The Precision Medicine Nation

Consideration and Disclosure of Group Risks in Genomics and Other Data-Centric Research: Does the Common Rule Need Revision?

Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements in the informed consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward.

'Being disabled' as an exclusion criterion for clinical trials: a scoping review

BACKGROUND

People with disabilities (PWDs) are often excluded from biomedical research, but comprehensive data regarding their participation in clinical trials are not available. The objective of this study was to assess the rates of exclusion of PWDs from recent medical scientific research.

METHODS

The protocol of the study was designed according to PRISMA-ScR (PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for Scoping Reviews) guidelines. All completed interventional clinical trials registered on ClinicalTrials.gov between 2010 and 2020 regarding the 10 leading causes of global disability-adjusted life-years according to the Global Burden of Disease Study were analysed. An exclusion criterion from the study was considered explicit if it could be associated with one of the following seven categories: disability, physical impairment, cognitive impairment, behavioural or psychiatric disorders, language and communication impairment, sensory impairment. Comorbidities not more clearly defined and researcher discretion regarding exclusion of study participants were considered to be 'implicit exclusion criteria'. We assessed the appropriateness of explicit exclusion criteria in relation to the primary objectives of the trials and labelled them as 'absolute', 'relative' or 'questionable'.

RESULTS

The total number of trials analysed was 2710; 170 were paediatric trials (6.3%), 2374 were adult trials (87.6%) and 166 were trials including subjects of all ages (6.1%). Explicit exclusion criteria were found in 958 trials (35.3%). The disability category most frequently excluded was behavioural or psychiatric disorders, present in 588 trials (61.4%). In only 3% and 1% of the trials, the exclusion criteria were considered either 'absolute' or 'questionable', while in 96% the exclusion criteria were judged as 'relative'. Implicit exclusion criteria were present in 1205 trials (44.5%).

CONCLUSIONS

This study highlights the high rate of exclusion of PWDs from biomedical research and the widespread use of ill-defined exclusion criteria in clinical trials. It underscores the importance of more inclusive study designs so that PWDs can become active participants in research.

The fertility of moral ambiguity in precision medicine

Although precision medicine cuts across a large spectrum of professions, interdisciplinary and cross-sectorial moral deliberation has yet to be widely enacted, let alone formalized in this field. In a recent research project on precision medicine, we designed a dialogical forum (i.e. 'the Ethics Laboratory') giving interdisciplinary and cross-sectorial stakeholders an opportunity to discuss their moral conundrums in concert. We organized and carried out four Ethics Laboratories. In this article, we use Simone de Beauvoir's concept of moral ambiguity as a lens to frame the participants' experience with fluid moral boundaries. By framing our approach through this concept we are able to elucidate irremediable moral issues that are collectively underexplored in the practice of precision medicine. Moral ambiguity accentuates an open and free space where different types of perspectives converge and can inform each other. Based on our study, we identified two dilemmas, or thematic interfaces, in the interdisciplinary moral deliberations which unfolded in the Ethics Laboratories: (1) the dilemma between the individual and the collective good; and (2) the dilemma between care and choice. Through our investigation of these dilemmas, we show how Beauvoir's concept of moral ambiquity not only serves as a fertile catalyst for greater moral awareness but, furthermore, how the concept can become an indispensable part of the practices of and the discourse about precision medicine.

Precision medicine and the problem of structural injustice

Many countries currently invest in technologies and data infrastructures to foster precision medicine (PM), which is hoped to better tailor disease treatment and prevention to individual patients. But who can expect to benefit from PM? The answer depends not only on scientific developments but also on the willingness to address the problem of structural injustice. One important step is to confront the problem of underrepresentation of certain populations in PM cohorts via improved research inclusivity. Yet, we argue that the perspective needs to be broadened because the (in)equitable effects of PM are also strongly contingent on wider structural factors and prioritization of healthcare strategies and resources. When (and before) implementing PM, it is crucial to attend to how the organisation of healthcare systems influences who will benefit, as well as whether PM may present challenges for a solidaristic sharing of costs and risks. We discuss these issues through a comparative lens of healthcare models and PM-initiatives in the United States, Austria, and Denmark. The analysis draws attention to how PM hinges on-and simultaneously affects-access to healthcare services, public trust in data handling, and prioritization of healthcare resources. Finally, we provide suggestions for how to mitigate foreseeable negative effects.

Community Engagement in Precision Medicine Research: Organizational Practices and Their Impacts for Equity

BACKGROUND

In the wake of mandates for biomedical research to increase participation by members of historically underrepresented populations, community engagement (CE) has emerged as a key intervention to help achieve this goal.

METHODS

Using interviews, observations, and document analysis, we examine how stakeholders in precision medicine research understand and seek to put into practice ideas about who to engage, how engagement should be conducted, and what engagement is for.

RESULTS

We find that ad hoc, opportunistic, and instrumental approaches to CE exacted significant consequences for the time and resources devoted to engagement and the ultimate impacts it has on research. Critical differences emerged when engagement and research decisionmaking were integrated with each other versus occurring in parallel, separate parts of the study organization, and whether community members had the ability to determine which issues would be brought to them for consideration or to revise or even veto proposals made upstream based on criteria that mattered to them. CE was understood to have a range of purposes, from instrumentally facilitating recruitment and data collection, to advancing community priorities and concerns, to furthering long-term investments in relationships with and changes in communities. These choices about who to engage, what engagement activities to support, how to solicit and integrate community input into the workflow of the study, and what CE was for were often conditioned upon preexisting perceptions and upstream decisions about study goals, competing priorities, and resource availability.

CONCLUSIONS

Upstream choices about CE and constraints of time and resources cascade into tradeoffs that often culminated in "pantomime community engagement." This approach can create downstream costs when engagement is experienced as improvised and sporadic. Transformations are needed for CE to be seen as a necessary scientific investment and part of the scientific process.

Scientists' Views on Scientific Self-Governance for Human Genome Editing Research

As research on human gene editing has grown, a variety of prominent international organizations are considering how best to govern such research. But what role do scientists engaged in genome editing think they should have in developing research governance? In this study, we present results from a survey of 212 U.S.-based scientists regarding views on human genome editing governance. Most did not believe that scientists should be allowed to self-govern human genome editing research. Open-ended responses revealed four main reasons: conflicts of interest, the inevitability of rare "bad apples," historical evidence to the contrary, and the limitations of scientific expertise. Analyses of open-ended responses also revealed scientists' views on how human gene editing research should be governed. These views emphasize interdisciplinary professional and public input. The study results illustrate a noteworthy shift in the scientific community's traditional vision of professional autonomy and can inform ongoing efforts to develop research governance approaches.

Precision patients: Selection practices and moral pathfinding in experimental oncology

This paper addresses selection practices in a Danish phase 1 unit specialised in precision medicine in the field of oncology. Where precision medicine holds the ambition of selecting genetically fit medicine for the patient, we find that precision medicine in the early trial setting is oriented towards selecting clinically and genetically fit patients for available treatment protocols. Investigating how phase 1 oncologists experience and respond to the moral challenges of selecting patients for early clinical trials, we show that inclusion criteria and patient categories are not always transparent to patients. Lack of transparency about inclusion criteria has been interpreted as morally problematic. Yet drawing on social science studies of 'unknowing', we argue that silence and non-transparency in interactions between oncologists and patients are crucial to respect the moral agency of patients at the edge of life and recognise them as belonging to the public of Danish health care. In the discussion, we consider the practice of placing 'unfit' patients on a waiting list for trial participation. Rather than representing an ethical and political problem, we argue, the waiting list can act as a valve enabling oncologists to navigate the scientific and as well as the moral uncertainties in phase 1 oncology.

Governing Personalized Health: A Scoping Review

Genetic research is advancing rapidly. One important area for the application of the results from this work is personalized health. These are treatments and preventive interventions tailored to the genetic profile of specific groups or individuals. The inclusion of personalized health in existing health systems is a challenge for policymakers. In this article, we present the results of a thematic scoping review of the literature dealing with governance and policy of personalized health. Our analysis points to four governance challenges that decisionmakers face against the background of personalized health. First, researchers have highlighted the need to further extend and harmonize existing research infrastructures in order to combine different types of genetic data. Second, decisionmakers face the challenge to create trust in personalized health applications, such as genetic tests. Third, scholars have pointed to the importance of the regulation of data production and sharing to avoid discrimination of disadvantaged groups and to facilitate collaboration. Fourth, researchers have discussed the challenge to integrate personalized health into regulatory-, financing-, and service provision structures of existing health systems. Our findings summarize existing research and help to guide further policymaking and research in the field of personalized health governance.

Recent scientific/intellectual movements in biomedicine

This study compares the trajectories of recent scientific/intellectual movements (SIMs) in biomedicine: evidence-based medicine, translational medicine, precision medicine, personalized medicine, stratified medicine, and genomic medicine. Drawing on bibliometric analysis of these six SIMs, this study identifies three patterns: field integration, niche creation, and disruptive insurgence. Field integration SIMs such as evidence-based medicine and translational medicine are characterized by centrality of key concept papers of the SIM in co-citation networks and dense institutional and country collaboration networks, signaling the resonance of the SIM to the broader biomedical community. In contrast, niche creation SIMs such as stratified medicine and genomic medicine are characterized by lower levels of annual scientific production, the lack centrality or connectivity of key concept papers in co-citation networks, and less density in collaboration networks. Disruptive insurgence SIMs such as precision medicine and personalized medicine are characterized by a high level of annual scientific production, driven by a smaller core of institutions and countries. This is likely a transitional stage as field disrupting SIMs can either become integrated with the broader field or become influential in niches. Proponents of the current push for precision medicine should ensure that a wide range of institutions and specialties be included while being mindful of the dominance of cancer and genomic approaches to health and medicine.

Perceptions of 'Precision' and 'Personalised' Medicine in Singapore and Associated Ethical Issues

Governments are investing in precision medicine (PM) with the aim of improving healthcare through the use of genomic analyses and data analytics to develop tailored treatment approaches for individual patients. The success of PM is contingent upon clear public communications that engender trust and secure the social licence to collect and share large population-wide data sets because specific consent for each data re-use is impractical. Variation in the terminology used by different programmes used to describe PM may hinder clear communication and threaten trust. Language is used to create common understanding and expectations regarding precision medicine between researchers, clinicians and the volunteers. There is a need to better understand public interpretations of PM-related terminology. This paper reports on a qualitative study involving 24 focus group participants in the multi-lingual context of Singapore. The study explored how Singaporeans interpret and understand the terms ‘precision medicine’ and ‘personalised medicine’, and which term they felt more aptly communicates the concept and goals of PM. Results suggest that participants were unable to readily link the terms with this area of medicine and initially displayed preferences for the more familiar term of ‘personalised’. The use of visual aids to convey key concepts resonated with participants, some of whom then indicated preferences for the term ‘precision’ as being a more accurate description of PM research. These aids helped to facilitate dialogue around the ethical and social value, as well as the risks, of PM. Implications for programme developers and policy makers are discussed.

Precision Health: The Role of the Social and Behavioral Sciences in Advancing the Vision

BACKGROUND

In 2015, Collins and Varmus articulated a vision for precision medicine emphasizing molecular characterization of illness to identify actionable biomarkers to support individualized treatment. Researchers have argued for a broader conceptualization, precision health. Precision health is an ambitious conceptualization of health, which includes dynamic linkages between research and practice as well as medicine, population health, and public health. The goal is a unified approach to match a full range of promotion, prevention, diagnostic, and treatment interventions to fundamental and actionable determinants of health; to not just address symptoms, but to directly target genetic, biological, environmental, and social and behavioral determinants of health.

PURPOSE

The purpose of this paper is to elucidate the role of social and behavioral sciences within precision health.

MAIN BODY

Recent technologies, research frameworks, and methods are enabling new approaches to measure, intervene, and conduct social and behavioral science research. These approaches support three opportunities in precision health that the social and behavioral sciences could colead including: (a) developing interventions that continuously "tune" to each person's evolving needs; (b) enhancing and accelerating links between research and practice; and (c) studying mechanisms of change in real-world contexts. There are three challenges for precision health: (a) methods of knowledge organization and curation; (b) ethical conduct of research; and (c) equitable implementation of precision health.

CONCLUSIONS

Precision health requires active coleadership from social and behavioral scientists. Prior work and evidence firmly demonstrate why the social and behavioral sciences should colead with regard to three opportunity and three challenge areas.

Personalised medicine and the state: A political discourse analysis

The last decade has seen a range of health policy initiatives relating to personalised medicine. There is an emerging body of studies that demonstrates the continued importance of states in the development of personalised medicine. This paper contributes to this literature by focusing on how political discourses construct the role of states in personalised medicine. Based on a case study of the introduction of a national programme in Denmark, the analysis identifies specific discursive mechanisms in this construction. The material consists of documents from key national stakeholders, media coverage and interviews with experts at the national level. The analysis found three types of discursive mechanisms. Firstly, mechanisms can relate to problem definitions, and these were concerned with a number of salient problems of health services. Secondly, mechanisms can relate to underlying assumptions, and these were about the possibility of engineering healthcare improvement through data and by extension personalised medicine. Thirdly, mechanisms can relate to discursive effects, and here the state emerged as a highly influential governor. These mechanisms are likely to be highly relevant for other countries, but future research needs to test this. Health policy practitioners and health administrators thus need to invest effort into influencing political discourses around personalised medicines, in addition to the formulation of policies itself.

A roadmap for precision medicine research recruitment: empirical assessment of the public's willingness to participate

Aim: Precision medicine research recruitment poses challenges. To better understand factors impacting recruitment, this study assessed hypothetical willingness, public opinions of and familiarity with precision medicine research. Materials & methods: Adult attendees (n = 942) at the 2017 Minnesota State Fair completed an electronic survey. Results: Few respondents had heard of 'precision medicine' (18%), and familiarity came mostly from media (43%). Fifty-six percent expressed hypothetical willingness to participate in precision medicine research. Significant predictors of willingness were: comfort with unconditional research; perceiving precision medicine research as beneficial, trustworthy and confidential; having a graduate degree; comfort with self- but not family-participation; and familiarity with precision/personalized medicine. Conclusion: This study identified predictors of hypothetical willingness to participate in precision medicine research. Alternative recruitment strategies are needed.

Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities

The machine learning community has become alert to the ways that predictive algorithms can inadvertently introduce unfairness in decision-making. Herein, we discuss how concepts of algorithmic fairness might apply in healthcare, where predictive algorithms are being increasingly used to support decision-making. Central to our discussion is the distinction between algorithmic fairness and algorithmic bias. Fairness concerns apply specifically when algorithms are used to support polar decisions (i.e., where one pole of prediction leads to decisions that are generally more desired than the other), such as when predictions are used to allocate scarce health care resources to a group of patients that could all benefit. We review different fairness criteria and demonstrate their mutual incompatibility. Even when models are used to balance benefits-harms to make optimal decisions for individuals (i.e., for non-polar decisions)-and fairness concerns are not germane-model, data or sampling issues can lead to biased predictions that support decisions that are differentially harmful/beneficial across groups. We review these potential sources of bias, and also discuss ways to diagnose and remedy algorithmic bias. We note that remedies for algorithmic fairness may be more problematic, since we lack agreed upon definitions of fairness. Finally, we propose a provisional framework for the evaluation of clinical prediction models offered for further elaboration and refinement. Given the proliferation of prediction models used to guide clinical decisions, developing consensus for how these concerns can be addressed should be prioritized.

Return of Value in the New Era of Biomedical Research-One Size Will Not Fit All

Background: There is a growing interest in creating large-scale repositories that store genetic, behavioral, and environmental data for future, unspecified uses. The All of Us Research Program is one example of such a repository. Its participants will get access to their personal data and the results of the studies that used them. However, little is known about what researchers should return to participants and how they should do it in a way that is valuable and meaningful to participants. Methods: To better understand the concept of "return of value" and the practice of returning valuable study information, we conducted semi-structured telephone interviews with 44 stakeholders with diverse perspectives on this topic. All interviews have been transcribed and coded thematically to identify the most salient themes, to explore differences between returning different types of study results, and to describe differences and similarities in perspectives of different stakeholder groups. Results: We found that one size does not fit all when it comes to returning value to participants: the decisions about return of results are affected by participant preferences, researchers' concerns about feasibility, the types of data collected, their level of granularity, and available options for supporting result interpretation. Conclusions: Our findings suggest that the key to operationalizing return of value and to identifying ways to return valuable information to study participants may be to find a point of equilibrium between criteria that may affect usefulness and feasibility. The point of equilibrium may vary by study, by participants' backgrounds and preferences, by their health literacy and access to regular healthcare, and by the resources available to professionals controlling the data. Future studies should explore the factors that determine the point of equilibrium between feasibility and usefulness.

Contested futures: envisioning "Personalized," "Stratified," and "Precision" medicine

In recent years, discourses around "personalized," "stratified," and "precision" medicine have proliferated. These concepts broadly refer to the translational potential carried by new data-intensive biomedical research modes. Each describes expectations about the future of medicine and healthcare that data-intensive innovation promises to bring forth. The definitions and uses of the concepts are, however, plural, contested and characterized by diverse ideas about the kinds of futures that are desired and desirable. In this paper, we unpack key disputes around the "personalized," "stratified," and "precision" terms, and map the epistemic, political and economic contexts that structure them as well as the different roles attributed to patients and citizens in competing future imaginaries. We show the ethical and value baggage embedded within the promises that are manufactured through terminological choices and argue that the context and future-oriented nature of these choices helps to understanding how data-intensive biomedical innovations are made socially meaningful.

Cultivating inclusivity in precision medicine research: disability, diversity, and cultural competence

Cultural competence is increasingly viewed as key for the inclusion of diverse populations in precision medicine research (PMR) in the USA. Precision medicine researchers and personnel are thus increasingly expected to undergo cultural competency trainings and to engage with relevant racial/ethnic communities to ensure that all research components are culturally and linguistically sensitive to these communities. However, the need for PMR enterprises to ensure competence with and understanding of disability rights, history, and needs (hereinafter disability culture competency) have not received attention. This article discusses the importance of disability inclusivity in PMR and the construct-and challenges-of disability as a cultural community. Reviewing and extrapolating from studies in healthcare settings, the article considers three interrelated issues that are likely to impact disability inclusivity in PMR: disability accessibility and accommodation; disability stigma and unconsious bias; and disability language and communication. Next, disability competency trainings that were developed in healthcare settings are surveyed and their applicability for PMR is discussed. The arguments advanced are that disability culture competency among precision medicine researchers, personnel, and oversight committees is essential to upholding the welfare and rights of human subjects with disabilities in PMR; that engagement with disability communities is imperative for this endeavor; and that such knowledge of disability culture is crucial for cultivating inclusivity of people with different (dis)abilities in PMR.

Genomic Justice and Imagined Communities

In this issue of the Hastings Center Report, Maya Sabatello and Paul Appelbaum explore the assumptions about community embedded in the U.S. Precision Medicine Initiative, which aims to recruit donor-partners who reflect the United States' racial and ethnic diversity. As Sabatello and Appelbaum discuss, the initiative is like other national biobanking efforts in bringing to life an imagined genetic community in need of critical attention, and given the public-private forms of partnership at the heart of the PMI, such efforts could become avenues to deepen existing inequalities rather than to alleviate them. The notion of justice has underwritten debates about genomic medicine, informed consent, citizenship, benefit sharing, and profit making since the first national biobanking project emerged at the dawn of the twenty-first century. In a paradigmatic case, the creation, by an Icelandic company, of the deCODE genomic biobank opened up fierce debates about the proper relationship between public good and private gain and became the first global example of the economic and political implications that imagined genetic communities could have in our shared future. In Mexico, in 2001, the Icelandic case fueled a policy agenda to deal with global health justice and the prospects of a future market-based colonialism predicated on the intimate knowledge of DNA.

The Precision Medicine Nation

The United States' ambitious Precision Medicine Initiative proposes to accelerate exponentially the adoption of precision medicine, an approach to health care that tailors disease diagnosis, treatment, and prevention to individual variability in genes, environment, and lifestyle. It aims to achieve this by creating a cohort of volunteers for precision medicine research, accelerating biomedical research innovation, and adopting policies geared toward patients' empowerment. As strategies to implement the PMI are formulated, critical consideration of the initiative's ethical and sociopolitical dimensions is needed. Drawing on scholarship of nationalism and democracy, we discuss the PMI's construction of what we term "genomic citizenship"; the possible normative obligations arising therefrom; and the ethical, legal, and social challenges that will ensue. Although the PMI is a work in progress, discussion of the existing and emerging issues can facilitate the development of policies, structures, and procedures that can maximize the initiative's ability to produce equitable and socially sensitive outcomes. Our analysis can also be applied to other population-based, precision medicine research programs.