medicine.

Physical frailty and loss of muscular mass (sarcopenia) are believed to be predictors of age-related conditions, such as disability and loss of autonomy. In this paper, I show that what in political and moral philosophy has come to be known as "the capability approach" may indeed provide much needed conceptual clarification in the area of frailty research. Other than being useful at the theoretical level, the capability approach can definitely help in the implementation of clinical guidelines and public health measures aimed at translating the results that are accumulating from frailty research. I will first briefly review the main philosophical tenets of the capability approach, and then analyze how they relate to current debates about frailty and sarcopenia by introducing the notion of "enablement". Finally, I will show how my analysis bears on both clinical research in this domain and public policy aimed at tackling some of the age-related issues in an aging society.

"Tailored-to-You": Public Engagement and the Political Legitimation of Precision Medicine.

With the launch of the Precision Medicine Initiative (PMI) in January 2015, the White House granted a high degree of federal support to an emerging biomedical paradigm. What explains this level of political recognition? Based on literature and policy analysis, we reconstruct the scientific and the legislative paths that led to the political endorsement of precision medicine. First, we describe the proliferation of personalized approaches to therapy ignited by the discovery of hemoprotein cytochrome P450 polymorphism in 1988. Then, we analyze the legislative history of precision medicine, from the unsuccessful introduction of Genomics and Personalized Medicine Acts in the second half of the last decade, to the highly acclaimed PMI. However, scientific progress and political contingency alone do not explain the upheaval of precision medicine as an institutionally supported initiative. On examination, the launch of a Precision Medicine Research Cohort and the incorporation of a participatory ethos into the fabric of the PMI proved to be crucial determinants of the political support for precision medicine. Weaving together the scientific and legislative antecedents of precision medicine, we illuminate how the mutual constitution of science and social order generates political recognition for innovative biomedical paradigms.

Cell reprogramming requires silencing of a core subset of polycomb targets.

Transcription factor (TF)-induced reprogramming of somatic cells into induced pluripotent stem cells (iPSC) is associated with genome-wide changes in chromatin modifications. Polycomb-mediated histone H3 lysine-27 trimethylation (H3K27me3) has been proposed as a defining mark that distinguishes the somatic from the iPSC epigenome. Here, we dissected the functional role of H3K27me3 in TF-induced reprogramming through the inactivation of the H3K27 methylase EZH2 at the onset of reprogramming. Our results demonstrate that surprisingly the establishment of functional iPSC proceeds despite global loss of H3K27me3. iPSC lacking EZH2 efficiently silenced the somatic transcriptome and differentiated into tissues derived from the three germ layers. Remarkably, the genome-wide analysis of H3K27me3 in Ezh2 mutant iPSC cells revealed the retention of this mark on a highly selected group of Polycomb targets enriched for developmental regulators controlling the expression of lineage specific genes. Erasure of H3K27me3 from these targets led to a striking impairment in TF-induced reprogramming. These results indicate that PRC2-mediated H3K27 trimethylation is required on a highly selective core of Polycomb targets whose repression enables TF-dependent cell reprogramming.

Becoming partners, retaining autonomy: ethical considerations on the development of precision medicine.

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.

Sync fast and solve things-best practices for responsible digital health.

Digital health innovation is expected to transform healthcare, but it also generates ethical and societal concerns, such as privacy risks, and biases that can compound existing health inequalities. While such concerns are widely recognized, existing regulatory principles, oversight methods and ethical frameworks seem out of sync with digital health innovation. New governance and innovation best practices are thus needed to bring such principles to bear with the reality of business, innovation, and regulation.To grant practical insight into best practices for responsible digital health innovation, we conducted a qualitative study based on an interactive engagement methodology. We engaged key stakeholders (n = 46) operating at the translational frontier of digital health. This approach allowed us to identify three clusters of governance and innovation best practices in digital health innovation: i) inclusive co-creation, ii) responsive regulation, and iii) value-driven innovation. Our study shows that realizing responsible digital health requires diverse stakeholders' commitment to adapt innovation and regulation practices, embracing co-creation as the default modus operandi for digital health development. We describe these collaborative practices and show how they can ensure that innovation is neither slowed by overregulation, nor leads to unethical outcomes.

From lab to society: Fostering clinical translation of molecular systems engineering.

Over the last decade, bioengineering has seen a sustained growth in scientific publications, patents, and clinical trials. As the field attempts to bridge the gap between discovery and clinical application, a broader societal dialogue is needed to build public trust and address potential ethical, societal, and regulatory challenges. In this essay, we discuss societal aspects linked to the clinical use of biomedical engineering approaches and technologies, with a specific focus on molecular systems engineering. Drawing on data from interviews with 24 scientists, we identified four key aspects for fostering societal support for translational efforts in this domain: (1) effective science communication and internal awareness; (2) open societal dialogue; (3) fair and equitable access to new technologies; and (4) adequate science and technology policies. We conclude that molecular systems engineering would benefit from anticipating future challenges with the view of building a robust bond of trust with lay publics, regulators, and society at large.

Organizational aspects of tissue engineering clinical translation: insights from a qualitative case study.

Background: Tissue engineering is a multidisciplinary field that combines principles from cell biology, bioengineering, material sciences, medicine and surgery to create functional and viable bioproducts that can be used to repair or replace damaged or diseased tissues in the human body. The complexity of tissue engineering can affect the prospects of efficiently translating scientific discoveries in the field into scalable clinical approaches that could benefit patients. Organizational challenges may play a key role in the clinical translation of tissue engineering for the benefit of patients. Methods: To gain insight into the organizational aspects of tissue engineering that may create impediments to efficient clinical translation, we conducted a retrospective qualitative case study of one tissue engineering multi-site translational project on knee cartilage engineered tissue grafts. We collected qualitative data using a set of different methods: semi-structured interviews, documentary research and audio-visual content analysis. Results: Our study identified various challenges associated to first-in-human trials in tissue engineering particularly related to: logistics and communication; research participant recruitment; clinician and medical student participation; study management; and regulation. Conclusions: While not directly generalizable to other types of advanced therapies or to regenerative medicine in general, our results offer valuable insights into organizational barriers that may prevent efficient clinical translation in the field of tissue engineering.

Mapping the ethical landscape of digital biomarkers: A scoping review.

In the evolving landscape of digital medicine, digital biomarkers have emerged as a transformative source of health data, positioning them as an indispensable element for the future of the discipline. This necessitates a comprehensive exploration of the ethical complexities and challenges intrinsic to this cutting-edge technology. To address this imperative, we conducted a scoping review, seeking to distill the scientific literature exploring the ethical dimensions of the use of digital biomarkers. By closely scrutinizing the literature, this review aims to bring to light the underlying ethical issues associated with the development and integration of digital biomarkers into medical practice.

How Do Molecular Systems Engineering Scientists Frame the Ethics of Their Research?

BACKGROUND: There 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Talking Ethics Early in Health Data Public Private Partnerships.

Data access and data sharing are vital to advance medicine. A growing number of public private partnerships are set up to facilitate data access and sharing, as private and public actors possess highly complementary health data sets and treatment development resources. However, the priorities and incentives of public and private organizations are frequently in conflict. This has complicated partnerships and sparked public concerns around ethical issues such as trust, justice or privacy-in turn raising an important problem in business and data ethics: how can ethical theory inform the practice of public and private partners to mitigate misaligned incentives, and ensure that they can deliver societally beneficial innovation? In this paper, we report on the development of the Swiss Personalized Health Network's ethical guidelines for health data sharing in public private partnerships. We describe the process of identifying ethical issues and engaging core stakeholders to incorporate their practical reality on these issues. Our report highlights core ethical issues in health data public private partnerships and provides strategies for how to overcome these in the Swiss health data context. By agreeing on and formalizing ethical principles and practices at the beginning of a partnership, partners and society can benefit from a relationship built around a mutual commitment to ethical principles. We present this summary in the hope that it will contribute to the global data sharing dialogue.