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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 dialog 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., Bioengineering & Translational Medicine, ISSN:2380-6761

Introduction Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine learning algorithms, clinical decision support systems (CDSS) can generate unprecedented amounts of predictive information about individuals' health. Yet, despite the potential of these systems to promote proactive decision-making and improve health outcomes, their utility and impact remain poorly understood due to their still rare application in clinical practice. Taking the example of AI-powered CDSS in stroke medicine as a case in point, this paper provides a nuanced account of stroke survivors', family members', and healthcare professionals' expectations and attitudes towards medical AI. Methods We followed a qualitative research design informed by the sociology of expectations, which recognizes the generative role of individuals' expectations in shaping scientific and technological change. Semi-structured interviews were conducted with stroke survivors, family members, and healthcare professionals specialized in stroke based in Germany and Switzerland. Data was analyzed using a combination of inductive and deductive thematic analysis. Results Based on the participants' deliberations, we identified four presumed roles that medical AI could play in stroke medicine, including an administrative, assistive, advisory, and autonomous role AI. While most participants held positive attitudes towards medical AI and its potential to increase accuracy, speed, and efficiency in medical decision making, they also cautioned that it is not a stand-alone solution and may even lead to new problems. Participants particularly emphasized the importance of relational aspects and raised questions regarding the impact of AI on roles and responsibilities and patients' rights to information and decision-making. These findings shed light on the potential impact of medical AI on professional identities, role perceptions, and the doctor-patient relationship. Conclusion Our findings highlight the need for a more differentiated approach to identifying and tackling pertinent ethical and legal issues in the context of medical AI. We advocate for stakeholder and public involvement in the development of AI and AI governance to ensure that medical AI offers solutions to the most pressing challenges patients and clinicians face in clinical care., PLoS ONE, 18 (1), ISSN:1932-6203

Spurred by recent advances in machine learning and electronic hardware, digital health promises to profoundly transform medicine. At the same time, however, it raises conspicuous ethical and regulatory issues. This has led to a growing number of calls for responsible digital health. Based on stakeholder engagement methods, this paper sets out to identify core impediments hindering responsible digital health in Switzerland. We developed a participatory research methodology to access stakeholders' fragmented knowledge of digital health, engaging 46 digital health stakeholders over a period of five months (December 2020–April 2021). We identified ineffective stakeholder collaboration, lack of ethical awareness among digital health innovators, and lack of relevant regulation as core impediments to responsible digital health. The stakeholders' accounts indicate that ethical concerns may considerably slow the pace of digital health innovation – implying that responsible innovation is a core catalyst for the progress of digital health overall., Frontiers in Digital Health, 5, ISSN:2673-253X

AJOB Neuroscience, 12 (4)

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., History and Philosophy of the Life Sciences, 43 (2), ISSN:0391-9714

The implementation of the General Data Protection Regulation (GDPR) raises a series of challenges for scientific research, in particular for research that is dependent on data. This study comprehensively investigates the promises and challenges associated with the implementation of the GDPR in the scientific domain, with a special focus on the impact of the new rights and obligations enshrined in the GDPR on the design and conduct of scientific research. Furthermore, the study examines the adequacy of the GDPR's derogations for scientific research in terms of safeguarding scientific freedom and technological progress. The study also provides policy options that delineate a pathway towards enhancing rather than stifling research, and facilitating privacy-preserving data-driven research under the provisions of the GDPR., ISBN:978-92-846-5045-3

European Data Protection Law Review, 4 (3)

We explored the characteristics and motivations of people who, having obtained their genetic or genomic data from Direct-To-Consumer genetic testing (DTC-GT) companies, voluntarily decide to share them on the publicly accessible web platform openSNP. The study is the first attempt to describe open data sharing activities undertaken by individuals without institutional oversight. In the paper we provide a detailed overview of the distribution of the demographic characteristics and motivations of people engaged in genetic or genomic open data sharing. The geographical distribution of the respondents showed the USA as dominant. There was no significant gender divide, the age distribution was broad, educational background varied and respondents with and without children were equally represented. Health, even though prominent, was not the respondents' primary or only motivation to be tested. As to their motivations to openly share their data, 86.05% indicated wanting to learn about themselves as relevant, followed by contributing to the advancement of medical research (80.30%), improving the predictability of genetic testing (76.02%) and considering it fun to explore genotype and phenotype data (75.51%). Whereas most respondents were well aware of the privacy risks of their involvement in open genetic data sharing and considered the possibility of direct, personal repercussions troubling, they estimated the risk of this happening to be negligible. Our findings highlight the diversity of DTC-GT consumers who decide to openly share their data. Instead of focusing exclusively on health-related aspects of genetic testing and data sharing, our study emphasizes the importance of taking into account benefits and risks that stretch beyond the health spectrum. Our results thus lend further support to the call for a broader and multi-faceted conceptualization of genomic utility., PLoS ONE, 12 (5), ISSN:1932-6203

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., BMC Medical Ethics, 17 (1), ISSN:1472-6939

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., Journal of Medical Internet Research, 20 (12), ISSN:1438-8871

Translating the knowledge from biomedical science into clinical applications that help patients has been compared to crossing a valley of death because of the many issues that separate the bench from the bedside and threaten to stall progress. But translation is also inhibited by a science policy environment with its own impediments. Mapping these policy impediments give a more complete picture of the valley of death. Stem cell science is one example where success in moving from the bench to the bedside has confronted policy challenges generating difficulties as challenging as those facing scientists and clinicians. We highlight some of the characteristics and challenges of the science policy valley of death common to the U.S. and Europe, illustrate them with a recent example from stem cell science, and describe some promising strategies for traversing the valley., Clinical and Translational Medicine, 2, ISSN:2001-1326

A recent United Kingdom survey reports that 63% of the adult population is uncomfortable with allowing personal data to be used to improve healthcare and is unfavorable to artificial intelligence (AI) systems replacing doctors and nurses in tasks they usually perform [1]. Another study, conducted in Germany, found that medical students—the doctors of tomorrow—overwhelmingly buy into the promise of AI to improve medicine (83%) but are more skeptical that it will establish conclusive diagnoses in, for instance, imaging exams (56% disagree) [2]. When asked about the prospects of AI, United States decision-makers at healthcare organizations are confident that it will improve medicine, but roughly half of them think it will produce fatal errors, will not work properly, and will not meet currently hyped expectations [3]. These survey data resonate to the ethical and regulatory challenges that surround AI in healthcare, particularly privacy, data fairness, accountability, transparency, and liability. Successfully addressing these will foster the future of machine learning in medicine (MLm) and its positive impact on healthcare. Ethical and regulatory concerns about MLm can be grouped into three broad categories according to how and where they emerge, namely, around the sources of data needed for MLm and the approaches used in the development and deployment of MLm in clinical practice (for a hypothetical case study, see Fig 1)., PLoS Medicine, 15 (11), ISSN:1549-1277, ISSN:1549-1676

Digital technologies introduce both opportunities and novel ethical issues in medical research, healthcare, and biotechnology. Moreover, discussions surrounding bioethical issues increasingly take place online, and the results of ethical deliberation and normative analysis are routinely disseminated through digital communication channels. Although empirical bioethics research has been growing over the last two decades, the field has only started to pay attention to the peculiarities of digital technologies and online spaces as well as the opportunities they offer. To foster inquiries into digital technologies, we need, on the one hand, to understand how bioethics and digital technologies relate to each other and, on the other hand, a methodological toolbox suited for this digital context. To start building such a toolbox, we can resort to other disciplines such as digital anthropology and computational social science to learn from their methodological innovations and adopt their digital methods for bioethical inquiries. In this thesis, I introduce a holistic approach to integrate digital technologies, both as research subjects and as tools, in the field of bioethics. In Chapter 1, I demonstrate the need for such an approach and provide a definition for digital bioethics, which incorporates three areas of bioethical interest: (1) the study of bioethical issues arising from digital technology applications, (2) the use of digital tools to disseminate bioethical content to stakeholders, and (3) the use of digital methods for empirical bioethics research. In Chapters 2, 3 and 4, I present case studies to exemplify what constitutes these three areas. Thereby, the focus lies on the use of digital methods in Chapter 4, which demonstrates the methods’ value for bioethics and illustrates how they integrate with normative considerations. Chapter 5 reports the development of a research platform that addresses challenges related to the digital methods case studies. The platform exhibits one avenue to support bioethics researchers in conducting digital methods research and, through that, to establish digital bioethics within the discipline. This thesis closes by discussing the case studies in the broader disciplinary context of bioethics and outlines a way forward for bioethics to go digital.

This thesis contributes to our understanding of the strategies and features necessary to build and maintain trust in digital health. Myriad experts foresee digital health technologies as a solution to alleviate the demands on contemporary health systems. Yet, these technologies introduce many ethical challenges, one of which is trust. Besides altering the status quo in physician-patient relationships, plenty of evidence suggests that certain digital health technologies may be unreliable or even promote detrimental behaviors. Moreover, these technologies remain increasingly susceptible to malicious actors; while a number of developers and implementers continue to act negligently. As a result, the perceived risks of digital health continue to grow and thus deteriorate trust. Since trust is imperative to the proper functioning of health systems, it is necessary to determine how to assess the trustworthiness of digital health technologies. The thesis employs both empirical and theoretical methods. The first chapter offers an introductory analysis of digital health and trust in relation to this rapidly expanding form of medical technology. Chapter 2 discusses the major ethical issues posed by digital health in a global as well as in the Swiss context. Through a scoping review of the literature, Chapter 3 identifies the facilitators and inhibitors to trust in digital health as well as the main stakeholders. Meanwhile, since precision medicine relies on diverse datasets that may be obtained from digital health technologies, Chapter 4, stipulates some requirements for trust in precision medicine. Through focus group discussions, Chapter 5 identifies trust-related expectations with respect to mobile health apps, and translates such findings into a trustworthiness checklist. In Chapter 6, the checklist is validated by relevant stakeholders via an online survey. Finally, chapter 7 discusses the overall findings of this thesis, compares it to existing research, and determines its implications