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Global Perspectives on Stem Cell Technologies pp 51–84Cite as

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Intersections of Technological and Regulatory Zones in Regenerative Medicine

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Abstract

This chapter situates contemporary debates over regenerative medicine governance within a broader framework, taking intersections with economic, political, and other kinds of technological zones into account. With the inherent complexities of regenerative medicine products, the advent of techniques such as gene editing and tissue organoids, and pragmatic problems of scaling-up cell manufacturing, conventional ways of thinking about and producing evidence are challenged. At the same time, the push to speed product approvals endures, but now in political and economic environments that include differing attitudes toward risk and patients’ roles in decision-making. The chapter highlights how crossing technological and political zones, data-driven approaches plus a return to observational data in particular are being incorporated into US regulatory law and product review.

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Notes

  1. 1.

    Evidence as produced by privileged EBM methods has not always been taken up in practice despite its promise of providing a more systematic, scientific basis for clinical decision-making (cf. Lambert 2006). More than a simple matter of behavior change and slow uptake of new ideas, Timmermans and Mauck (2005) position resistance from clinicians within the broader context of actual medical work practices, professionalism expectations, and institutional constraints in which clinicians practice.

  2. 2.

    There has been little guidance on the necessity of knowing specific mechanisms. The International Society for Stem Cell Research Guidelines of 2016 has vague instructions: Section 3.2.3 states that ‘complete understanding of the biological mechanisms at work after stem cell transplantation in a preclinical model is not a prerequisite to initiating human experimentation, especially in the case of serious and untreatable diseases’ and Section 3.2.3.1 states, ‘Before clinical testing, preclinical evidence … should ideally provide a mechanism of action … and demonstrate ability to modify disease or injury when applied in suitable animal systems’ (ISSCR 2016, emphasis added).

  3. 3.

    Because of the ability to test responses to adventitious agents, drug candidates, and environmental exposures, iPS cells are rapidly becoming a key research tool outside of therapeutic uses (Laustriat et al. 2010). This is likely to become a larger market than therapies.

  4. 4.

    See, for example, Canadian policy at http://publications.gc.ca/collections/Collection/CP22-78-2004E.pdf and the European Commission report at https://www.oecd.org/regreform/policyconference/46528683.pdf

  5. 5.

    The Patient Protection and Affordable Care Act (PL111-148 [2010]) is also known as the ACA or ‘Obamacare’, after President Obama.

  6. 6.

    As he later put it: ‘In the future, biology and medicine will increasingly become ‘digital sciences… We need to complete a national system of pre-designed, pre-populated, pre-positioned databases for open science, so researchers can literally log on to the world’s evidence base for biomedical and clinical research.…’

  7. 7.

    This aim has been restated in subsequent reports: ‘Improving quality and controlling costs requires moving from [an] unsustainable and flawed organizational arrangement to a system that gains knowledge from every care-delivery experience and is engineered to promote continuous improvement. In short, the nation needs a healthcare system that learns…’ (IOM 2013, p. 135).

  8. 8.

    Adaptive designs use interim findings to alter the course of a trial during its course, which may include modifying randomization (which would change the probability that a patient is assigned to a control or test arm), adjusting patient recruitment, or other decisions that would affect a patient’s treatment. These designs have been criticized for eliminating equipoise, diminishing statistical power, and potentially increasing bias, especially the possibility of a Type I error (e.g., rejection of a null hypothesis that is actually true).

  9. 9.

    Such approaches, however, require ready access to relatively sophisticated laboratory tests, including next-generation genome sequencing, which is unlikely to be accessible or affordable to many global sites.

  10. 10.

    The Roundtable has expanded working groups on value incentives, systems engineering, and digital health technology. Members include representatives from the National Institutes of Health, from the pharmaceutical and insurance industries, health economists, and physicians.

  11. 11.

    Insurers, of course, were very supportive of such linkages: data from medical records and claims data linked to clinical trials and registries data could be used to support decisions about which treatments to reimburse and at which rates.

  12. 12.

    Guidance for the public, industry, and CMS staff on Coverage with Evidence Development can be found at https://www.cms.gov/medicare-coverage-database/details/medicare-coverage-document-details.aspx?MCDId=27

  13. 13.

    Although computational tools are thought to distance the human’ there are nonetheless judgments about what to include or exclude in the making of algorithms that may reflect situated perspectives. There still may be sampling bias and problems with ontology (boyd and Crawford 2012).

  14. 14.

    The term ‘Big Data’ has been defined as data sets so large and complex as to strain the capacity of conventional information processing and storage technologies. Kitchin (2014) adds that it is scalable and exhaustive.

  15. 15.

    Morris is the scientific officer for Archimedes, a company using simulation models from clinical trials, health records, literature reviews, and more to make predictions about individual patients.

  16. 16.

    In many cases, data sharing will be allowed to proceed without express informed consent. These changes represent a significant departure from current policy, but for purposes of this chapter, the implications are that many uses of information from and about patients would be categorized as minimal risk and could be redefined as ‘operational studies’ rather than ‘research’, enabling third parties to access personal health information. Thus, the ubiquitous and continual collection of data ostensibly for research may be used for other purposes, such as cost efficiency or by for-profit entities for commercial purposes. The significant concerns over the collection, surveillance, and use of personal health information are discussed in Hogle (2016b).

  17. 17.

    PL 114-255 114th Congress. Discussing ‘valid scientific evidence’, Title III Subtitle C Section 3022 505F (b) amends the Food, Drug, and Cosmetic Act, adding the use of ‘real-world evidence’, defined as ‘data regarding the usage, potential benefits or risks, of a drug derived from sources other than randomized clinical trials’. Available at https://www.gpo.gov/fdsys/pkg/PLAW-114publ255/pdf/PLAW-114publ255.pdf

  18. 18.

    Computational techniques have become increasingly popular as a way to predict cytotoxicity, analyze pharmacodynamics, and more to inform regulatory requirements for risk modeling. More recently, stem cells are being used to screen genetic variants to do drug sensitivity and toxicity testing, disease modeling, and other applications. For example, induced pluripotent stem cells are grown in culture to the stage of small ‘organoids’ that mimic tissue in the body, then candidate drugs are introduced to test whether there is an adverse or beneficial response rather than administering to a whole organism. This is a sea change in thinking, since conventional experimental science would demand knowing how substances would interact in living, whole organisms rather than project potential responses based on testing in tissue-like composites in the lab.

  19. 19.

    Examples include Avandia, which lowered Hb A1C (an indicator of a patient’s blood glucose in the past two months) in diabetic patients but increased the rate of heart attacks.

  20. 20.

    The Healthcare Information and Management Systems Society, a major health information technology advocacy organization, lauds provisions that prevent software from health-tracking devices and smart phone apps from being FDA regulated and argues that eliminating barriers to sharing of personal health information as currently protected by the Health Information Portability and Accountability Act is a leap forward for health-data analysis. The Act also extends brand exclusivity for some drugs, delays entry for generics for others, and allows device makers to obtain third-party assessments if the design or materials used in products changes rather than provide new study data.

  21. 21.

    Although highly controversial, legislation promising accelerated access to unapproved treatments has been enacted in 38 US state legislatures as of this writing, and a federal-level bill has been proposed (Bateman-House et al. 2015; Richardson 2015).

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  1. Department of Medical History & Bioethics, School of Medicine & Public Health, University of Wisconsin–Madison, Madison, WI, USA

    Linda F. Hogle

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  1. Department of Anthropology and Sociology, Graduate Institute of International and Development Studies, Geneva, Switzerland

    Aditya Bharadwaj

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Hogle, L.F. (2018). Intersections of Technological and Regulatory Zones in Regenerative Medicine. In: Bharadwaj, A. (eds) Global Perspectives on Stem Cell Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-63787-7_3

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