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This paper develops four alternative scenarios depicting possible futures for genomics applications within a broader social context. The scenarios integrate forecasts for future genomics applications with key drivers that are shaping genomics. Each scenario is a narrative depiction of an alternative path towards four very different futures for genomics. The scenarios are intended to give the user the a framework to explore and test their assumptions about the future of genomics, and help them explore the wider interactions between genomics applications and society. Scenario 1, “genomics, inc.”, is a “best guess extrapolation” of key drivers shaping genomics. Scenario 2, “broken promises”, explores hard times for genomics. Scenario 3, “out of our control”, explores the opportunities and challenges brought about by the globalisation of genomics. Scenario 4, “genomics for all”, explores the successful and visionary development of genomics.

New technologies are posing new challenges to social science. Their very novelty also challenges the established methods that social research institutions have used to define their priorities. The UK’s Economic and Social research Council (ESRC) confronted these challenges, in part, by commissioning a futures study. It engaged the Institute for Alternative Futures (IAF) and the Centre for Research on Innovation and Competition (CRIC), to develop quickly a process for informing the choice of social science research priorities related to genomics. Four major reports were developed as background inputs to a scenario workshop process. As well as outlining a set of scenarios for the development of the genomics field, reports covered genomic applications, forecasts for drivers shaping genomics, and how the ESRC’s “thematic priorities” might relate to developments in genomics in the coming years. With this input and using advanced “groupware”, the scenario workshop identified five priority areas focused on how research should be conducted and 11 priority topics for what research is needed.

Clinical genomics is a complex, innovative medical speciality requiring clinical and organizational engagement to fulfil the clinical reward promised to date. Focus thus far has been on gene discovery and clinicians’ perspectives. The purpose of this study was to use implementation science theory to identify organizational barriers and enablers to implementation of clinical genomics along an organizations’ implementation journey from Preadoption through to Adoption and Implementation.

We used a deductive qualitative approach study design drawing on implementation science theory - (1) Translation Science to Population Impact Framework, to inform semi structured interviews with organizational decision-makers collaborating with Australian and Melbourne Genomics, alongside and (2) Theoretical Domains Framework (TDF), to guide data analysis.

We identified evolving organizational barriers across the implementation journey from Preadoption to Implementation. Initially the organizational focus is on understanding the value of clinical genomics (TDF code: belief about consequences) and setting the scene (TDF code: goals) before organizational (TDF codes: knowledge and belief about consequences) and clinician (TDF codes: belief about capability and intentions) willingness to adopt is apparent. Once at the stage of Implementation, leadership and clarity in organizational priorities (TDF codes: intentions, professional identity and emotion) that include clinical genomics are essential prerequisites to implementing clinical genomics in practice. Intuitive enablers were identified (e.g. ‘providing multiple opportunities for people to come on board) and mapped hypothetically to barriers.

Attention to date has centred on the barriers facing clinicians when introducing clinical genomics into practice. This paper uses a combination of implementation science theories to begin to unravel the organizational perspectives of implementing this complex health intervention.

This essay examines the issues that the ongoing revolution in biosciences and biotechnology pose to social science. A convenient frame for examining these issues is the framework of “thematic priorities” established by the British funding agency for social science, the Economic and Social Research Council (ESRC). These “thematic priorities” are used to identify major challenges and opportunities that currently confront social research. Though not constructed as part of a futures exercise, this framework proved useful for organising the issues that were generated from literature review and brainstorming, provided a stimulus to identify new issues, and was a useful filter for presenting results to the ESRC, which sponsored the study. This range of issues does not just call for interaction between natural and social scientists: there is also need for the sharing of knowledge and perspectives across diverse fields of social science. In order to help inform future research priorities, we need to move beyond the perspectives of single disciplines, and make sure that we do not simply emphasise those areas where social scientists have already been actively engaged. The study concludes clearly that there is a huge range of vital questions that social science needs to address if we are to understand, let alone bring more social intelligence to bear on shaping, the scientific and technological revolutions that are under way, and their broader social implications.

This chapter explores the rise in genetic approaches to health disparities at the turn of the twenty-first century.

Analysis of public health policies, genome project records, ethnography of project leaders and leading genetic epidemiologists, and news coverage of international projects demonstrates how the study of health disparities and genetic causes of health simultaneously took hold just as the new field of genomics and matters of racial inequality became a global priority for biomedical science and public health.

As the U.S. federal government created policies to implement racial inclusion standards, international genome projects seized the study race, and diseases that exhibit disparities by race. Genomic leaders made health disparities research a central feature of their science. However, recent attempts to move toward analysis of gene-environment interactions in health and disease have proven insufficient in addressing sociological contributors to health disparities. In place of in-depth analyses of environmental causes, pharmacogenomics drugs, diagnostics, and inclusion in sequencing projects have become the frontline solutions to health disparities.

The chapter argues that genetic forms of medicalization and racialization have taken hold over science and public health around the world, thereby engendering a divestment from sociological approaches that do not align with the expansion of genomic science. The chapter thus contributes to critical discussions in the social and health sciences about the fundamental processes of medicalization, racialization, and geneticization in contemporary society.

The expected growth of elders and chronically ill patients requires health insurers and health-care systems to shift from primarily focusing on the care of the sick to focusing both on care of the sick and on preventive health care. Public expectations for high-quality health care call for a new, more profound, and more actionable understanding of the healthy customer’s mind regarding health-promoting behaviors. Mind-Genomics may become the next big idea in health service. The relation between Mind-Genomics and data-driven personalized health plans is now being systematically explored. Some of the findings are reported in this research project.

Methodology: Respondents were 200 members of the Excellus American health fund. Based on measures of patient experience the authors created and tested concepts of messaging. The authors conducted a series of conjoint-based designed experiments to establish response patterns to our messaging. The authors analyzed data using Mind-Genomics, an empirical “micro-science” for discovering psychographic mind-sets and mapping motivating messages for healthy behaviors.

Results: The authors segmented patients by attitudes, perceptions, preferences, needs, and behaviors by their responses to messaging, thereby uncovering underlying psychographic mind-sets. The authors used the Personal Viewpoint Identifier to tag each person in the population by a sample mind-set and use the right messaging.

Discussion: To understand the mind of the patient regarding health plans, health funds may use the powerful tools of Mind-Genomics. Health insurers and health systems may implement Mind-Genomics as the next frontier of knowledge development to offer customized health plans, thus investing in preventive medicine.

Using a dynamic capabilities lens, this paper aims to study the impact of genomics generally and gene therapy specifically on the rare disease sector of the biopharmaceutical industry.

In this study, 24 genomics-based, rare disease-focused biopharma companies were studied and several variables were tested with respect to enterprise value growth. The companies were analyzed as a group of rare disease firms, as well as by size.

The authors found that number of employees, revenues, number of pipeline and marketed products and retained earnings are strongly correlated (in that order) with enterprise value in rare disease focused biopharma companies. These correlations seem to be weaker as a company’s market capitalization size decreases, indicating that there tends to be increasing returns to scale.

This study found that increasing rates of cumulative returns to enterprise value growth depends on accumulating knowledge-based employees and expanding product portfolios of disruptive genomics-based technologies for treating rare diseases. Aggregating skilled and innovative employees (especially in bigger companies) can be seen as a cumulative bolstering factor in leveraging dynamic capabilities which can be recognized, understood and transformed into commercial success (i.e. increasing returns in enterprise value). In other words, technology managers’ job is to manage not only the financial aspects of the technology but also human resources, asset configuration and strategic alliances efficiently toward faster and better innovation. Strong dynamic capabilities can be formed with the accumulation of experience, articulation and codification of knowledge and an adaptive ability to change the way they solve problems as their environment transforms.

This is the first study to demonstrate and measure a relationship between dynamic capabilities and enterprise value in genomics-based rare disease firms. Further, this study highlights the importance of building the capability and capacity to absorb expertise and accumulate knowledge for new product innovations and sustainable competitive advantage in industries characterized by disruptive innovation.

In February this year the sequence of the human genome was published, opening a new chapter in medicine. Soon genetic testing will be at the heart of diagnosis, epidemiology, drug development and even regenerative medicine. Before we are born there will be new opportunities to remedy genetic defects, and afterwards to make almost lifelong prognoses. The debate will intensify on the use of human embryos in medical research, while the prospect of human cloning will fascinate some scientists and horrify others. Europe needs to be in the vanguard of this new industrial revolution, but a host of ethical concerns must first be addressed – because genomics is as much about privacy as Petri dishes.

The Australian Government recognises an obligation to ensure that Aboriginal and Torres Strait Islanders (Australia’s First Peoples) are included in the integration of genomics into the healthcare system. First Peoples inclusion in this area requires going beyond general principles for First Peoples health research. This extra need exists for historical reasons as well as the need to maintain connections between patients, participants and communities and between the bio-specimens and data contributing to the resources underpinning genomics. The National Centre for Indigenous Genomics (NCIG) at the Australian National University in Canberra, Australia, has developed a framework that addresses these requirements through its dedicated First Peoples governance and enduring community engagement processes relating to stored heritage materials, data management and culturally agreed terms for collection preservation and potential use into the future. This chapter incorporates a First Peoples perspective on the NCIG by describing the practical application of ‘doing the right thing’, proceeding at ‘the pace of trust’, obtaining informed consent as part of enduring relationships, acknowledging cultural perspectives, understanding diversity of views and cultural practices within and between communities and respecting the need for community ownership and self-determined mobilisation of First Peoples involvement with research. This culturally appropriate methodology has been developed in partnership with individuals, family groups and community leaders, who are directly involved in genomic research. It provides a model for First Peoples to play an invested and sustaining role in the future development of genome science and precision medicine.

This study analyzes the rise of genome instability in the life sciences and traces the problematic of instability as it relates to the sociology of health. Genome instability is the study of how genomes change and become variable between generations and within organisms over the life span. Genome instability reflects a significant departure from the Platonic genome imagined during the Human Genome Project. The aim of this chapter is to explain and analyze research on copy number variation and somatic mosaicism to consider the implications of these sciences for sociologists interested in genomics.

This chapter draws on two multi-sited ethnographies of contemporary biomedical science and literature in the sociology of health, science, and biomedicine to document a shift in thinking about the genome from fixed and universal to highly variable and influenced by time and context.

Genomic instability has become a framework for addressing how genomes change and become variable between generations and within organisms over the life span. Instability is a useful framework for analyzing changes in the life sciences in the post-genomic era.

Genome instability requires life scientists to address how differences both within and between individuals articulate with shifting disease categories and classifications. For sociologists, these findings have implications for studies of identity, sociality, and clinical experience.

This is the first sociological analysis of genomic instability. It identifies practical and conceptual implications of genomic instability for life scientists and helps sociologists delineate new approaches to the study of genomics in the post-genomic era.