Section IIB - Widening the Lens

The sheer diversity of topics in health research makes for a daunting task in the development, establishment, and application of oversight mechanisms and various methods of governance. The authors of this section illustrate how this task is made even more complex by emerging technologies, applications and context, as well as the presence of a variety of actors both in the research and the governance landscape. Nevertheless, key themes emerge, and these sometimes trouble existing paradigms and parameters, and shift and widen our regulatory lenses. A key anchor is the relationship between governance and time: be it the urgent nature of research conducted in global health emergencies; the appropriate weight given to historical data in establishing evidence, anticipating future risk, benefit or harm; or the historical and current forces that have shaped regulatory structures as we meet them today. The perspectives explored in this section can be seen to illustrate different kinds of liminality, which result in regulatory complexity but also offer potential for new kinds of imaginaries, norms and processes.

A first kind of shift in lens is created by the nature of research contexts: for example, whether research is carried out in labs, in clinical settings, traditional healing encounters or, indeed, in a pandemic. These spaces might be the site where values, interests or rules conflict, or they might be characterised by the absence of regulation. Additional tension might be brought about in the interaction of what is being regulated, with how it is being regulated: emerging interventions in already established processes, traditional interventions in more recently developed but strongly established paradigms, or marginal interventions precipitated to the centre by outside forces (crises, economic profit, unexpected findings, imminent or certain injury or death). These shifts give rise to considerations of flexibility and resilience in regulation, of the legitimacy and authority of different actors, and the epistemic soundness in the development and deployment of innovative, experimental, or less established practices.

In Chapter 28, Ho addresses the key concept of risk, and its role within the governance of artificial intelligence (AI) and machine learning (ML) as medical devices. Using the illustration of AI/ML as clinical decision support in the diagnosis of diabetic retinopathy, the author situates their position in qualified opposition to those who perceive governance as an impediment to development and economic gain and those who favour more oversight of AI/ML. In managing such algorithms as risk objects in governance, Ho advocates a governance structure that re-characterises risk as a form of iterative learning process, rather than a rule-based one-time evaluation and regulatory approval based on the quantification of future risk.

The theme of regulation as obstacle is also explored in the following chapter (Chapter 29) by Lipworth et al., in the context of autologous mesenchymal stem cell-based interventions. Here, too, the perspective of the authors is set against those who see traditional governance and translational pathways as an impediment to addressing life-threatening and debilitating illnesses. They also resist the reimagination of healthcare as a marketplace (complete with aggressive marketing and dubious claims) where the patient is seen as a consumer, and the decision to access emerging and novel (unproven and potentially risky) interventions merely as a matter of shared decision-making between patient and clinician. The authors recommend the strengthening a multipronged governance framework, which includes professional regulation, marketplace regulation, regulation of therapeutic products, and research oversight.

In Chapter 30, Haas and Cloatre also explore the difficult task of aligning interventions and products within established regulatory and translational pathways. Here, however, the challenge is not novel or emerging interventions, but traditional or non-conventional medicine, which challenges establishes governance frameworks based on the biomedical paradigm, and yet which millions of patients worldwide rely on as their primary form of healthcare. Here, uncertainty relates to the epistemic legitimacy of non-conventional forms of knowledge gathering. Actors in conflict with established epistemic processes are informed by historical and contextual evidence and practices that far predate the establishment of current frameworks. Traditional and non-conventional interventions are, nevertheless, pushed towards hegemonic governance pathways, often in the ‘scientised and commercial’ forms, in order to gain recognition and legitimacy.

When considering pathways to legitimacy, a key role is played by ethics, in its multiple forms. In Chapter 31, Pickersgill explores ethics in its multiple forms through the eyes of neuroscience researchers, who in their daily practice experience the ethical dimensions of neuroscience and negotiate ethics as a regulatory tool. Ethics can be seen as obstacle to good science, and the (institutional) ethics of human research is often seen as prone to obfuscation and in lack of clear guidance. This results in novel practices and norms within the community, which are informed by a commitment to doing the right thing and by institutional requirements. In order to minimise potential subversion (even well-meant) of ethics in research, Pickersgill advocates the development of governance that arises not only from collaborations between scientists and regulators but also those who can act as critical friends to both of these groups of actors.

Ethics guidance and ethical practices are also explored by Ganguli-Mitra and Hunt (Chapter 32), this time in the context of research carried out in global health emergencies (GHEs). These contexts are characterised by various factors that complicate ethical norms and practices, as well as trouble existing frameworks and paradigms. GHEs are sites of multiple kinds of practices (humanitarian, medical, public health, development) and of multiple actors, whose goals and norms of conduct might be in conflict in a context that is characterised by urgency and high risk of injury and death. Using the examples of recent emergencies, the authors explore the changing nature of ethics and ethical practices in extraordinary circumstances.

In the final chapter of this section (Chapter 33), Arzuaga offers an illustration of regulatory development, touching upon the many actors, values, interests, and forces explored in the earlier chapters. Arzuaga reports on the governance of advanced therapeutic medicinal products (ATMPs) in Argentina, moving from a situation of non-intervention on the part of the state, to the establishment of a governance framework. Here, the role of hard and soft law as adding both resilience and flexibility to regulation is explored, fostering innovation without abdicating ethical concerns. Arzuaga describes early, unsuccessful attempts at regulating stem cell-based interventions, echoing the concerns presented by Lipworth et al., before exploring a more promising exercise in legal foresighting, which included a variety of actors and collaboration, as well a combination of top-down models and bottom-up, iterative processes.

28 When Learning Is Continuous Bridging the Research–Therapy Divide in the Regulatory Governance of Artificial Intelligence as Medical Devices

Calvin W. L. Ho

28.1 Introduction

The regulatory governance of Artificial Intelligence and Machine Learning (AI/ML) technologies as medical devices in healthcare challenges the regulatory divide between research and clinical care, which is typically of pharmaceutical products. This chapter considers the regulatory governance of an AI/ML clinical decision support (CDS) software for the diagnosis of diabetic retinopathy as a ‘risk object’ by the Food and Drug Administration (FDA) in the United States (US). The FDA’s regulatory principles and approach may play an influential role in how other countries govern this and other software as a medical device (SaMD). The disruptions that AI/ML technologies can cause are well publicised in the lay and academic media alike, although the more serious ‘risks’ of harm are still essentially anticipatory. In some quarters, there is a prevailing sense that a ‘light-touch’ approach to regulatory governance should be adopted to ensure that the advancement of AI – particularly in ways that are expected to generate economic gain – should not be unduly burdened. Hence, in response to the question of whether regulation of AI is needed now, scholars like Chris Reed have responded with a qualified ‘No’. As Reed explains, the use of the technology in medicine is already regulated by the profession, and regulation will be adapted piecemeal as new AI technologies come into use anyway.¹ A ‘wait and see’ approach is likely to produce better long-term results than hurried regulation based on a very partial understanding of what needs to be regulated. It is also perhaps consistent with this mind-set that the commercial development and application of AI and AI-based technologies remain largely unregulated.

This chapter takes a different view on the issue, and argues that the response should be a qualified ‘Yes’ instead, partly because there is already an existing regulatory framework in place that may be adapted to meet anticipated challenges. As a ‘risk object’, the regulation of AI/ML medical devices cannot be understood and managed separately from a broader ‘risk culture’ within which it is embedded. Contrary to what an approach in ‘command-and-control’ suggests, regulatory governance of AI/ML medical devices should not be understood merely as the application of external forces to contain ills that must somehow be managed in order to derive the desired effects. Arguably, it is this limited conception of ‘risks’ and its relationship with regulation that give rise to liminality. As Laurie and others clearly explains,² a liminal space is created contemporaneously with the uncertainties generated by new and emerging technologies. Drawing on the works of Arnold van Gennep and Victor Turner, ‘liminality’ is presented as an analytic to engage with the processual and experiential dynamics of transitional and transformational inter-structural boundary or marginal spaces. It is itself an intermediary process in a three-part pattern of experience, that begins with separation from an existing order, and concludes with re-integration into a new world.³ Mapping liminal spaces and the changing boundaries entailed can help to highlight gaps in regulatory regimes.⁴

Risk-based evaluation is often a feature of such liminal spaces, and when they become sites for battles of power and values, ethical issues arise. Whereas liminality has been applied to account for human experiences within regulated spaces, this chapter considers the epistemic quality of ‘risks’ and its situatedness within regulatory governance as a discursive practice and as a matter of social reality. In this respect, regulation is not necessarily extrinsic to its regulatory object, but constitutive of it. Concerns about ‘risks’ from technological innovations and the need to tame them have been central to regulatory governance.⁵ Whereas governance has been a longstanding cultural phenomenon that relates to ‘the system of shared beliefs, values, customs, behaviours and artifacts that members of society use to cope with their world and with one another, and that are transmitted from generation to generation through learning’,⁶ it is the regulatory turn that is especially instructive. Here, regulatory response is taken to reduce the uncertainty and instability of mitigating potential risks and harms and by directing or influencing actors’ behaviour to accord with socially accepted norms and/or to promote desirable social outcomes, and regulation encompasses any instrument (legal or non-legal in character) that is designed to channel group behaviour.⁷ The high connectivity of AL/ML SaMDs that are capable of adapting to their digital environment in order to optimise performance suggests that the research agenda persists beyond what may be currently limited to the pilot or feasibility stages of medical device trials. If continuous risk-monitoring is required to support the use of SaMDs in a learning healthcare system, more robust and responsive regulatory mechanisms are needed, not less.⁸

28.2 AI/ML Software as Clinical Decision Support

In April 2018, the FDA granted approval for IDx-DR (DEN180001) to be marketed as the first AI diagnostic system that does not require clinician interpretation to detect greater than a mild level of diabetic retinopathy in adults diagnosed with diabetes.⁹ In essence, this SaMD applies an AI algorithm to analyse images of the eye taken with a retinal camera that are uploaded to a cloud server. A screening decision is made by the device as to whether the individual concerned is detected with ‘more than mild diabetic retinopathy’ and, if so, is referred to an eye care professional for medical attention. Where the screening result is negative, the individual will be rescreened in twelve months. IDx-DR was reviewed under the FDA’s De Novo premarket review pathway and was granted Breakthrough Device designation,¹⁰ as the SaMD is novel and of low to moderate risk. On the whole, the regulatory process did not detract substantially from the existing regulatory framework for medical devices in the USA. A medical device is defined broadly to include low-risk adhesive bandages to sophisticated implanted devices. In the USA, a similar approach is adopted in the definition of the term ‘device’ in Section 201(h) of the Federal Food, Drug and Cosmetic Act.¹¹

For regulatory purposes, medical devices are classified based on their intended use and indications for use, degree of invasiveness, duration of use, and the risks and potential harms associated with their use. At the classification stage, a manufacturer is not expected to have gathered sufficient data to demonstrate that its proposed product meets the applicable marketing authorisation standard (e.g. data demonstrating effectiveness).  Therefore, the focus of the FDA’s classification analysis is on how the product is expected to achieve its primary intended purposes.¹² The FDA has established classifications for approximately 1700 different generic types of devices and grouped them into sixteen medical specialties referred to as ‘panels’. Each of these generic types of devices is assigned to one of three regulatory classes based on the level of control necessary to assure the safety and effectiveness of the device. The class to which the device is assigned determines, among other things, the type of premarketing submission/application required for FDA clearance to market. All classes of devices are subject to General Controls,¹³ which are the baseline requirements of the FD&C Act that apply to all medical devices. Special Controls are regulatory requirements for Class II devices, and are usually device-specific and include performance standards, postmarket surveillance, patient registries, special labelling requirements, premarket data requirements and operational guidelines. For Class III devices, active regulatory review in the form of premarket approval is required (see Table 28.1).

Table 28.1. FDA classification of medical devices by risks

Class	Risk	Level of regulatory controls	Whether clinical trials required	Examples
I	Low	General	No	Gauze, adhesive bandages, toothbrush
II	Moderate	General and special	Maybe	Suture, diagnostic X-rays
III	High	General and premarket approval	Yes	Pacemakers, implantable defibrillators, spinal cord stimulators

Clinical trials of medical devices, where required, are often non-randomised, non-blinded, do not have active control groups, and lack hard endpoints, since randomisation and blinding of patients or physicians for implantable devices will in many instances be technically challenging and ethically unacceptable.¹⁴ Table 28.2 shows key differences between clinical trials of pharmaceuticals in contrast to medical devices.¹⁵ Class I and some Class II devices may be introduced into the US market without having been tested in humans through an approval process that is based on predicates. Through what is known as the 510(k) pathway, a manufacturer needs to show that its ‘new’ device is at least as safe and effective as (or substantially equivalent to) a legally marketed predicate device (as was the case for IDx-DR).¹⁶

Table 28.2. Comparing pharmaceutical trial phases and medical device trial stages

Pharmaceuticals			Medical devices
Phase	Participants	Purpose	Stage	Participants	Purpose
0 (Pilot/exploratory ; not all drugs undergo this phase)	10–15 participants with disease or condition	Test very small (subtherapeutic) dosage to study effects and mechanisms	Pilot/early feasibility/ first-in-human	10–15 participants with disease or condition	Collect preliminary safety and performance data to guide development
I (Safety and toxicity)	10–100 healthy participants	Test safety and tolerance Determine dosing and major adverse effects	Feasibility	20–30 participants with disease or condition	Assess safety and efficacy of near-final or final device design Guides design of pivotal study
II (Safety and effectiveness)	50–200 participants with disease or condition	Test safety and effectiveness Confirm dosing and major adverse effects
III (Clinical effectiveness)	>100–1000 participants with disease or condition	Test safety and effectiveness Determine drug–drug interaction and minor adverse effects	Pivotal	>100–300 participants with disease or condition	Establish clinical efficacy, safety and risks
IV (Post-approval study)	>1000	Collect long-term data and adverse effects	Post-approval study	>1000	Collect long-term data and adverse effects

The nature of regulatory control is changing; regulatory control does not arise solely through the exertion of regulatory power over a regulated entity but also acts intrinsically from within the entity itself. It is argued that risk-based regulation draws on different knowledge domains to constitute the AI/ML algorithm as a ‘risk object’, and not merely to subjugate it. Risk objectification renders the regulated entity calculable. Control does not thereby arise because the regulated entity behaves strictly in adherence to specific commands but rather because of the predictability of its actions. Where risk cannot be precisely calculated however, liminal spaces may help to articulate various ‘scenarios’ with different degrees of plausibility. These liminal spaces are thereby themselves a means by which uncertainty is managed. Typically, owing to conditions that operate outside of direct regulatory control, liminal spaces can either help to maintain a broader regulatory space to which they are peripheral, or contribute to its re-configuration through a ‘domaining effect’. This aspect will be considered in the penultimate section of this chapter.

28.3 Re-embedding Risk and a Return to Sociality

The regulatory construction of IDx-DR as a ‘risk object’ is accomplished by linking the causal attributes of economic and social risks, and risks to human safety and agency, to its constitutive algorithms reified as a medical device.¹⁷ This ‘risk object’ is made epistemically ‘real’ when integrated through a risk discourse, by which risk attributions and relations have come to define identities, responsibilities, and socialities. While risk objectification has been effective in paving a way forward to market approval for IDx-DR, this technological capability is pushed further into liminality. The study that supported the FDA’s approval was conducted under highly controlled conditions where a relatively small group of carefully selected patients had been recruited to test a diagnostic system that had a narrow usage criteria.¹⁸ It is questionable whether the AI/ML feature was itself tested, since the auto-didactic aspect of the algorithm was locked prior to the clinical trial, which greatly constrained the variability of the range of outputs.¹⁹ At this stage, IDx-DR is not capable of evaluating the most severe forms of diabetic retinopathy that requires urgent ophthalmic intervention. However, IDx-DR is capable of ML, which is a subset of AI and refers to a set of methods that have the ability to automatically detect patterns in data in order to predict future data trends or for decision-making under uncertain conditions.²⁰ Deep learning (DL) is in turn a subtype of ML (and a subfield of representation learning) that is capable of delivering a higher level of performance, and does not require a human to identify and compute the discriminatory features for it. From the 1980s onwards, DL software has been applied in computer-aided detection systems, and the field of radiomics (a process that extracts large number of quantitative features from medical images) is broadly concerned with computer-aided diagnosis systems, where DL has enabled the use of computer-learned tumour signatures.²¹ It has the potential to detect abnormalities, make differential diagnoses and generate preliminary radiology reports in the future, but only a few methods are able to manage the wide range of radiological presentations of subtle disease states. In the foreseeable future, unsupervised AI/ML will test the limits of conventional means of regulation of medical devices.²² The challenges to risk assessment, management and mitigation will be amplified as AI/ML medical devices change rapidly and become less predictable.²³

Regulatory conservatism reflects a particular positionality and related interests that are at stake. For many high-level policy documents on AI, competitive advantage for economic gain is a key interest.²⁴ This position appears to support a ‘light touch’ approach to regulatory governance of AI in order to sustain technological development and advance national economic interests. If policymakers, as a matter of socio-political construction, consider regulation as impeding technological development, then regulatory governance is unlikely to see meaningful progression. Not surprisingly, the private sector has had a dominant presence in defining the agenda and shape of AI and related technologies. While this is not in and of itself problematic, the narrow regulatory focus and absence of broader participation could be. For instance, it is not entirely clear to what extent the development of AI/ML algorithms is determined primarily by sectorial interests.²⁵

Initial risk assessment is essentially consequentialist in its focus on intended use of the SaMD to achieve particular clinical outcomes. Risk characterisation is abstracted to two factors:²⁶ (1) significance of the information provided by the SaMD to the healthcare decision; and (2) state of the healthcare situation or condition. Risk is thereby derived from ‘objective’ information that is provided by the manufacturer on intended use of the information provided by the SaMD in clinical management. Such use may be significant in one of three ways: (1) to treat or to diagnose, (2) to drive clinical management or (3) to inform clinical management. The significance of an intended use is then associated with a healthcare situation or condition (i.e. critical, serious or non-serious). Schematically, Table 28.3 presents the risk characterisation framework based on four different levels of impact on the health of patients or target populations. Level IV of the framework (e.g. SaMD that performs diagnostic image analysis for making treatment decisions in patients with acute stroke, or screens for mutable pandemic outbreak that can be highly communicable through direct contact or other means) relates to the highest impact while Level I (e.g. SaMD that analyses optical images to guide next diagnostic action of astigmatism) relates to the lowest.²⁷

Table 28.3. Risk characterisation framework for software as a medical device

State of healthcare situation or condition	Significance of information provided by SaMD to healthcare decision
	Treat or diagnose	Drive clinical management	Inform clinical management
Critical	IV	III	II
Serious	III	II	I
Non-serious	II	I	I

To counter the possible deepening of regulatory impoverishment, regulatory governance as concept and process will need to re-characterise risk management as a form of learning and experimentation rather than rule-based processes, thus placing stronger reliance on human capabilities to imagine alternative futures instead of quantitative ambitions to predict the future. Additionally, a regulatory approach that is based on total project lifecycle needs to be taken up. This better accounts for modifications that will be made to the device through real-world learning and adaptation. Such adaptation enables a device to change its behaviour over time based on new data and optimise its performance in real time with the goal of improving health outcomes. As the FDA’s conventional review procedures for medical devices discussed above are not adequately responsive to assess adaptive AI/ML technologies, the FDA has proposed for a premarket review mechanism to be developed.²⁸ This mechanism seeks to introduce a predetermined change control plan in the premarket submission, in order to give effect to the risk categorisation and risk management principles, as well as the total product lifecycle approach, of the IMDRF. The plan will include the types of anticipated modifications (or pre-specifications) and associated methodology that is used to implement the changes in a controlled manner while allowing risks to patients to be managed (referred to as Algorithm Change Protocol). In essence, the proposed changes will place on manufacturers a greater responsibility of monitoring the real-world performance of their medical devices and to make available the performance data through periodic updates on what changes were made as part of the approved pre-specifications and the Algorithm Change Protocol. In totality, these proposed changes will enable the FDA to evaluate and monitor, collaboratively with manufacturers, an AI/ML software as a medical device from its premarket development to postmarket performance. The nature of the FDA’s regulatory oversight will also become more iterative and responsive in assessing the impact of device optimisation on patient safety.

As the IMDRF also explains, every SaMD will have its own risk category according to its definition statement even when it is interfaced with other SaMD, other hardware medical devices or used as a module in a larger system. Importantly, manufacturers are expected to have an appropriate level of control to manage changes during the lifecycle of the SaMD. The IMDRF labels any modifications made throughout the lifecycle of the SaMD, including its maintenance phase, as ‘SaMD Changes’.²⁹ Software maintenance is in turn defined in terms of post-marketing modifications that could occur in the software lifecycle processes identified by the International Organization for Standardization.³⁰ It is generally recognised that testing of software is not sufficient to ensure safety in its operation. Safety features need to be built into the software at the design and development stages, and supported by quality management and post marketing surveillance after the SaMD has been installed. Post market surveillance includes monitoring, measurement and analysis of quality data through logging and tracking of complaints, clearing technical issues, determining problem causes and actions to address, identify, collect, analyse and report on critical quality characteristics of products developed. However, monitoring software quality alone does not guarantee that the objectives for a process are being achieved.³¹

As a concern of Quality Management System (QMS), the IMDRF requires that maintenance activities preserve the integrity of the SaMD without introducing new safety, effectiveness, performance and security hazards. It recommends that a risk assessment, including considerations in relation to patient safety and clinical environment and technology and systems environment, should be performed to determine if the changes affect the SaMD categorisation and the core functionality of SaMD as set out in its definition statement. The proposed QMS complements the risk categorisation framework through its goal of incorporating good software quality and engineering practices into the device. Principles underscoring QMS are set out in terms of organisational support structure, lifecycle support processes, and a set of realisation and use processes for assuring safety, effectiveness and performance. These principles have been endorsed by the FDA in its final guidance to describe an internally agreed upon understanding (among regulators) of clinical evaluation and principles for demonstrating the safety, effectiveness and performance of the device, and activities that manufacturers can take to clinically evaluate their device.³²

28.4 Regulatory Governance as Participatory Learning System

In this penultimate section of this chapter, it is argued that the regulatory approach considered in the preceding sections is intended to support a participatory learning system comprising at least two key features: (1) a platform and/or mechanisms that enable constructive engagement with, and participation of, members of society; and (2) the means by which a common fund of knowledges (to be explained below) may be pooled to generate an anticipatory knowledge that could guide collective action. In some instances, institutionalisation could advance this agenda, but it is beyond the scope of this manuscript to examine this possibility to a satisfactory degree.

There is a diverse range of modalities through which constituents of a society engage in collaborative learning. As Annelise Riles’s PAWORNET illustrates, each modality has its own goals, character, strengths and limitations. In her study, Riles observes that networkers did not understand themselves to share a set of values, interests or culture.³³ Instead, they understood themselves to be sharing their involvement in a certain network that was a form of institutionalised association devoted to information sharing. What defined networkers most of all was the fact that they were personally and institutionally connected or knowledgeable about the world of specific institutions and networks. In particular, it was the work of creating documents, organising conferences or producing funding proposals that generated a set of personal relations that drew people together and also created divisions of its own. In the author’s own study,³⁴ ethnographic findings illustrate how the ‘publics’ of human stem cell research and oocyte donation were co-produced with an institutionalised ‘bioethics-as-public-policy’ entity known as the Bioethics Advisory Body. In that context, the ‘publics’ comprised institutions and a number of individuals – often institutionally connected – that represented a diverse set of values, interests and perhaps cultures (construed in terms of their day-to-day practices in the least). These ‘publics’ resemble a network in a number of ways. They were brought into a particular set of relationship within a deliberative space created mainly by the consultation papers and reinforced through a variety of means that included public meetings, conferences, and feedback sessions. Arguably, even individual feedback from a public outreach platform known as ‘REACH’ encompassed a certain kind of pre-existing (sub-) network that has been formed with a view to soliciting relatively more spontaneous and independent, uninvited forms of civil participatory action. But this ‘network’ is not a static one. It varied with, but was also shaped by, the broader phenomenon of science and expectations as to how science ought to be engaged. In this connection, Riles’s observation is instructive: ‘It is not that networks “reflect” a form of society, therefore, nor that society creates its artifacts … Rather, it is all within the recursivity of a form that literally speaks about itself’.³⁵

A ‘risk culture’ that supports learning and experimentation rather than rule-based processes must embed the operation of AI and related technologies as ‘risk objects’ within a common fund of knowledges. Legal processes are inherent to understanding the risk, such as that of a repeat sexual offence under ‘Megan’s Law’, which encompasses the US community notification statutes relating to sexual offenders.³⁶ Comprising three tiers, this risk assessment process determines the scope of community notification. In examining the constitutional basis of Megan’s Law, Mariana Valverde et al. observe that ‘the courts have emphasised the scientific expertise that is said to be behind the registrant risk assessment scale (RRAS) in order to argue that Megan’s Law is not a tool of punishment but rather an objective measure to regulate a social problem’.³⁷ However, reliance on Megan’s Law as grounded in objective scientific knowledge has given rise to an ‘intermediary knowledge in which legal actors – prosecutors and judges – are said not only to be more fair but even more reliable and accurate in determining a registrant’s risk of re-offence’.³⁸ In this, the study also illustrates a translation from scientific knowledge and processes to legal ones, and how the ‘law’ may be cognitively and normatively open.

Finally, the articulation of possible harms and dangers as ‘risks’ involves the generation of ‘anticipatory knowledge’, which is defined as ‘social mechanisms and institutional capacities involved in producing, disseminating, and using such forms [as] … forecasts, models, scenarios, foresight exercises, threat assessments, and narratives about possible technological and societal futures’.³⁹ Like Ian Hacking’s ‘looping effect’, anticipatory knowledge is about knowledge-making about the future, and could operate as a means to gap-filling. The study by Hugh Gusterson of the Reliable Replacement Warhead (RRW) program is illustrative of this point, where US weapons laboratories could design new and highly reliable nuclear weapons that are safe to manufacture and maintain.⁴⁰ Gusterson shows that struggle over the RRW Program, initiated by the US Congress in 2004, occurred across four intersecting ‘plateaus of nuclear calculations’ – geopolitical, strategic, enviropolitical, and technoscientific – each with its own contending narratives of the future. He indicates that ‘advocates must stabilise and align anticipatory knowledge from each plateau of calculation into a coherent-enough narrative of the future in the face of opponents seeking to generate and secure alternative anticipatory knowledges’.⁴¹ Hence the interconnectedness of the four plateaus of calculation, including the trade-offs entailed, was evident in the production of anticipatory knowledge vis-à-vis the RRW program. In addition, the issues of performativity and ‘social construction of ambiguity’ were also evident. Gusterson observes that being craft items, no two nuclear weapons are exactly alike. However, the proscription of testing through detonation meant that both performativity and ambiguity over reliability became matters of speculation, determined through extrapolation from the past to fill knowledge ‘gaps’ in the present and future. This attempt at anticipatory knowledge creation also prescribed a form that the future was to take. Applying a similar analysis from a legal standpoint, Graeme Laurie and others explain that foresighting as a means of devising anticipatory knowledge is neither simple opinion surveying nor mere public participation.⁴² It must instead be directed at the discovery of shared values, the development of shared lexicons, the forging of a common vision of the future and the taking of steps to realise the vision with the understanding that this is being done from a position of partial knowledge about the future. As we have considered earlier on in this chapter, this visionary account captures the approach that has been adopted by the IMDRF impressively well.

28.5 Conclusion

Liminality highlights the need for a processual-oriented mode of regulation in order to recognise the flexibility and fluidity of the regulatory context (inclusive of its objects and subjects) and the need for iterative interactions, as well as to possess the capacity to provide non-directive guidance.⁴³ If one considers law as representing nothing more than certainty, structure and directed agency, then we should rightly be concerned as to whether the law can envision and support the creation of genuinely liminal regulatory spaces, which is typified by uncertainty, anti-structure and an absence of agency.⁴⁴ The crucial contribution of regulatory governance however, is its conceptualisation of law as an epistemically open enterprise, and in respect of which learning and experimentation are possible.

29 The Oversight of Clinical Innovation in a Medical Marketplace

Wendy Lipworth , Miriam Wiersma , Narcyz Ghinea , Tereza Hendl , Ian Kerridge , Tamra Lysaght , Megan Munsie , Chris Rudge , Cameron Stewart and Catherine Waldby

29.1 Introduction

Clinical innovation is ubiquitous in medical practice and is generally viewed as both necessary and desirable. While innovation has been the source of considerable benefit, many clinical innovations have failed to demonstrate evidence of clinical benefit and/or caused harm. Given uncertainty regarding the consequences of innovation, it is broadly accepted that it needs some form of oversight. But there is also pushback against what is perceived to be obstruction of access to innovative interventions. In this chapter, we argue that this pushback is misguided and dangerous – particularly because of the myriad competing and conflicting interests that drive and shape clinical innovation.

29.2 Clinical Innovation and Its Oversight

While the therapeutics lifecycle is usually thought of as one in which research precedes clinical application, it is common for health professionals to offer interventions that differ from standard practice, and that have either not (yet) been shown to be safe or effective or have been shown to be safe but not yet subjected to large phase 3 trials. This practice is often referred to as ‘clinical innovation’.¹ The scope of clinical innovation is broad, ranging from minor alterations to established practice – for example using a novel suturing technique – to more significant departures from standard practice – for example using an invasive device that has not been formally tested in any population.

For the most part, clinical innovation is viewed as necessary and desirable. Medicine has always involved the translation of ideas into treatment and it is recognised that ideas originate in the clinic as well as in the research setting, and that research and practice inform each other in an iterative manner.² It is also recognised that the standard trajectory of research followed by health technology assessment, registration and subsidisation may be too slow for patients with life-limiting or debilitating diseases and that clinical innovation can provide an important avenue for access to novel treatments.³ There are also limitations to the systems that are used to determine what counts as ‘standard’ practice because it is up to – usually commercial – sponsors to seek formal registration for particular indications.⁴

While many clinical innovations have positively transformed medicine, others have failed to demonstrate evidence of clinical benefit,⁵ or exposed patients to considerable harm – for example, the use of transvaginal mesh for the treatment of pelvic organ prolapse.⁶ Many innovative interventions are also substantially more expensive than traditional treatments,⁷ imposing costs on both patients and health systems. It is therefore broadly accepted that innovation requires some form of oversight. In most jurisdictions, oversight of innovation consists of a combination of legally based regulations and less formal governance mechanisms. These, in turn, can be focused on:

1. 1. the oversight of clinical practice by professional organisations, medical boards, healthcare complaints bodies and legal regimes;

2. 2. the registration of therapeutic products by agencies such as the US Food and Drug Administration, the European Medicines Agency and Australia’s Therapeutic Goods Administration;

3. 3. consumer protection, such as laws aimed at identifying and punishing misleading advertising; and

4. 4. the oversight of research when innovation takes place in parallel with clinical trials or is accompanied by the generation of ‘real world evidence’ through, for example, clinical registries.

The need for some degree of oversight is relatively uncontroversial. But there is also pushback against what is perceived to be obstruction of access to innovative interventions.⁸ There are two main arguments underpinning this position. First, it is argued that existing forms of oversight create barriers to clinical innovation. Salter and colleagues, for example, view efforts to assert external control over clinical innovation as manifestations of conservative biomedical hegemony that deliberately hinders clinical innovation in favour of more traditional translational pathways.⁹ It has also been argued that medical negligence law deters clinical innovation¹⁰ and that health technology regulation is excessively slow and conservative, denying patients the ‘right to try’ interventions that have not received formal regulatory approval.¹¹

Second, it is argued that barriers are philosophically and politically inappropriate on the grounds that patients are not actually ‘patients’, but rather ‘consumers’. According to these arguments, consumers should be free to decide for themselves what goods and services they wish to purchase without having their choices restricted by regulation and governance systems – including those typically referred to as ‘consumer’ (rather than ‘patient’) protections. Following this line of reasoning, Salter and colleagues¹² argue that decisions about access to innovative interventions should respect and support ‘the informed health consumer’ who:

assumes she/he has the right to make their own choices to buy treatment in a health care market which is another form of mass consumption…¹³

and who is able to draw on:

a wide range of [information] sources which include not only the formally approved outlets of science and state but also the burgeoning information banks of the internet.¹⁴

There are, however, several problems with these arguments. First, there is little evidence to support the claim that there is, in fact, an anti-innovative biomedical hegemony that is creating serious barriers to clinical innovation. While medical boards can censure doctors for misconduct, and the legal system can find them liable for trespass or negligence, these wrongs are no easier to prevent or prove in the context of innovation than in any other clinical context. Product regulation is similarly facilitative of innovation, with doctors being free to offer interventions ‘off-label’ and patients being allowed to apply for case-by-case access to experimental therapies. The notion that current oversight systems are anti-innovative is therefore not well founded.

Second, it is highly contestable that patients are ‘simply’ consumers – and doctors are ‘simply’ providers of goods and services – in a free market. For several reasons, healthcare functions as a very imperfect market: there is often little or no information available to guide purchases; there are major information asymmetries – exacerbated by misinformation on the internet; and patients may be pressured into accepting interventions when they have few, if any, other therapeutic options.¹⁵ Furthermore, even if patients were consumers acting in a marketplace, it would not follow that the marketplace should be completely unregulated, for even the most libertarian societies have regulatory structures in place to prevent bad actors misleading people or exploiting them financially (e.g. through false advertising, price fixing or offering services that they are unqualified to provide).

This leaves one other possible objection to the oversight of clinical innovation – that patients are under the care of professionals who are able to collaborate with them in making decisions through shared decision-making. Here, the argument is that innovation (1) should not be overseen because it is an issue that arises between a doctor and a patient, and (2) does not need to be overseen because doctors are professionals who have their patients’ interests at heart. These are compelling arguments because they are consistent with both the emphasis on autonomy in liberal democracies and with commonly accepted ideas about professionals and their obligations.

Two objections can, however, be raised. First, these arguments ignore the fact that professionalism is concerned not only with patient well-being but also with commitments to the just distribution of finite resources, furthering scientific knowledge and maintaining public trust.¹⁶ The second problem with these arguments is that they are premised on the assumption that all innovating clinicians are consistently alert to their professional obligations and willing to fulfil them. Unfortunately, this assumption is open to doubt. To illustrate this point, we turn to the case of autologous mesenchymal stem cell-based interventions.

29.3 The Case of Autologous Mesenchymal Stem Cell Interventions

Stem cell-based interventions are procedures in which stem cells – cells that have the potential to self-replicate and to differentiate into a range of different cell types – or cells derived from stem cells are administered to patients for therapeutic purposes. Autologous stem cell-based interventions involve administering cells to the same person from whom they were obtained. The two most common sources of such stem cells are blood and bone marrow (haematopoietic) cells and connective tissue (mesenchymal) cells.

Autologous haematopoietic stem cells are extracted from blood or bone marrow and used to reconstitute the bone marrow and immune system following high dose chemotherapy. Autologous mesenchymal cells are extracted most commonly from fat and then injected – either directly from the tissue extracts or after expansion in the laboratory – into joints, skin, muscle, blood stream, spinal fluid, brain, eyes, heart and so on, in order to ‘treat’ degenerative or inflammatory conditions. The hope is that because mesenchymal stem cells may have immunomodulatory properties they may support tissue regeneration.

The use of autologous haematopoietic stem cells is an established standard of care therapy for treating certain blood and solid malignancies and there is emerging evidence that they may also be beneficial in the treatment of immunological disorders, such as multiple sclerosis and scleroderma. In contrast, evidence to support the use of autologous mesenchymal stem cell interventions is weak and limited to only a small number of conditions (e.g. knee osteoarthritis).¹⁷ And even in these cases, it is unclear what the precise biological mechanism is and whether the cells involved should even be referred to as ‘stem cells’¹⁸ (we use this phrase in what follows for convenience).

Despite this, autologous mesenchymal stem cell interventions (henceforth AMSCIs) are offered for a wide range conditions for which there is no evidence of effectiveness, including spinal cord injury, motor neuron disease, dementia, cerebral palsy and autism.¹⁹ Clinics offering these and other claimed ‘stem cell therapies’ have proliferated globally, primarily in the private healthcare sector – including in jurisdictions with well-developed regulatory systems – and there are now both domestic markets and international markets based on stem cell tourism.²⁰

While AMSCIs are relatively safe, they are far from risk-free, with harm potentially arising from the surgical procedures used to extract cells (e.g. bleeding from liposuction), the manipulation of cells outside of the body (e.g. infection) and the injection of cells into the bloodstream (e.g. immunological reactions, fever, emboli) or other tissues (e.g. cyst formation, microcalcifications).²¹ Despite these risks, many of the practitioners offering AMSCIs have exploited loopholes in product regulation to offer these interventions to large numbers of patients.²² To make matters worse, these interventions are offered without obvious concern for professional obligations, as evident in aggressive and misleading marketing, financial exploitation and poor-quality evidence-generation practices.

First, despite limited efficacy and safety, AMSCIs are marketed aggressively through clinic websites, advertisements and appearances in popular media.²³ This is inappropriate both because the interventions being promoted are experimental and should therefore be offered to the minimum number of patients outside the context of clinical trials, and because marketing is often highly misleading. In some cases, this takes the form of blatant misinformation – for example, claims that AMSCIs are effective for autism, dementia and motor neuron disease. In other cases, consumers are misled by what have been referred to as ‘tokens of legitimacy’. These include patient testimonials, references to incomplete or poor-quality research studies, links to scientifically dubious articles and conference presentations, displays of certification and accreditation from unrecognised organisations, use of meaningless titles such as ‘stem cell physician’ and questionable claims of ethical oversight. Advertising of AMSCIs is also rife with accounts of biological processes that give the impression that autologous stem cells are entirely safe – because they come from the patient’s own body – and possess almost magical healing qualities.²⁴

Second, AMSCIs are expensive, with patients paying thousands of dollars (not including follow-up care or the costs associated with travel).²⁵ In many cases, patients take drastic measures to finance access to stem cells, including mortgaging their houses and crowd-sourcing funding from their communities. Clinicians offering AMSCIs claim that such costs are justified given the complexities of the procedures and the lack of insurance subsidies to pay for them.²⁶ However, the costs of AMSCIs seem to be determined by the business model of the industry and by a determination of ‘what the market will bear’ – which in the circumstances of illness, is substantial. Furthermore, clinicians offering AMSCIs also conduct ‘pay-to-participate’ clinical trials and ask patients to pay for their information to be included in clinical registries. Such practices are generally frowned upon as they exacerbate the therapeutic misconception and remove any incentive to complete and report results in a timely manner.²⁷

Finally, contrary to the expectation that innovating clinicians should actively contribute to generating generalisable knowledge through research, clinics offering AMSCIs have proliferated in the absence of robust clinical trials.²⁸ Furthermore, providers of AMSCIs tend to overstate what is known about efficacy²⁹ and to misrepresent what trials are for, arguing that they simply ‘measure and validate the effect of (a) new treatment’.³⁰ Registries that have been established to generate observational evidence about innovative AMSCIs are similarly problematic because participation is voluntary, outcome measures are subjective and results are not made public. There are also problems with the overall framing of the registries, which are presented as alternatives – rather than supplements – to robust clinical trials.³¹ And because many AMSCIs are prepared and offered in private practice, there is lack of oversight and independent evaluation of what is actually administered to the patient, making it impossible to compare outcomes in a meaningful way.³²

While it is possible that doctors offering autologous stem cell interventions simply lack awareness of the norms relating to clinical innovation, this seems highly unlikely, as many of these clinicians are active participants in policy debates about innovation and are routinely censured for behaviour that conflicts with accepted professional obligations. A more likely explanation, therefore, is that the clinicians offering autologous stem cell interventions are motivated not (only) by concern for their patients’ well-being, but also by other interests such as the desire to make money, achieve fame and satisfy their intellectual curiosity. In other words, they have competing and conflicting interests that override their concerns for patient well-being and the generation of valid evidence.

29.4 Implications for Oversight of Clinical Innovation

Unfortunately, the case of AMSCIs is far from unique. Other situations in which clinicians appear to be abusing the privilege of using their judgement to offer non-evidence-based therapies include orthopaedic surgeons over-using arthroscopies for degenerative joint disease,³³ assisted reproductive technology specialists who offer unproven ‘add-ons’ to traditional in-vitro fertilisation³⁴ and health professionals engaging in irresponsible off-label prescribing of psychotropic medicines.³⁵

Clinicians in all of these contexts are embedded in a complex web of financial and non-financial interests such as the desire to earn money, create product opportunities, pursue intellectual projects, achieve professional recognition and career advancement, and develop knowledge for the good of future patients³⁶ – all of which motivate their actions. Clinicians are also susceptible to biases such as the ‘optimism bias’, which might lead them to over-value innovative technologies and they are impacted upon by external pressures, such as industry marketing³⁷ and pressure from patients desperate for a ‘miracle cure’.³⁸

With these realities in mind, arguments against the oversight of innovation – or, more precisely, a reliance on consumer choice – become less compelling. Indeed, it could be argued that the oversight of innovation needs to be strengthened in order to protect patients from exploitation by those with competing and conflicting interests. That said, it is important that the oversight of clinical innovation does not assume that all innovating clinicians are motivated primarily by personal gain and, correspondingly, that it does not stifle responsible clinical innovation.

In order to strike the right balance, it is useful – following Lysaght and colleagues³⁹ – for oversight efforts to be framed in terms of, and account for, three separate functions: a negative function (focused on protecting consumers and sanctioning unacceptable practices, such as through tort and criminal law); a permissive function (concerned with frameworks that license health professionals and enable product development, such as through regulation of therapeutic products); and a positive function (dedicated to improving professional ethical behaviour, such as through professional registration and disciplinary systems). With that in mind, we now present some examples of oversight mechanisms that could be employed.

Those with responsibility for overseeing clinical practice need to enable clinicians to offer innovative treatments to selected patients outside the context of clinical trials, while at the same time preventing clinicians from exploiting patients for personal or socio-political reasons. Some steps that could be taken to both encourage responsible clinical innovation and discourage clinicians from acting on conflicts of interest might include:

• requiring that all clinicians have appropriate qualifications, specialisation, training and competency;

• mandating disclosure of competing and conflicting interests on clinic websites and as part of patient consent;

• requiring that consent be obtained by an independent health professional who is an expert in the patient’s disease (if necessary at a distance for patients in rural and remote regions);

• ensuring that all innovating clinicians participate in clinical quality registries that are independently managed, scientifically rigorous and publicly accessible;

• requiring independent oversight to ensure that appropriate product manufacturing standards are met;

• ensuring adequate pre-operative assessment, peri-operative care and post-operative monitoring and follow-up;

• ensuring that patients are not charged excessive amounts for experimental treatments, primarily by limiting expenses to cost-recovery; and

• determining that some innovative interventions should be offered only in a limited number of specialist facilities.

Professional bodies (such as specialist colleges), professional regulatory agencies, clinical ethics committees, drugs and therapeutics committees and other institutional clinical governance bodies would have an important role to play in ensuring that such processes are adhered to.

There may also be a need to extend current disciplinary and legal regimes regarding conflicts of interest (or at least ensure better enforcement of existing regimes). Many professional codes of practice already require physicians to be transparent about, and refrain from acting on, conflicts of interest. And laws in some jurisdictions already recognise that financial interests should be disclosed to patients, that patients should be referred for independent advice and that innovating clinicians need to demonstrate concern for patient well-being and professional consensus.⁴⁰

With respect to advertising, there is a need to prevent aggressive and misleading direct-to-consumer advertising while still ensuring that all patients who might benefit from an innovative intervention are aware that such interventions are being offered. With this in mind, it would seem reasonable to strengthen existing advertising oversight (which, in many jurisdictions, is weak and ad hoc). It may also be reasonable to prohibit innovating clinicians from advertising interventions directly to patients – including indirectly through ‘educational’ campaigns and media appearances – and instead develop systems that alert referring doctors to the existence of doctors offering innovative interventions.

Those regulating access to therapeutic products need to strike a balance between facilitating timely access to the products that patients want, and ensuring that those with competing interests are not granted licence to market products that are unsafe or ineffective. In this regard, it is important to note that product regulation is generally lenient when it comes to clinical innovation and it is arguable that there is a need to push back against current efforts to accelerate access to health technologies – efforts that are rapidly eroding regulatory processes and creating a situation in which patients are being exposed to an increasing number of ineffective and unsafe interventions.⁴¹ In addition, loopholes in therapeutic product regulation that can be exploited by clinicians with conflicts of interest should be predicted and closed wherever possible.

Although clinical innovation is not under the direct control of research ethics and governance committees, such committees have an important role to play in ensuring that those clinical trials and registries established to support innovation are not distorted by commercial and other imperatives. The task for such committees is to strike a balance between assuming that all researcher/innovators are committed to the generation of valid evidence and placing excessive burdens on responsible innovators who wish to conduct high-quality research. In this regard, research ethics committees could:

• ensure that participants in trials and registries are informed about conflicts of interest;

• ensure that independent consent processes are in place so that patients are not pressured into participating in research or registries; and

• consider whether it is ever acceptable to ask patients to ‘pay to participate’ in trials or in registries.

Research ethics committees also have an important role in minimising biases in the design, conduct and dissemination of innovation-supporting research. This can be achieved by ensuring that:

• trials and registries have undergone rigorous, independent scientific peer review;

• data are collected and analysed by independent third parties (e.g. Departments of Health);

• data are freely available to any researcher who wants to analyse it; and

• results – including negative results – are widely disseminated in peer-reviewed journals.

While this chapter has focused on traditional ‘top-down’ approaches to regulation and professional governance, it might also be possible to make use of what Devaney has referred to as ‘reputation-affecting’ regulatory approaches.⁴² Such approaches would reward those who maintain their independence or manage their conflicts effectively with reputation-enhancing measures such as access to funding and publication in esteemed journals. In this regard, other parties not traditionally thought of as regulators – such as employing institutions, research funders, journal reviewers and editors and the media – might have an important role to play in the oversight of clinical innovation.

Importantly, none of the oversight mechanisms we have suggested here would discourage responsible clinical innovation. Indeed, an approach to the oversight of clinical innovation that explicitly accounts for the realities of competing and conflicting interests could make it easier for well-motivated clinicians to obtain the trust of both individual patients and broader social licence to innovate.

29.5 Conclusion

Clinical innovation has an important and established role in biomedicine and in the development and diffusion of new technologies. But it is also the case that claims about patients’ – or consumers’ – rights and about the sanctity of the doctor–patient relationship, can be used to obscure both the risks of innovation and the vested interests that drive some clinicians’ decision to offer innovative interventions. In this context, adequate oversight of clinical innovation is crucial. After all, attempts to exploit the language and concept of innovation not only harms patients, but also threatens legitimate clinical innovation and undermines public trust. Efforts to push back against the robust oversight of clinical innovation need, therefore, to be viewed with caution.

30 The Challenge of ‘Evidence’ Research and Regulation of Traditional and Non-Conventional Medicines

Nayeli Urquiza Haas and Emilie Cloatre

30.1 Introduction

Governments and stakeholders have struggled to find a common ground on how to regulate research for different (‘proven’ or ‘unproven’) practices. Research on traditional, alternative and complementary medicines is often characterised as following weak research protocols and as producing evidence too poor to stand the test of systematic reviews, thus rendering individual case studies results insignificant. Although millions of people rely on traditional and alternative medicine for their primary care needs, the regulation of research into, and practice of, these therapies is governed by biomedical parameters. This chapter asks how, despite efforts to accommodate other forms of evidence, regulation of research concerning traditional and alternative medicines is ambiguous as to what sort of evidence – and therefore what sort of research – can be used by regulators when deciding how to deal with practices that are not based on biomedical epistemologies. Building on ideas from science and technology studies (STS), in this chapter we analyse different approaches to the regulation of traditional and non-conventional medicines adopted by national, regional and global governmental bodies and authorities, and we identify challenges to the inclusion of other modes of ‘evidence’ based on traditional and hybrid epistemologies.

30.2 Background

Non-conventional medicines are treatments that are not integrated to conventional medicine and are not necessarily delivered by a person with a degree in medical science. This may include complementary, alternative and traditional healers who may derive their knowledge from local or foreign knowledges, skills or practices.¹ For the World Health Organization (WHO), traditional medicine may be based on explicable or non-explicable theories, beliefs and experiences of different indigenous cultures.² That being said, traditional medicine is often included within the umbrella term of ‘non-conventional medicine’ in countries where biomedicine is the norm. However, this is often considered a misnomer insofar as traditional medicine may be the main source of healthcare in many countries, independent of its legitimate or illegitimate status. Given the high demand for traditional and non-conventional therapies, governments have sought to bring these therapies into the fold of regulation, yet, the processes involved to accomplish this task have been complicated by the tendency to rely on biomedicine’s standards of practice as a baseline. For example, the absence of and/or limited data produced by traditional and non-conventional medicine research and the unsatisfactory methodologies that do not stand the test of internationally recognised norms and standards for research involving human subjects have been cited as common barriers to the development of legislation and regulation of traditional and non-conventional medicine.³ In 2019, the WHO reported that 99 out of 133 countries considered the absence of research as one of the main challenges to regulating these fields.⁴ At the same time, governments have been reluctant to integrate traditional and non-conventional medicines as legitimate healthcare providers because their research is not based on the ‘gold standard’, namely multi-phase clinical trials.⁵ Without evidence produced through conventional research methodologies, it is argued that people are at risk of falling prey to charlatans who peddle magical cures – namely placebos without any concrete therapeutic value – or that money is wasted on therapies and products based on outdated or disparate bodies of knowledge rather than systematic clinical research.⁶ While governments have recognised to some extent the need to accommodate traditional and non-conventional medicines for a variety of reasons⁷ – including the protection of cultural rights, consumer rights, health rights, intellectual property and biodiversity⁸ – critics suggest that there is no reason why these modalities of medicine should be exempted from providing quality evidence.⁹

Picking up on some of these debates, this chapter charts the challenges arising from attempts to regulate issues relevant to research in the context of traditional and alternative medicine. From the outset, it explores what kinds of evidence and what kinds of research are accepted in the contemporary regulatory environment. It outlines some of the sticky points arising out of debates about research of traditional and non-conventional medicines, in particular, the role of placebo effects and evidence. Section 30.4 explores two examples of research regulation: WHO’s Guidelines for Methodologies on Research and Evaluation of Traditional Medicine and the European Directive on Traditional Herbal Medicine Products (THMPD). Both incorporate mixed methodologies into research protocols and allow the use of historical data as evidence of efficacy, thus recognising the specificity of traditional medicine and non-conventional medicine. However, we argue that these strategies may themselves become subordinated to the biomedical logics, calling into question the extent to which other epistemologies or processes are allowed to shape what is considered as acceptable evidence. Section 30.5 focuses on the UK, as an example of how other processes and rationalities, namely economic governmentalities, shape the spaces that non-conventional medicine can inhabit. Section 30.6 untangles and critically analyses the assumptions and effects arising out of the process of deciding what counts as evidence in healthcare research regulations. It suggests that despite attempts to include different modalities, ambiguities persist due to acknowledged and unacknowledged hierarchies of knowledge-production explored in this chapter. The last section opens up a conversation about what is at stake when the logic underpinning the regulation of research creates a space for difference, including different medical traditions and what counts as evidence.¹⁰

30.3 Evidence-Based Medicine and Placebo Controls

Evidence-based medicine (EBM) stands for the movement which suggests that the scientific method allows researchers to find the best evidence available in order to make informed decisions about patient care. To find the best evidence possible, which essentially means that the many is more significant than the particular, EBM relies on multiple randomised controlled trials (RCTs) and evidence from these is eventually aggregated and compared.¹¹ Evidence is hierarchically organised, whereby meta-reviews and systematic reviews based on RCTs stand at the top, followed by non-randomised controlled trials, observational studies with comparison groups, case series and reports, single case studies, expert opinion, community evidence and individual testimonies at the bottom. In addition to reliance on quantity, the quality of the research matters. Overall, it means that the best evidence is based on data from blinded trials, which show a causal relation between therapeutic interventions and the effect, and isolates results from placebo-effects.

From a historical perspective, the turn to blinded tests represented a significant shift in medical practice insofar as it diminished the relevance of expert opinion, which was itself based on a hierarchy of knowledge that tended to value authority and theory over empirical evidence. Physicians used to prescribe substances, such as mercury, that although believed to be effective for many ailments, were later found to be highly toxic.¹² Thus, the notion of evidence arising out of blinded trials closed the gap between science and practice, and also partially displaced physicians’ authority. Blinded trials and placebo controls had other effects: they became a tool to demarcate ‘real’ medicine from ‘fake’ medicine, proper doctors from ‘quacks’ and ‘snake-oil’ peddlers. By exposing the absence of a causal relationships between the therapy and the physical effect, some therapies and knowledges associated with them were rebranded as fraudulent or as superstitions. While the placebo effect might retrospectively explain why some of these discarded therapies were seen as effective, in practice, EBM’s hierarchy of evidence dismisses patients’ subjective accounts.¹³ While explanations about the placebo effect side-lined the role of autosuggestion in therapeutic interventions, they did not clarify either the source or the benefits of self-suggestion.

Social studies suggest that the role of imagination has been overlooked as a key element mediating therapeutic interactions. Phoebe Friesen argues that, rather than being an ‘obstacle’ that modern medicine needed to overcome, imagination ‘is a powerful instrument of healing that can, and ought to be, subjected to experimental investigations.’¹⁴ At the same time, when the positive role of the placebo effect and self-suggestion has been raised, scholarship research has pointed out dilemmas that remain unsolved, for example: Is it ethical to give a person a placebo in the conduct of research on non-orthodox therapies, and when is it justifiable, and for which conditions? Or, could public authorities justify the use of tax-payers money for so-called ‘sham’ treatments when people themselves, empowered by consumer choice rhetoric and patient autonomy, demand it? As elaborated in this chapter, some governments have been challenged for using public money to fund therapies deemed to be ‘unscientific’, while others have tightened control, fearing that self-help gurus, regarded as ‘cultish’ sect-leaders, are exploiting vulnerable patients.

To the extent that physiological mechanisms of both placebo and nocebo effects are still unclear, there does not seem to be a place in mainstream public healthcare for therapies that do not fit the EBM model because it is difficult to justify them politically and judicially, especially as healthcare regulations rely heavily on science to demonstrate public accountability.¹⁵ And yet, while the importance of safety, quality and efficacy of therapeutic practices cannot be easily dismissed, the reliance on EBM as a method to demarcate effective from non-effective therapies dismisses too quickly the reasons why people are attracted to these therapies. When it comes to non-conventional medicines, biomedicine and the scientific method do not factor in issues such as patient choice or the social dimension of medical practice.¹⁶ In that respect, questions as to how non-conventional medicine knowledges can demonstrate whether they are effective or not signal broader concerns. First, is it possible to disentangle the reliance of public accountability from science in order to solve the ethical, political, social and cultural dilemmas embedded in the practice of traditional and alternative medicine? Second, if we are to broaden the scope of how evidence is assessed, are there other processes or actors that shape what is considered effective from the perspective of healthcare regulation, for example, patient choice or consumer rights? And, finally, if science is not to be considered as the sole arbiter of healing, what are the spaces afforded for other epistemologies of healing? Without necessarily answering all of these questions, the aim of this chapter is to signpost a few sticky points in these debates. The next section explores three examples, at different jurisdictional levels – national, regional and international – of how healthcare regulators have sought to provide guidelines on how to incorporate other types of evidence into research dealing with traditional and non-conventional medicine.

30.4 Integration as Subordination: Guidelines and Regulations on Evidence and Research Methodologies

Traditional medicine has been part of the WHO’s political declarations and strategies born in the lead up to the 1978 Declaration of Alma Ata.¹⁷ Since then, the WHO has been at the forefront of developing regulations aimed at carving out spaces for traditional medicines. However, the organisation has moved away from its original understanding of health, which was more holistic and focused on social practices of healing. Regional political mobilisations underpinned by postcolonial critiques of scientific universalism were gradually replaced again by biomedical logics of health from the 1980s onwards.¹⁸ This approach, favouring biomedical standards of practice, can be appreciated to some extent in the ‘General Guidelines for the Research of Non-Conventional Medicines’, which is prefaced by the need to improve research data and methodologies with a view of furthering the regulation and integration of traditional herbal medicines and procedure-based therapies.¹⁹ The guidelines state that conventional methodologies should not hamper people’s access to traditional therapies; and instead, reaffirms the plurality of non-orthodox practices.²⁰ Noting the great diversity of practices and epistemologies framing traditional medicine, the guidelines re-organised them around two broad classifications – medicines and procedure-based therapies.

Based on these categories, the guidelines suggest that efficacy can be demonstrated through different research methodologies and types of evidence, including historical evidence of traditional use. To ensure safety and efficacy standards are met, herbal medicines ought to be first differentiated through botanical identification based on scientific Latin plant names. Meanwhile, the guidelines leave some room for the use of historical records of traditional evidence of efficacy and safety, which should be demonstrated through a variety of sources including literature reviews, theories and concepts of system of traditional medicine, as well as clinical trials. It also affirms that post-marketing surveillance systems used for conventional medicines are relevant in monitoring, reporting and evaluating adverse effects of traditional medicine.

More importantly, the guidelines contemplate the use of mixed methodologies, whereby EBM can make up for the gaps of evidence of efficacy in traditional medicine. And, where claims are based on different traditions, for example, Traditional Chinese Medicine (TCM) and Western Herbalism, the guidelines require evidence linking them together; and where there is none, scientific evidence should be the basis. If there are any contradictions between them, ‘the claim used must reflect the truth, on balance of the evidence available’.²¹ Although these research methodologies give the impression of integrating traditional medicine into the mainstream, the guidelines reflect policy transformations since the late 1980s, when plants appeared more clearly as medical objects in the Declaration of Chiang Mai.²² Drawing on good manufacturing practice guidelines as tools to assess the safety and quality of medicines, WHO’s guidelines and declarations between 1990 and 2000 increasingly framed herbal medicines as an object of both pharmacological research and healthcare governance.²³

WHO’s approach resonates with contemporary European Union legislation, namely the Directive 2004/24/EC on the registration of traditional herbal medicines.²⁴ This Directive also appears to be more open to qualitative evidence based on historical sources, but ultimately subordinates evidence to the biomedical mantra of safety and quality that characterises the regulation of conventional medicines. Traditional herbal medicine applications should demonstrate thirty years of traditional use of the herbal substances or combination thereof, of which fifteen years should be in the European Union (EU). In comparison with conventional medicines requiring multiphase clinical trials in humans, the Directive simplifies the authorisation procedure by admitting bibliographic evidence of efficacy. However, applications must be supplemented with non-clinical studies – namely, toxicology studies – especially if the herbal substance or preparation is not listed in the Community Pharmacopeia.²⁵ In the end, these regulations subordinate traditional knowledges to the research concepts and methodologies of conventional medicine. Research centres of non-conventional medicines in the EU also align mission statements to integration-based approaches, whereby inclusion of traditional and non-conventional medicine is premised on their modernisation through science.²⁶ However, as we argue in the next section, science is not the sole arbiter of what comes to be excluded or not in the pursuit of evidence. Indeed, drawing on the UK as a case study, we argue that economic rationalities are part of the regulatory environment shaping what is or is not included as evidence in healthcare research.

30.5 Beyond Evidence: The Economic Reasoning of Clinical Guidelines

Despite there being no specific restrictions preventing the use of non-conventional treatments within the National Health Service (NHS), authorities involved in the procurement of health or social care work have been under increasing pressure to define the hierarchy of scientific evidence in public affairs. For example, under pressure of being judicially reviewed, the Charities Commission opened up a consultation that produced new guidance for legal caseworkers assessing applications from charities promoting the use of complementary and alternative medicine. Charities have to define their purpose and how this benefits publics. For example, if the declared purpose is to cure cancer through yoga, it will have to demonstrate evidence of public benefit, based on accepted sources of evidence and EBM’s ‘recognised scales of evidence’. Although observations, personal testimonies or expert opinion are not excluded per se, they cannot substitute scientific medical explanation.²⁷ For the Commission, claims that fail the scientifically-based standard are meant to be regarded as cultural or religious beliefs.

There have also been more conspicuous ways in which evidence, as understood through a ‘scientific-bureaucratic-medicine’ model, has been used to limit the space for non-conventional medicines.²⁸ Clinical guidelines are a key feature of this regulatory model – increasingly institutionalised in the UK since the 1980s. The main body charged with this task is the National Institute for Health and Care Excellence (NICE), a non-departmental public body with statutory footing through the Health and Social Care Act 2012. The purpose of NICE clinical guidelines is to reduce variability in both quality and availability in the delivery of treatments and care and to confirm an intervention’s effectiveness. Although not compulsory, compliance with the guidelines is the norm and exceptions are ‘both rare and carefully documented’²⁹ because institutional performance is tied to their implementation and non-adherence may have a financial impact.³⁰ Following a campaign by ‘The Good Thinking Society’, an anti-pseudoscience charity, NHS bodies across London, Wales and the North of England have stopped funding homeopathic services.³¹ Meanwhile, an NHS England consultation also led to the ban of the prescription of products considered to be of ‘low clinical value’, such as homeopathic and herbal products. Responding to critics, the Department of Health defended its decision to defund non-conventional medicine products stating they were neither clinically nor cost effective.³² However, it is also worth noting that outside of the remit of publicly funded institutions, traditional and non-conventional medicines have been tolerated, or even encouraged, as a solution to relieve the pressure from austerity healthcare policies. For example, the Professional Standards Authority (PSA) has noted that accredited registered health and social care practitioners – which include acupuncturists, sports therapists, aromatherapy practitioners, etc. – could help relieve critical demand for NHS services.³³ This raises questions about what counts as evidence and how different regulators respond to specific practices that are not based on biomedical epistemologies, particularly what sort of research is acceptable in healthcare policy-making. What we have sought to demonstrate in this section is the extent to which, under the current regulatory landscape, the production of knowledge has become increasingly enmeshed with various layers of laws and regulations drafted by state and non-state actors.³⁴ Although the discourse has focused on problems with the kind of evidence and research methodologies used by advocates of non-conventional medicine, a bureaucratic application of EBM in the UK has limited access to traditional and non-conventional medicines in the public healthcare sector. In addition to policing the boundaries between ‘fake’ and ‘real’ medicines, clinical guidelines also delimit which therapies should be funded or not by the state. Thus, this chapter has sketched the links between evidence-based medicine and law, and the processes that influence what kind of research and what kind of evidence are appropriate for the purpose of delivering healthcare. Regulation, whether through laws implementing the EU Directives on the registration of traditional herbal medicines, or clinical guidelines produced by NICE, can be seen as operating as normative forces shaping healthcare knowledge production. The final section analyses the social and cultural dimensions of knowledge production and it argues that contemporary regulatory approaches discussed in the preceding sections assume non-conventional knowledges follow a linear development. Premised upon notions of scientific progress and modernity, this view ultimately fails to grasp the complexity of knowledge-production and the hybrid nature of healing practices.

30.6 Regulating for Uncertainty: Messy Knowledges and Practices

Hope for a cure, dissatisfaction with medical authority, highly bureaucratised healthcare systems or limited access to primary healthcare, are among some of the many reasons that drive people to try untested as well as the unregulated pills and practice-based therapies from traditional and non-conventional medicines. While EBM encourages a regulatory environment averse to the miracle medicines or testimonies of overnight cures and home-made remedies, Lucas Richert argues ‘unknown unknowns fail to dissuade the sick, dying or curious from experimenting with drugs’.³⁵ The problem, however, is the assumption that medicines, and also law, progress in a linear trajectory. In other words, that unregulated drugs became regulated through standardised testing and licensing regulations that carefully assess medicines quality, safety and efficacy before and after they are approved into the market.³⁶

Instead, medicines’ legal status may not always follow this linear evolution. We have argued so far that the regulatory environment of biomedicine demarcates boundaries between legitimate knowledge-makers/objects and illegitimate ones, such as street/home laboratories and self-experimenting patients.³⁷ But ‘evidence’ also acts as a signpost for a myriad of battles to secure some kind of authority over what is legitimate or not between different stakeholders (patient groups, doctors, regulators, industry, etc.).³⁸ Thus, by looking beyond laboratories and clinical settings, and expanding the scope of research to the social history of drugs, STS scholarship suggests that the legal regulation of research and medicines is based on more fragmented and dislocated encounters between different social spaces where experimentation happens.³⁹ For example, Mei Zhan argues that knowledge is ‘always already impure, tenuously modern, and permanently entangled in the networks of people, institutions, histories, and discourses within which they are produced’.⁴⁰ This means neither ‘Western’ biomedical science or ‘traditional’ medicines have ever been static and hermeneutically sealed spaces. Instead, therapeutic interventions and encounters are often ‘uneven’ and messy, linking dissimilar traditions and bringing together local and global healing practices, to the point that they constantly disturb assumptions about ‘the Great Divides’ in medicine. For example, acupuncture’s commodification and marketisation in Western countries reflects how Traditional Chinese Medicine has been transformed through circulation across time and space, enlisting various types of actors from different professional healthcare backgrounds – such as legitimate physicians, physiotherapists, nurses, etc. – as well as lay people who have not received formal training in a biomedical profession. New actors with different backgrounds take part in the negotiations for medical legitimacy and authority that are central to the reinvention of traditional and non-conventional medicine. These are processes of ‘translocation’ – understood as the circulation of knowledges across different circuits of exchange value – which reconfigure healing communities worldwide.⁴¹

So, in the process of making guidelines, decisions and norms about research on traditional and non-conventional medicines, the notion of ‘evidence’ could also signify a somewhat impermanent conclusion to a struggle between different actors. As a social and political space, the integration of traditional medicine and non-conventional medicine is not merely a procedural matter dictated by the logic of medical sciences. Instead, what is accepted or not as legitimate is constantly ‘remodelled’ by political, economic and social circumstances.⁴² In that sense, Stacey Langwick argues that evidence stands at the centre of ontological struggles rather than simply being contestations of authority insofar it is a ‘highly politicized and deeply intimate battle over who and what has the right to exist’.⁴³ For her, determination of what counts as evidence is at the heart of struggles of postcoloniality. When regulations based on EBM discard indigenous epistemologies of healing or the hybrid practices of individuals and communities who pick up knowledge in fragmented fashion, they also categorise their experiences, histories and effects as non-events. This denial compounds the political and economic vulnerability of traditional and non-conventional healers insofar as their survival depends on their ability to adapt their practice to conventional medicine, by mimicking biomedical practices and norms.⁴⁴ Hence, as Marie Andree Jacobs argues, the challenge for traditional and non-conventional medicines lies in translating ‘the alternativeness of its knowledge into genuinely alternative research practices’ and contributes to reimagining alternative models of regulation.⁴⁵

30.7 Conclusion

This chapter analysed how regulators respond to questions of evidence of traditional and non-conventional medicines. It argued that these strategies tend to subordinate data that is not based on EBM’s hierarchies of evidence, allowing regulators to demarcate the boundaries of legitimate research as well as situating the ‘oddities’ of non-conventional medicines outside of science (e.g. as ‘cultural’ or ‘religious’ issues in the UK’s case). In order to gain legitimacy and authority, as exemplified through the analysis of specific guidelines and regulations of research of traditional and non-conventional medicines, the regulatory environment favours the translation and transformation of traditional and non-conventional medicines into scientised and commercial versions of themselves. Drawing on STS scholarship, we suggested understanding these debates as political and social struggles reflecting changes about how people heal themselves and others in social communities that are in constant flux. More importantly, they reflect struggles of healing communities seeking to establish their own viability and right to exist within the dominant scientific-bureaucratic model of biomedicine. This chapter teased out limits of research regulation on non-conventional medicines, insofar practices and knowledges are already immersed in constantly shifting processes, transformed by the very efforts to pin them down into coherent and artificially closed-off systems. By pointing out the messy configurations of social healing spaces, we hope to open up a space of discussion with the chapters in this section. Indeed, how can we widen the lens of research regulation, and accommodate non-conventional medicines, without compromising the safety and quality of healthcare interventions? At the very minimum, research on regulation could engage with the social and political context of medicine-taking, and further the understanding of how and why patients seek one therapy over another.

31 Experiences of Ethics, Governance and Scientific Practice in Neuroscience Research

Martyn Pickersgill

31.1 Introduction¹

Over the last decade or so, sociologists and other social scientists concerned with the development and application of biomedical research have come to explore the lived realities of regulation and governance in science. In particular, the instantiation of ethics as a form of governance within scientific practice – via, for instance, research ethics committees (RECs) – has been extensively interrogated.² Social scientists have demonstrated the reciprocally constitutive nature of science and ethics, which renders problematic any assumption that ethics simply follows (or stifles) science in any straightforward way.³

This chapter draws on and contributes to such discussion through analysing the relationship between neuroscience (as one case study of scientific work) and research ethics. I draw on data from six focus groups with scientists in the UK (most of whom worked with human subjects) to reflect on how ethical questions and the requirements of RECs as a form of regulation are experienced within (neuro)science. The focus groups were conducted in light of a conceptual concern with how ‘issues and identities interweave’; i.e. how personal and professional identities relate to how particular matters of concern are comprehended and engaged with, and how those engagements themselves participate in the building of identities.⁴ The specific analysis presented is informed by the work of science and technology studies (STS) scholar Sheila Jasanoff and other social scientists who have highlighted the intertwinement of knowledge with social order and practices.⁵ In what follows, I explore issues that the neuroscientists I spoke with deem to be raised by their work, and characterise how both informal ideas about ethics and formal ethical governance (e.g. RECs) are experienced and linked to their research. In doing so, I demonstrate some of the lived realities of scientists who must necessarily grapple with the heterogenous forms of health-related research regulation the editors of this volume highlight in their Introduction, while seeking to conduct research with epistemic and social value.⁶

31.2 Negotiating the Ethical Dimensions of Neuroscience

It is well known that scientists are not lovers of the bureaucracies of research management, which are commonly taken to include the completion of ethical review forms. This was a topic of discussion in the focus groups: one scientist, for instance, spoke of the ‘dread’ (M3, Group 5) felt at the prospect of applying for ethical approvals. Such an idiom will no doubt be familiar to many lawyers, ethicists and regulatory studies scholars who have engaged with life scientists about the normative dimensions of their work.

Research governance – specifically, ethical approvals – could, in fact, be seen as having the potential of hampering science, without necessarily making it more ethical. In one focus group (Group 1), three postdoctoral neuroscientists discussed the different terms ethics committees had asked them to use in recruitment materials. One scientist (F3) expressed irritation that another (F2) was required to alter a recruitment poster, in order that it clearly stated that participants would receive an ‘inconvenience allowance’ rather than be ‘paid’. The scientists did not think that this would facilitate recruitment into a study, nor enable it to be undertaken any more ethically. F3 described how ‘it’s just so hard to get subjects. Also if you need to get subjects from the general public, you know, you need these tricks’. It was considered that changing recruitment posters would not make the research more ethical – but it might prevent it happening in the first place.

All that being said, scientists also feel motivated to ensure their research is conducted ‘ethically’. As the power of neuroimaging techniques increases, it is often said that it becomes all the more crucial for neuroscientists to engage with ethical questions.⁷ The scientists in my focus groups shared this sentiment, commonly expressed by senior scientists and ethicists. As one participant reflected, ‘the ethics and management of brain imaging is really becoming a very key feature of […] everyday imaging’ (F2, Group 4). Another scientist (F1, Group 2) summarised the perspectives expressed by all those who participated in the focus groups:

I think the scope of what we can do is broadening all the time and every time you find out something new, you have to consider the implications on your [research] population.

What scientists consider to be sited within the territory of the ‘ethical’ is wide-ranging, underscoring the scope of neuroscientific research, and the diverse institutional and personal norms through which it is shaped and governed. One researcher (F1, Group 2) reflected that ethical research was not merely that which had been formally warranted as such:

I think when I say you know ‘ethical research’, I don’t mean research passed by an ethics committee I mean ethical to what I would consider ethical and I couldn’t bring myself to do anything that I didn’t consider ethical in my job even if it’s been passed by an ethics committee. I guess researchers should hold themselves to that standard.

Conflicts about what was formally deemed ethical and what scientists felt was ethical were not altogether rare. In particular, instances of unease and ambivalence around international collaboration were reflected upon in some of the focus group discussions. Specifically, these were in relation to collaboration with nations that the scientists perceived as having relatively lax ethical governance as compared to the UK. This could leave scientists with a ‘slight uneasy feeling in your stomach’ (F2, Group 4). Despite my participants constructing some countries as being more or less ‘ethical’, no focus group participant described any collaborations having collapsed as a consequence of diverging perspectives on ethical research. However, the possibility that differences between nations exist, and that these difference could create problems in collaboration, was important to the scientists I spoke with. There was unease attached to collaborating with a ‘country that doesn’t have the same ethics’ (F2, Group 4). To an extent, then, an assumption of a shared normative agenda seemed to have significance as an underpinning for cross-national team science.

The need to ensure confidentiality while also sharing data with colleagues and collaborators was another source of friction. This was deemed to be a particularly acute issue for neuroscience, since neuroimaging techniques were seen as being able to generate and collect particularly sensitive information about a person (given both the biological salience of the brain and the role of knowledge about it in crafting identities).⁸ The need to separate data from anything that could contribute to identifying the human subject it was obtained from impacted scientists’ relationships with their research. In one focus group (Group 3), M3 pointed out that no longer were scientists owners of data, but rather, they were responsible chaperones for it.

Fears were expressed in the focus groups that neuroscientific data might inadvertently impact upon research participants, for instance, affecting their hopes for later life, legal credibility and insurance premiums. Echoing concerns raised in both ethics and social scientific literatures, my participants described a wariness about any attempt to predict ‘pathological’ behaviours, since this could result in the ‘labelling’ (F1, Group 4) or ‘compartmentalising’ (F2, Group 4) of people.⁹ As such, these scientists avoided involving themselves in research that necessarily entailed children, prisoners, or ‘vulnerable people’ (F2, group 4). Intra-institutional tensions could emerge when colleagues were carrying out studies that the scientists I spoke with did not regard as ethically acceptable.

Some focus group participants highlighted the hyping of neuroscience, and argued that it was important to resist this.¹⁰ These scientists nevertheless granted the possibility that some of the wilder promises made about neuroscience (e.g. ‘mind reading’) could one day be realised – generating ethical problems in the process:

there’s definitely a lot of ethical implications on that in terms of what the average person thinks that these methods can do and can’t do, and what they actually can do. And if the methods should get to the point where they could do things like that, to what extent is it going to get used in what way. (F1, group 1)

Scientists expressed anxiety about ‘develop[ing] your imaging techniques’ but then being unable to ‘control’ the application of these (F2, Group 4). Yet, not one of my participants stated that limits should be placed on ‘dangerous’ research. Developments in neuroscience were seen neither as intrinsically good nor as essentially bad, with nuclear power sometimes invoked as a similar example of how, to their mind, normativity adheres to deployments of scientific knowledge rather than its generation. More plainly: the rightness or wrongness of new research findings were believed to ‘come down to the people who use it’ (F1, Group 1), not to the findings per se. Procedures almost universally mandated by RECs were invoked as a way of giving licence to research: ‘a good experiment is a good experiment as long as you’ve got full informed consent, actually!’ (F1, Group 3). Another said:

I think you can research any question you want. The question is how you design your research, how ethical is the design in order to answer the question you’re looking at. (F2, Group 2)

Despite refraining from some areas of work themselves, due to the associated social and ethical implications my participants either found it difficult to think of anything that should not be researched at all, or asserted that science should not treat anything as ‘off-limits’. One scientist laughed in mock horror when asked if there were any branches of research that should not be progressed: ‘Absolutely not!’ (F1 Group 3). This participant described how ‘you just can’t stop research’, and prohibitions in the UK would simply mean scientists in another country would conduct those studies instead. In this specific respect, ethical issues seemed to be somewhat secondary to the socially produced sense of competition that appears to drive forward much biomedical research.

31.3 Incidental Findings within Neuroimaging Research

The challenge of what to do with incidental findings is a significant one for neuroscientists, and a matter that has exercised ethicists and lawyers (see Postan, Chapter 23 in this volume).¹¹ They pose a particular problem for scientists undertaking brain imaging. Incidental findings have been defined as ‘observations of potential clinical significance unexpectedly discovered in healthy subjects or in patients recruited to brain imaging research studies and unrelated to the purpose or variables of the study’.¹² The possibilities and management of incidental findings were key issues in the focus group discussions I convened, with a participant in one group terming them ‘a whole can of worms’ (F1, Group 3). Another scientist reflected on the issue, and their talk underscores the affective dimensions of ethically challenging situations:

I remember the first time [I discovered an incidental finding] ’cos we were in the scanner room we were scanning the child and we see it online basically, that there might be something. It’s a horrible feeling because you then, you obviously at this point you know the child from a few hours, since a few hours already, you’ve been working with the child and it’s … you have a personal investment, emotional investment in that already but the important thing is then once the child comes out of the scanner, you can’t say anything, you can’t let them feel anything, you know realise anything, so you have to be just really back to normal and pretend there’s nothing wrong. Same with the parents, you can’t give any kind of indication to them at all until you’ve got feedback from an expert, which obviously takes so many days, so on the day you can’t let anything go and no, yeah it was, not a nice experience. (F2, Group 2)

Part of the difficulties inherent in this ethically (and emotionally) fraught area lies in the relationality between scientist and research subject. Brief yet close relationships between scientists and those they research are necessary to ensure the smooth running of studies.¹³ This intimacy, though, makes the management of incidental findings even more challenging. Further, the impacts of ethically significant issues on teamwork and collaboration are complex; for instance, what happens if incidental findings are located in the scans of co-workers, rather than previously unknown research subjects? One respondent described how these would be ‘even more difficult to deal with’ (F1, Group 1). Others reflected that they would refrain from ‘helping out’ by participating in a colleague’s scan when, for instance, refining a protocol. This was due to the potential of neuroimaging to inadvertently reveal bodily or psychological information that they would not want their colleagues to know.

The challenge of incidental findings is one that involves a correspondence between a particular technical apparatus (i.e. imaging methods that could detect tumours) and an assemblage of normative imperatives (which perhaps most notably includes a duty of care towards research participants). This correspondence is reciprocally impactful: as is well known, technoscientific advances shift the terrain of ethical concern – but so too does the normative shape the scientific. In the case of incidental findings, for example, scientists increasingly felt obliged to cost in an (expensive) radiologist into their grants, to inspect each participant’s scan; a scientist might ‘feel uncomfortable showing anybody their research scan without having had a radiologist look at it to reassure you it was normal’ (F1, Group 3). Hence, ‘to be truly ethical puts the cost up’ (F2, Group 4). Not every scientist is able to command such sums from funders, who might also demand more epistemic bang for the buck when faced with increasingly costly research proposals. What we can know is intimately linked to what we can, and are willing to, spend. And if being ‘truly ethical’ indeed ‘puts the cost up’, then what science is sponsored, and who undertakes this, will be affected.

31.4 Normative Uncertainties in Neuroscience

Scientific research using human and animal subjects in the UK is widely felt to be an amply regulated domain of work. We might, then, predict that issues like incidental findings can be rendered less challenging to deal with through recourse to governance frameworks. Those neuroscientists who exclusively researched animals indeed regarded the parameters and procedures defining what was acceptable and legal in their work to be reasonable and clear. In fact, strict regulation was described as enjoining self-reflection about whether the science they were undertaking was ‘worth doing’ (F1, Group 6). This was not, however, the case for my participants working with humans. Rather, they regarded regulation in general as complicated, as well as vague: in the words of two respondents, ‘too broad’ and ‘open to interpretation’ (F1, Group 2), and ‘a bit woolly’ and ‘ambiguous’ (F2, group 2). Take, for instance, the Data Protection Act: in one focus group (Group 3) a participant (F1) noted that a given university would ‘take their own view’ about what was required by the Act, with different departments and laboratories in turn developing further – potentially diverging – interpretations.

Within the (neuro)sciences, procedural ambiguity can exist in relation to what scientists, practically, should do – and how ethically valorous it is to do so. Normative uncertainty can be complicated further by regulatory multiplicity. The participants of one focus group, for example, told me about three distinct yet ostensibly nested ethical jurisdictions they inhabited: their home department of psychology, their university medical school and their local National Health Service Research Ethics Committee (NHS REC). The scientists I spoke with understood these to have different purviews, with different procedural requirements for research, and different perspectives on the proper way enactment of ethical practices, such as obtaining informed consent in human subjects research.

Given such normative uncertainty, scientists often developed what we might term ‘ethical workarounds’. By this, I mean that they sought to navigate situations where they were unsure of what, technically, was the ‘right’ thing to do by establishing their own individual and community norms for the ethical conduct of research, which might only be loosely connected to formal requirements. In sum, they worked around uncertainty by developing their own default practices that gave them some sense of surety. One participant (F1, Group 2) described this in relation to drawing blood from people who took part in her research. To her mind, this should be attempted only twice before being abandoned. She asserted that this was not formally required by any research regulation, but instead was an informal standard to which she and colleagues nevertheless adhered.

In the same focus group discussion, another scientist articulated a version of regulatory underdetermination to describe the limits of governance:

not every little detail can be written down in the ethics and a lot of it is in terms of if you’re a researcher you have to you know make your mind up in terms of the ethical procedures you have to adhere to yourself and what would you want to be done to yourself or not to be done … (F2, Group 2)

Incidental findings were a key example of normative uncertainty and the ethical workarounds that resulted from this. Although ‘not every little detail can be written down’, specificity in guidelines can be regarded as a virtue in research that is seen to have considerable ethical significance, and where notable variations in practice were known to exist. The scientist quoted above also discussed how practical and ethical decisions must be made as a result of the detection of clinically relevant incidental findings, but that their precise nature was uncertain: scientists were ‘struggling’ due to being ‘unsure’ what the correct course of action should be. Hence, ‘proper guidelines’ were invoked as potentially useful, but these were seemingly considered to be hard to come by.

The irritations stimulated by a perceived lack of clarity on the ethically and/or legally right way to proceed are similarly apparent in the response of this scientist to a question about her feelings upon discovering, for the first time, a clinically relevant incidental finding in the course of her neuroimaging work:

It was unnerving! And also because it was the first time I wasn’t really sure how to deal with it all, so I had to go back in the, see my supervisor and talk to them about it and, try to find out how exactly we’re dealing now with this issue because I wasn’t aware of the exact clear guidelines. (F2, Group 2)

Different scientists and different institutions were reported to have ‘all got a different way of handling’ (F2, Group 4) the challenge of incidental findings. Institutional diversity was foregrounded, such as in the comments of F1 (Group 1). She described how when working at one US university ‘there was always a doctor that had to read the scans so it was just required’. She emphasised how there was no decision-making around this on behalf of the scientist or the research participant: it was simply a requirement. On the other hand, at a different university this was not the case – no doctor was on call to assess neuroimages for incidental findings.

An exchange between two researchers (F1 and F2, Group 2) also illustrates the problems of procedural diversity. Based in the same university but in different departments, they discussed how the complexities of managing incidental findings was related, in part, to practices of informed consent. Too lengthy a dialogue to fully reproduce here, two key features stood out. First, differences existed in whether the study team would, in practice, inform a research subject’s physician in the event of an individual finding: in F2’s case, it was routine for the physician to be contacted, but F1’s participants could opt out of this. However, obtaining physician contact details was itself a tricky undertaking:

we don’t have the details of the GP so if we found something we would have to contact them [the participant] and we’d have to ask them for the GP contact and in that case they could say no, we don’t want to, so it’s up to them to decide really, but we can’t actually say anything directly to them what we’ve found or what we think there might be because we don’t know, ’cos the GP then will have to send them to proper scans to determine the exact problem, ’cos our scans are obviously not designed for any kind of medical diagnosis are they? So I suppose they’ve still got the option to say no. (F2, Group 2)

It is also worth noting at this point the lack of certitude of the scientists I spoke with about where directives around ethical practice came from, and what regulatory force these had. F1 (Group 1) and F2 (Group 2) above, for instance, spoke about how certain processes were ‘just required’ or how they ‘have to’ do particular things to be ‘ethical’. This underscores the proliferation and heterogeneity of regulation the editors of this volume note in their Introduction, and the challenges of comprehending and negotiating it in practice by busy and already stretched professionals.

31.5 Discussion

The ethical aspects of science often require discursive and institutional work to become recognised as such, and managed thereafter. In other words, for an issue to be regarded as specifically ethical, scientists and universities need to, in some sense, agree that it is; matters that ethicists, for instance, might take almost for granted as being intrinsically normative can often escape the attention of scientists themselves. After an issue has been characterised by researchers as ethical, addressing it can necessitate bureaucratic innovation, and the reorganisation of work practices (including new roles and changing responsibilities). Scientists are not always satisfied with the extent to which they are able, and enabled, to make these changes. The ethics of neuroscience, and the everyday conversations and practices that come into play to deal with them, can also have epistemic effects: ethical issues can and do shape scientists relationships with the work, research participants, and processes of knowledge-production itself.

The scientists I spoke with listed a range of issues as having ethical significance, to varying degrees. Key among these were incidental findings. The scientists also engaged in what sociologist Steven Wainwright and colleagues call ‘ethical boundary work’; i.e. they sometimes erected boundaries between scientific matters and normative concerns, but also collapsed these when equating good science with ethical science.¹⁴ This has the effect of enabling scientists to present research they hold in high regard as being normatively valorous, while also bracketing off ethical questions they consider too administratively or philosophical challenging to deal with as being insufficiently salient to science itself to necessitate sustained engagement.

Still, though, ethics is part and parcel of scientific work and of being a scientist. Normative reflection is, to varying degrees, embedded within the practices of researchers, and can surface not only in focus group discussions but also in corridor talk and coffee room chats. This is, in part, a consequence of the considerable health-related research regulation to which scientists are subject. It is also a consequence of the fact that scientists are moral agents: people who live and act in a world with other persons, and who have an everyday sense of right and wrong. This sense is inevitably and essentially context-dependent, and it inflects their scientific practice and will be contoured in turn by this. It is these interpretations of regulation in conjunction with the mundane normativity of daily life that intertwine to constitute scientists’ ethical actions within the laboratory and beyond, and in particular that cultivate their ethical workarounds in conditions of uncertainty.

31.6 Conclusion

In this chapter I have summarised and discussed data regarding how neuroscientists construct and regard the ethical dimensions of their work, and reflected on how they negotiate health-related research regulation in practice. Where does this leave regulators? For a start, we need more sustained, empirical studies of how scientists comprehend and negotiate the ethical dimensions of their research in actual scientific work, in order to ground the development and enforcement of regulation.¹⁵ What is already apparent, however, is that any regulation that demands actions that require sharp changes in practice, to no clear benefit to research participants, scientists, or wider society, is unlikely to invite adherence. Nor are frameworks that place demands on scientists to act in ways they consider unethical, or which place unrealistic burdens (e.g. liaising with GPs without the knowledge of research participants) on scientists that leave them anxious and afraid that they are, for instance, ‘breaking the law’ when failing to act in a practically unfeasible way.

It is important to recognise that scientists bring to bear their everyday ethical expertise to their research, and it is vital that this is worked with rather than ridden over. At the same time, it takes a particular kind of scientist to call into question the ethical basis of their research or that of close colleagues, not least given an impulse to conflate good science with ethical science. Consequently, developing regulation in close collaboration with scientists also needs the considered input of critical friends to both regulators and to life scientists (including but not limited to social scientific observers of the life sciences). This would help mitigate the possibility of the inadvertent reworking or even subverting of regulation designed to protect human subjects by well-meaning scientists who inevitably want to do good (in every sense of the word) research.

32 Humanitarian Research Ethical Considerations in Conducting Research during Global Health Emergencies

Agomoni Ganguli-Mitra and Matthew Hunt

32.1 Introduction

Global health emergencies (GHEs) are situations of heightened and widespread health crisis that usually require the attention and mobilisation of actors and institutions beyond national borders. Conducting research in such contexts is both ethically imperative and requires particular ethical and regulatory scrutiny. While global health emergency research (GHER) serves a crucial function of learning how to improve care and services for individuals and communities affected by war, natural disasters or epidemics, conducting research in such settings is also challenging at various levels. Logistics are difficult, funding is elusive, risks are elevated and likely to fluctuate, social and institutional structures are particularly strained, infrastructure destroyed. GHER is diverse. It includes biomedical research, such as studies on novel vaccines and treatments, or on appropriate humanitarian and medical responses. Research might also include the development of novel public health interventions, or measures to strength public health infrastructure and capacity building. Social science and humanities research might also be warranted, in order to develop future GHE responses that better support affected individuals and populations. Standard methodologies, including those related to ethical procedures, might be particularly difficult to implement in such contexts.

The ethics of GHER relates to a variety of considerations. First are the ethical and justice-based justifications to conduct research at all in conditions of emergency. Second, the ethics of GHER considers whether research is designed and implemented in an ethically robust manner. Finally, ethical issues also relate to questions arising in the course of carrying out research studies. GHER is characterised by a heterogeneity (of risk, nature, contexts, urgency, scope) which itself gives rise to various kinds of ethical implications:¹ why research is done, who conducts research, where and when it is conducted, what kind of research is done and how. It is therefore difficult to fully capture the range of ethical considerations that arise, let alone provide a one-size-fits-all solution to such questions. Using illustrations drawn from research projects conducted during GHEs, we discuss key ethical and governance concerns arising in GHER – beyond those traditionally associated with biomedical research – and explore the future direction of oversight for GHER. After setting out the complex context of GHER, we illustrate the various ethical issues associated with justifying research, as well as considerations related to context, social value and engagement with the affected communities. Finally, we explore some of the new orientations and lenses in the governance of GHER through recent guidelines and emerging practices.

32.2 The Context of Global Health Emergency Research

GHEs are large-scale crises that affect health and that are of global concern (epidemics, pandemics, as well as health-related crises arising from conflicts, natural disasters or forced displacement). They are characterised by various kinds of urgency, driven by the need to rapidly and appropriately respond to the needs of affected populations. However, effective responses, treatments or preventative measures require solid evidence bases, and the establishment of such knowledge is heavily dependent on findings from research (including biomedical research) carried out in contexts of crises.² As the Council for International Organizations of Medical Sciences (CIOMS) guidelines point out: ‘disasters can be difficult to prevent and the evidence base for effectively preventing or mitigating their public health impact is limited’.³ Generating relevant knowledge in emergencies is therefore necessary to enhance the care of individuals and communities, for example through treatments, vaccines or improved palliative care. Research can also consolidate preparedness for public health and humanitarian responses (including triage protocols) and contribute to capacity building (for example, by training healthcare professionals) in order to strengthen health systems in the long run. Ethical consideration and regulation must therefore adapt to both immediate and urgent issues, as well as contribute to developing sustainable and long-term processes and practices.

Adding to this is the fact that responses to GHEs involve a variety of actors: humanitarian responders, health professionals, public health officials, researchers, media, state officials, armed forces, national governments and international organisations. Actors conducting both humanitarian work and research can encounter particular ethical challenges, given the very different motivations behind response and research. Such dual roles might, at times, pull in different directions and therefore warrant added ethical scrutiny and awareness, even where such actors might be best placed to deliver both aims, given their presence and knowledge of the context, and especially if they have existing relationships with affected communities.⁴ Medical and humanitarian responses to GHEs are difficult contexts for ethical deliberation – for ethics review and those involved in research governance – where various kinds of motivations and values collide, potentially giving rise to conflicting values and aims, or to incompatible lines of accountability⁵ (for example, towards humanitarian versus research organisations or towards national authorities versus international organisations).

Given the high level of contextual and temporal complexity, and the heightened vulnerability to harm of those affected by GHEs, there is a broad consensus within the ethics literature that research carried out in such contexts requires both a higher level of justification and careful ongoing ethical scrutiny. Attention to vulnerability is, of course, not new to research ethics. It has catalysed many developments in the field, such as the establishment of frameworks, principles, and rules aiming to ensure that participants are not at risk of additional harm, and that their interests are not sacrificed to the needs and goals of research. It has also been a struggle in research governance, however, to find appropriate regulatory measures and measures of oversight that are not overly protectionist; ones that do not stereotype and silence individuals and groups but ensure that their interests and well-being are protected. The relationship between research and vulnerability becomes particularly knotty in contexts of emergency. How should we best attend to vulnerability when it is pervasive?⁶ On the one hand, all participants are in a heightened context of vulnerability when compared to populations under ordinary circumstances. On the other hand, those individuals who suffer from systematic and structural inequality, disadvantage and marginalisation, will also see their potential vulnerabilities exacerbated in conditions of public health and humanitarian emergencies. The presence of these multiple sources and forms of vulnerability adds to the difficulty in determining whether research and its design are ethically justified.

32.3 Justifying Research: Why, Where and When?

While research is rightly considered an integral part of humanitarian and public health responses to GHEs,⁷ and while there may indeed, as the WHO suggests, be an ‘ethical obligation to learn as much as possible, as quickly as possible’,⁸ research must be ethically justified on various fronts. At a minimum, GHER must not impede current humanitarian and public health responses, even as it is deployed with the aim of improving future responses. Nor should it drain existing resource and skills. Additionally, the social value of such research derives from its relevance to the particular context and the crisis at hand.⁹ Decisions regarding location, recruitment of participants, as well as study design (including risk–benefit calculations) must ensure that scientific and social value are not compromised¹⁰ in the process. The Working Group on Disaster Research Ethics (WGDRE), formed in response to the 2004 Indian Ocean tsunami, has argued that while ethical research can be conducted in contexts of emergencies, such research must respond to local needs and priorities, in order avoid being opportunistic.¹¹ Similar considerations were reiterated during the 2014–2016 Ebola outbreak. Concern was expressed that ‘some clinical sites could be perversely incentivized to establish research collaborations based on resources promised, political pressure or simply the powers of persuasion of prospective researchers – rather than a careful evaluation of the merits of the science or the potential benefit for patients. Some decision-makers at clinical sites may not have the expertise to evaluate the scientific merits of the research being proposed’.¹² Such observation reflects considerations that have been identified in a range of GHE settings.

The question of social value is not only related to the ultimate or broad aims of research. Specific research questions can only be justified if these cannot be investigated in non-crisis conditions,¹³ and as specified above, where the answers to such questions is expected to be of benefit to the community in question – or to relevantly similar communities, be it during the current emergency, or in the future. Relatedly, research should be conducted within settings that are most likely to benefit from the generation of such knowledge, perhaps because they are the site of cyclical disasters or endemic outbreaks that frequently disrupt social structures. Given the heightened precarity of GHE contexts, the risk of exposing study participants to additional harm is particularly salient, and such potential risk must therefore be systematically justified. If considerations of social value are key, these need to extend to priority-setting in GHER. Yet, the funding and development of GHER is not immune to how research priority is set globally. Consequently, this divergence (between the kind of research that is currently being funded and developed, and the research that might be required in specific contexts of crisis) will present particular governance challenges at the local, national, and global levels. Stakeholders from contexts of scarce resources have warned that priority-setting in GHE might mirror broader global research agendas, where the health concerns and needs of low- and middle-income countries (LMICs) are systematically given lower priority.¹⁴ The global research agenda is not generally directed by the specific needs arising from crises (especially crisis in resource-poor contexts), and yet the less well-funded and less resilient health systems of LMICs frequently bear the brunt and severity of crises. The ethical challenges associated with conducting research in contexts of crisis therefore are consistently present at all levels, from the broader global research agenda, to the choice of context and participants, from how research is designed and conducted, to how research data and findings are used and shared.

32.4 Justifying Research: What and How?

GHER includes a wide range of activities, from minimally invasive collection of data¹⁵ and systems research aimed at strengthening health infrastructure,¹⁶ to more controversial procedures including testing of experimental therapeutics and vaccines.¹⁷ A common issue of GHER, one that has arisen prominently during recent epidemics and infectious disease outbreaks, is the challenge to long-established standards and trials designs, in particular to what is known as the ‘gold standard’: randomised, double-blind clinical trials as the standard developmental pathway for new drugs and interventions. The ethical intuitions and debates often pull in different direction. As discussed earlier in the chapter, the justification for conducting research in crises must be ethically robust, as must research design and deployment. Equally, in the context of the COVID-19 pandemic, a strong argument has been made for the need to ensure methodologically rigorous research design and not to accept lower scientific standards as a form of ‘pandemic research exceptionalism’.¹⁸ At the time of writing, human challenge trials – the intentional infection of research participants with the virus – proposed as a way to accelerate the development of a vaccine for the novel coronavirus, remain ethically and scientifically controversial. While some commentators have suggested that this may be a rapid and necessary route to vaccine development,¹⁹ others have argued that the criteria for ethical justification of human challenge studies, including social value and fair participation selection, are not likely to be met.²⁰

Such tensions are particularly heightened in contexts of high infectious rates, morbidity and mortality. During the 2014–2016 Ebola outbreak in West Africa, several unregistered interventions were approved for use as investigational therapeutics. Importantly, while these were approved for emergency use, they were to be deployed under the MEURI scheme: ‘monitored emergency use of unregistered and experimental interventions (MEURI)’,²¹ that is, through a process where results of an intervention’s use are shared with the scientific and medical community, and not under the medical label of ‘compassionate use’. This approach allows clinical data to be compiled and thus contributes to the process of generating generalisable evidence. The deployment of experimental drugs was once again considered – alongside the deployment of experimental vaccines – early during the 2018 Ebola outbreak in the Democratic Republic of the Congo.²² This time, regulatory and ethical frameworks were in place to approve access to five investigational therapeutics under the MEURI scheme,²³ two of which have since shown promise during the clinical trials conducted in 2018. The first Ebola vaccine, approved in 2019, was tested through ring vaccine trials first conducted during the 2014–2016 West African outbreak. Methods and study designs need to be aligned with the needs of the humanitarian response, and yet it is not an easy task to translate the values of humanitarian responses onto research design. How experimental interventions should be deployed under the MEURI scheme was heavily debated and contested by local communities, who saw these interventions as their only and last resort against the epidemic.

While success stories in GHER heavily depend on global cooperation, suitable infrastructure, and often collaboration between the public and private sector, such interventions are unlikely to succeed without the collaboration and engagement of local researchers and communities, and without establishing a relationship based on trust. Engaging with communities and establishing relationships of trust and respect are key to successful research endeavours in all contexts, but are particularly crucial where social structures have broken down and where individuals and communities are at heightened risk of harm. Community engagement, especially for endeavours not directly related to response and medical care, is also particularly challenging to implement. These challenges are most significant in sudden-onset GHE such as earthquakes,²⁴ if prior relationships do not exist between researchers and the communities. During the 2014–2016 Ebola outbreak, the infection and its spread caused ‘panic in the communities by the lack of credible information and playing to people’s deepest fears’.²⁵ Similarly, distrust arose during the subsequent outbreak in eastern DRC, a region already affected by conflict, where low trust in institutions and officials resulted in low acceptance of vaccines and a spread of the virus.²⁶ Similarly, in the aftermath of Hurricane Katrina there was widespread frustration and distrust of the US federal response by those engaged in civil society and community-led responses.²⁷ However, such contexts have also given rise to new forms solidarity and cooperation. The recent Ebola outbreaks, the aftermath of Katrina, the 2004 Indian Ocean tsunami and the Fukushima disaster have also given rise to unprecedent levels engagement and leadership by members of the affected communities.²⁸ Given that successful responses to GHEs are heavily dependent on trust as well as on the engagement and ownership of response activities by local communities, there is little doubt that successful endeavours in GHER will also depend on establishing close, trustworthy and respectful collaborations between researchers, responders, local NGOs, civil society and members of the affected population.

32.5 Governance and Oversight: Guidelines and Practices

The difficulty of conducting GHER is compounded by much complexity at the level of regulation, governance and oversight. Those involved in research in these contexts are working in and around various ethical frameworks including humanitarian ethics, medical ethics, public health ethics and research ethics. Each framework has traditionally been developed with very different actors, values and interests in mind. Navigating these might result in various kinds of conflicts or dissonance, and at the very least make GHER a particularly challenging endeavour. Such concerns are then compounded by regulatory complexity, including existing national laws and guidelines, international regulations and guidance produced by different international bodies (for example, the International Health Regulations 2005 by the WHO and Good Clinical Practice by the National Institute for Health Research in the United Kingdom), all of which are engaged in a context of urgency, shifting timelines and rapidly evolving background conditions. Two recent pieces of guidance are worth highlighting in this context. The first are the revised CIOMS guidelines, published in 2016, which have a newly added entry (Guideline 20) specifically addressing GHER. The CIOMS guidelines recognise that ‘[d]isasters unfold quickly and study designs need to be chosen so that studies will yield meaningful data in a rapidly evolving situation. Study designs must be feasible in a disaster situation but still appropriate to ensure the study’s scientific validity’.²⁹ While reaffirming the cornerstones of research ethics, Guideline 20 also refers to the need to ensure equitable distribution of risks and benefits; the importance of community engagement; the need for flexibility and expediency in oversight while providing due scrutiny; and the need to ensure the validity of informed consent obtained under conditions of duress. CIOMS also responds to the need for flexible and alternative study designs and suggests that GHER studies should ideally be planned ahead and that generic versions of protocols could be pre-reviewed prior to a disaster occurring.

Although acting at a different governance level to CIOMS, the Nuffield Council on Bioethics has also recently published a report on GHER,³⁰ engaging with emerging ethical issues and echoing the central questions and values reflected in current discussions and regulatory frameworks. Reflecting on the lessons learned from various GHEs over the last couple of decades, the report encourages the development of an ethical compass for GHER that focuses on respect, reducing suffering, and fairness.³¹ The report is notable for recommending that GHER endeavours attend not just to whose needs are being met (that is, questions of social value and responsiveness) but also to who has been involved in defining those needs. In other words, the report reminds us that beyond principles and values guiding study design and implementation, ethical GHER requires attention to a wider ethics ecosystem that includes all stakeholders, and that upholding fairness is not only a feature of recruitment or access to the benefits of research, but must also exist in collaborative practices with local researchers, authorities and communities.

All guidelines and regulations need interpretation on the ground,³² at various levels of governance, as well as by researcher themselves. The last couple of decades have seen a variety of innovative and adaptive practices being developed for GHER, including the establishment of research ethics committees specifically associated with humanitarian organisations. Similarly, many research ethics committees that are tasked with reviewing GHER protocols have adapted their standard procedures in line with the urgency and developing context of GHEs.³³ Such strategies include convening ad-hoc meetings, prioritising these protocols in the queue for review, waiving deadlines, having advisors pre-review protocols and conducting reviews by teleconference.³⁴ Another approach can be found in the development of pre-approved, or pre-reviewed protocol templates, which allow research ethics committees to conduct an initial review of proposed research ahead of a crisis occurring, or to review generic policies for the transfer of samples and data. Following their experience in reviewing GHER protocols during the 2014–2016 Ebola outbreak, members of the World Health Organization Ethics Review Committee recommended the formation of a joint research ethics committee for future GHEs.³⁵ A need for greater involvement and interaction between ethics committees and researchers has been indicated by various commentators, pointing to the need for ethical review to be an ongoing and iterative process. One such model for critical and ongoing engagement, entitled ‘real-time responsiveness’,³⁶ proposes a more dynamic approach to ethics oversight for GHER, including more engagement between researchers, research ethics committees, and advisors once the research is underway. An iterative review process has been proposed for research in ordinary contexts³⁷ but is particularly relevant to GHER, given the urgency and rapidly changing context.

It is important to also consider how to promote and sustain the ethical capacities of researchers in humanitarian settings. Such capacities include the following, which have been linked to ethical humanitarian action:³⁸ foresighting (the ability to anticipate potential for harms), attentiveness (especially for the social and relational dynamics of particular GHE contexts), and responsiveness to the often-shifting features of a crisis, and their implications for the conduct of the research. These capacities point to the role of virtues, in addition to guidelines and principles, in the context of GHER. As highlighted by O’Mathuna, humanitarian research calls for virtuous action on the part of researchers in crisis settings ‘to ensure that researchers do what they believe is ethically right and resist what is unethical’.³⁹ Ethics therefore is not merely a feature of approval or bureaucratic procedure. It must be actively engaged with at various levels and also by all involved, including by researchers themselves.

32.6 New Orientations and Lenses

As outlined above, GHEs present a distinctive context for the conduct of research. Tailored ethics guidance for GHER has been developed by various bodies, and it has been acknowledged that GHER can be a challenging fit for standard models to ethics oversight and review. As a result, greater flexibility in review procedures has been endorsed, while emphasising the importance of upholding rigorous appraisal of protocol. Particular attention has been given to the proportionality of ethical scrutiny to the ethical concerns (risk of harm, issues of equity, situations of vulnerability) associated with particular studies. Novel approaches, such as the preparation and pre-review of generic protocols, have also been incorporated into more recent guidance documents (e.g. CIOMS) and implemented by research ethics committees associated with humanitarian organisations.⁴⁰ These innovations reflect the importance of temporal sensitivity in GHER and in its review. As well as promoting timely review processes for urgent protocols, scrutiny is also needed to identify research that does not need to be conducted in an acute crisis and whose initiation ought to be delayed.

Discussions about GHER, and on disaster risk reduction more broadly, also point to the importance of preparedness and anticipation. Sudden onset events and crises often require quick response and reaction. Nonetheless, there are many opportunities to lay advance groundwork for research and also for research ethics oversight. In this sense, pre-review of protocols, careful preparation of standard procedures, and even research ethics committees undertaking their own planning procedures for reviewing GHER, are all warranted. It also suggests that while methodological innovation and adaptive designs may be required, methodological standards should be respected in crisis research and can be promoted with more planning and preparation.

32.7 Conclusion

Research conducted in GHEs present a particularly difficult context in terms of governance. While each kind of emergency presents its own particular challenge, there are recurring patterns, characterised by urgency in terms of injury and death, extreme temporal constraints, and uncertainty in terms of development and outcome. Research endeavours have to be ushered through a plethora of regulation at various levels, not all of which have been developed with GHER in mind. Several sectors are necessarily involved: humanitarian, medical, public health, and political to name just a few. Conducting research in these contexts is necessary, however, in order to contribute to a robust evidence-base for future emergencies. Ethical considerations are crucial in the implementation and interpretation of guidance, and in rigorously evaluating justification for research. Governance must find a balance between the protection of research participants, who find themselves in particular circumstances of precarity, and the need for flexibility, preparedness, and responsiveness as emergencies unfold. Novel ethical orientations suggest the need, at times, to rethink established procedures, such as one-off ethics approval, or gold standard clinical trials, as well as to establish novel ethical procedures and practice, such as specially trained ethics committees, and pre-approval of research protocols. However, the ethics of such research also suggest that time, risk and uncertainty should not work against key ethical considerations relating to social value, fairness in recruitment or against meaningful and ongoing engagement with the community in all phases of response and research. A dynamic approach to the governance of GHER will also require supporting the ability of researchers, ethics committees and those governing research to engage with and act according to the ethical values at stake.

33 A Governance Framework for Advanced Therapies in Argentina Regenerative Medicine, Advanced Therapies, Foresight, Regulation and Governance

Fabiana Arzuaga

33.1 Introduction

Research in the field of regenerative medicine, especially that which uses cells and tissues as therapeutic agents, has given rise to new products called ‘advanced therapies’ or advanced therapeutic medicinal products (ATMPs). These cutting-edge advances in biomedical research have generated new areas for research at both an academic and industrial level and have posed new challenges for existing regulatory regimes applicable to therapeutic products. The leading domestic health regulatory agencies in the world, such as the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA), have regulated therapeutic tissues and cells as biological medicines and are currently making efforts to establish a harmonised regulatory system that facilitates the process of approval and implementation of clinical trials.

In the mid-2000s, the Argentine Republic did not have any regulations governing ATMPs, and governance approaches to them were weak and diverse. Although the process of designing a governance framework posed significant challenges, Argentina started to develop a regulatory framework in 2007. After more than ten years of work, this objective was achieved thanks to local efforts and the support of academic institutions and regulatory agencies from countries with more mature regulatory frameworks. In 2019, however, Argentina was leading in the creation of harmonised regulatory frameworks in Latin America.

In this chapter I will show how the framework was developed from a position of state non-intervention to the implementation of a governance framework that includes hard and soft law. I will identify the main objectives that drove this process, the role of international academic and regulatory collaborations, milestones and critical aspects of the construction of normative standards and the ultimate governance framework, and the lessons learned, in order to be able to transfer them to other jurisdictions.

33.2 The Evolution of Regulation of Biotechnology in Argentina: Agricultural Strength and Human Health Fragmentation

Since its advent in the middle of the 1990s, modern biotechnology has represented an opportunity for emerging economies to build capacity alongside high-income countries, thereby blurring the developed/developing divide in some areas (i.e. it represents a ‘leapfrog’ technology similar to mobile phones). For this to occur, and for maximum benefit to be realised, an innovation-friendly environment had to be fostered. Such an environment does not abdicate moral limits or public oversight but is characterised by regulatory clarity and flexibility.¹ The development of biotechnology in the agricultural sector in Argentina is an example of this. Although it had not been a technology-producing country, Argentina faced a series of favourable conditions that allowed the rapid adoption of genetically modified crops.² At the same time, significant institutional decisions were made, especially with regard to biosecurity regulations, with the creation of the National Commission for Agricultural Biotechnology (CONABIA) in 1991.³ These elements, together with the fact that Argentina has 26 million hectares of arable land, made the potential application of these technologies in Argentina – and outside the countries of origin of the technology, especially the USA – possible. This transformed Argentina into an exceptional ‘landing platform’ for the rapid adoption of these biotechnological developments. The massive incorporation of Roundup Ready (RR) soybean is explained by the reduction of its production costs and by the expansion of arable land. This positioned Argentina as the world’s leading exporter of genetically modified soybean and its derivatives.⁴

The development of biotechologies directed at human health was more complex and uncertain, and unfolded in a more contested and dynamic setting, which resulted in it evolving at a much slower pace, with regulation also developing more slowly, involving a greater number of stakeholders. This context, as will be demonstrated below, offered opportunities for developing new processual mechanisms aimed at soliciting and developing the views and concerns of diverse stakeholders.⁵

33.3 First Steps in the Creation of A Governance Framework for Cell Therapies

The direct antecedent of stem cells for therapeutic purposes is the hematopoietic progenitor cell (HPC), which has been extracted from bone marrow to treat blood diseases for more than fifty years and is considered an ‘established practice’.⁶ HPC transplantation is regulated by the Transplant Act 1993, and its regulatory authority is the National Institute for Transplantation (INCUCAI), which adopted regulations governing certain technical and procedural aspects of this practice in 1993 and 2007.⁷ This explains the rationale by which many countries – including Argentina – started regulating cell therapies under the a transplantation legal framework. However, Argentina’s active pursuit of regenerative medicine research aimed at developing stem cell solutions to health problems required something more, and despite its efforts to promote this research, there were no regulations or studies related to ethics and the law in this field.⁸

In 2007, the Advisory Commission on Regenerative Medicine and Cellular Therapies (Commission) was created under the National Agency of Promotion of Science and Technology (ANPCYT) and the Office of the Secretary of Science and Technology was transformed into the Ministry of Science, Technology and Productive Innovation (MOST) in 2008.⁹ The Commission comprised Argentinian experts in policy, regulation, science and ethics, and was set up initially with the objective of advising the ANPCYT in granting funds for research projects in regenerative medicine.¹⁰ However, faced with a legal gap and the increasing offer of unproven stem cells treatments to patients, this new body became the primary conduit for identifying policy needs around stem cell research and its regulation, including how existing regulatory institutions in Argentina such INCUCAI and the National Administration of Drugs, Food and Medical Technology (ANMAT), would be implicated.

The Commission promoted interactions with a wide range of stakeholders from the public and private sectors, the aim being to raise awareness and interest regarding the necessity of forging a governance framework for research and products approval in the field of regenerative medicine. In pursuing this ambitious objective, the Commission wanted to benefit from lessons from other regions or countries.¹¹ In 2007, it signed a Collaborative Agreement between the Argentine Secretary of Science and Technology and the University of Edinburgh’s AHRC SCRIPT Centre (the Arts and Humanities Research Council Research Centre for Studies in Intellectual Property & Technology Law).¹² This collaboration, addressed in greater detail below, extended to 2019 and was a key factor in the construction of the regulatory framework for ATMPs in Argentina.

33.4 From Transplants to Medicines

In 2007, in an attempt to halt the delivery of untested stem cell–based treatments that were not captured by the current regulatory regime applicable to HPCs, the Ministry of Health issued Resolution MS 610/2007, under the Transplant Act 1993. The 610/2007 Resolution states ‘activities related to the use of human cells for subsequent implantation in humans fall within the purview of the Transplant Authority (INCUCAI)’.¹³ This Resolution formally recognises INCUCAI’s competence to deal with activities involving the implantation of cellular material into humans. However, it is very brief and does not specify which type of cell it applies to, nor any specific procedures (kind of manipulation) to which cells it can be subject, an issue that is, in any event, beyond the scope of the Act.¹⁴ This Resolution is supplemented by Regulatory Decree 512/95, which, in Article 2, states that ‘any practice that involves implanting of human cells that does not fall within HPC transplantation is radically new and therefore is considered as experimental practice until it is demonstrated that it is safe and effective’.

To start a new experimental practice, researchers or medical practitioners must seek prior authorisation from INCUCAI by submitting a research protocol signed by the medical professional or team leader who will conduct the investigation, complying with all requirements of the regulations, including the provision of written informed consent signed by the research subjects, who must not be charged any monies to participate in the procedure. In May 2012, INCUCAI issued Resolution 119/2012, a technical standard to establish requirements and procedures for the preparation of cellular products. Substantively, it is in harmony with international standards of good laboratory and manufacturing practices governing this matter. However, very few protocols have been filed with INCUCAI since 2007, and the delivery of unproven stem cell treatments continued to grow, a situation that exposed INCUCAI’s difficulties in policing the field and reversing the growth of health scams.¹⁵

Another attempt to regulate was the imposition of obligations to register some cellular-based products as biological medicaments. The ANMAT issued two regulations under the Medicines Act 1964:¹⁶ Dispositions 7075/2011 and 7729/2011. These define ‘biological medicinal products’ as ‘products derived from living organisms like cells or tissues’, a definition that captures stem cell preparations, and they are categorised in both Dispositions as ATMPs. Cellular-based or biological medicaments must be registered with the National Drugs Registry (REM), and approval for marketing, use and application in humans falls within the scope of the Medicines Act and its implementing regulations. Cellular medicine manufacturers must register at the ANMAT as manufacturing establishments, and they must request product registration before marketing or commercialising their products.

Importantly, the ANMAT regulations do not apply in cases where ATMPs are manufactured entirely by an authorised medical centre, to be used exclusively in that centre. In that case, the local health authority maintains the right for approval. Like all regulations issued by the national Ministry of Health under the Medicines Act, the provisions of Dispositions 7075/2011 and 7729/2011 apply only in areas of national jurisdiction, in cases where interprovincial transit is implicated, or where ATMPs are imported or exported. In short, the Medicines Act is not applicable so long as the product does not leave the geographic jurisdiction of the province. And within the provinces, regulatory solutions were inconsistent; for example, in one they were regulated as transplants and in another as medicines.

As alluded to above, while imperfect regulatory attempts were pursued, the offer of unproven treatments with cells continued to grow. As in many countries, it was usual to find publications in the media reporting the – almost magical – healing power of stem cells, with little or no supporting evidence, and such claims have great impact on public opinion and on the decisions of individual patients. Moreover, the professionals offering these ‘treatments’ took refuge in the independence of medical practice and the autonomy that it offers, but it seems clear that some of the practices reported were directly contrary to established professional ethics, and they threatened the safety of patients receiving the treatments.¹⁷ In addition to the safety issues, given that these were experimental therapies (that have not been proven to be safe and effective), health insurers have stated their refusal to cover them (and one can anticipate the same antipathy to indemnifying patients who chose to accept them and are injured by them). Indeed, patients filed judicial actions demanding payment of such treatments by both health insurance institutions and the national and provincial state (as guarantors of public health).¹⁸

The regulatory regime – by virtue of its silence, its imperfect application to regenerative medicine and concomitant practices, and its shared authority between national and provincial bodies – permitted unethical practices to continue, and decisions of some courts have mandated the transfer of funds from the state (i.e. the social welfare system) to the medical centres offering these experimental cellular therapies. In short, the regime established a poorly coordinated regulatory patchwork that was proving to be insufficient to uniformly regulate regenerative medicine – and stem cell – research and its subsequent translation into clinical practice and treatments as ATMPs. Moreover, attempts by regulatory authorities to stop these practices, though valiant, also proved ineffective.

33.5 Key Drivers for the Construction of the Governance Framework

The landscape described above endured until 2017, when the Interministerial Commission for Research and Medicaments of Advanced Therapies (Interminsterial Commission) was created. This new body, jointly founded by the Ministry of Science and Technology (MOST) and the Ministry of Health (MOH), which also oversaw INCUCAI and ANMAT, was set up to:

1. 1. Advise the MOST and MOH in the subjects of their competence.

2. 2. Review current regulations on research, development and approval of products in order to propose and raise for the approval of the competent authority, a comprehensive and updated regulatory framework for advanced therapies.

3. 3. Promote dissemination within the scientific community and the population more broadly on the state of the art relating to ATMPs.

Led by a coordinator appointed by the MOST, the Interministerial Commission focused its efforts first on adopting a new regulatory framework that was harmonised with the EMA and FDA, and that recognised the strengths of local institutions in fulfilling its objectives. The strategy to create the governance framework was centred in three levels of norms: federal law, regulation and soft law. The proposal was accepted by both Ministries and efforts were made to put in force, first, the regulatory framework and soft law in order to stop the delivery of unproven treatments. These elements would then be in force while a bill of law was sent to the National Parliament.

On September 2018, the new regulatory framework was issued through ANMAT Disposition 179/2018 and an amendment to the Transplant Law giving competence to INCUCAI to deal with hematopoietic progenitor cells (CPH) in their different collection modalities, the cells, tissues and/or starting materials that originate, compose or form part of devices, medical products and medicines, as well as cells of human origin of autologous use used in the same therapeutic procedure with minimal manipulation and to perform the same function of origin.

The Interministerial Commission benefitted immensely from the work of the original Commission, which was formed in 2007 and which collaborated across technical fields and jurisdictional borders for a decade, moving Argentina from a position of no regulation for ATMPs, to one of imperfect regulation (limited by the conditions of the time). The original Commission undertook the following:

1. 1. Undertaking studies on the legislation of Argentina and other countries to better understand how these technical developments might be shaped by law (i.e. through transplant, medicines or a sui generis regime).

2. 2. Proposing a governance framework adapted to the Argentine legal and cultural context, harmonised with European and US normative frameworks.

3. 3. Communicating this initiative to all interested sectors and managing complex relationships to promote debate in society, and then translate learnings from that debate into a normative/governance plan.¹⁹

The work of the Commission was advanced through key collaborations; first and foremost with the University of Edinburgh (2007–2019). This collaboration had several strands and an active institutional relationship.²⁰

Other collaborations involved the Spanish Agency for Medicaments, the Argentine judiciary²¹ and the creation of the Patient Network for Advanced Therapies (APTA Network) to provide patients with accurate information about advances in science and their translation into healthcare applications. All this was accompanied by interactions with a range of medical societies in order to establish a scientific position in different areas of medicine against the offer of unproven treatments.²²

33.6 Current Legal/Regulatory Framework

The current legal framework in force and proposed by the Interministerial Commission is the result of a collaboration work focused on identifying the different processes involved in research and approval of ATMPs and set up an effective articulation between its parts. It consists of laws and regulations and establishes a coordinated intervention of both authorities, ANMAT and INCUCAI, in the process of approval of research and products. The system operates as follows:

1. 1. Medicaments Law establishes ANMAT with competence to regulate the scientific and technical requirements at national level applicable to clinical pharmacology studies, the authorisation of manufacturing establishments, production, registration and authorisation of commercialisation, and surveillance of Advanced Therapy Medicaments.²³

2. 2. Transplants Law establishes INCUCAI with competencies to regulate the stages of donation, obtaining, and control of cells and/or tissues from human beings when they are used as starting material in the production of an ATMP.²⁴

3. 3. Manufacturing establishments that produce ATMP must be authorised by ANMAT.

4. 4. When an ATMP is developed and used within the same facility, the donation, procurement, production and control stages are ruled under the INCUCAI regulations. INCUCAI must request the intervention of ANMAT for the evaluation and technical assistance in the stages of the manufacturing process, in order to guarantee that they meet the same standards as the rest of the Advanced Therapy Medications.

5. 5. Cell preparations containing cells of human origin with minimal manipulation are not considered medications and will be under the INCUCAI regulations.

Finally, the newly amended Argentine Civil Commercial Code 2015 establishes the ethico-legal requirements for clinical trials. Specifically, Article 58 states that investigations in human beings through interventions, such as treatments, preventative methods, and diagnostic or predictive tests, whose efficacy or safety are not scientifically proven, can only be carried out if specific requirements are met relating to consent, privacy, and a protocol that has received ethical approval, etc.

Laws and regulations above described combine to form a reasonably comprehensive normative system applicable to research, market access approval and pharmacovigilance for ATMPs, harmonised with international standards.

Importantly, and interestingly, though many stakeholders in the period 2011–2017 reported a preference for command-and-control models of regulation (i.e. state-led, top-down approaches)²⁵ and many elements of the prevailing regime do now reflect this, the framework itself emerged through a bottom-up, iterative process, which sought to connect abstract concepts and models of governance with actual experience and the national social and legal normative culture. While the Commission, together with a key circle of actors, shaped the process, a wide variety of stakeholders from academia, regulatory bodies, medical societies, researchers, patients and social media cooperated to advance the field. Their efforts were very much an example, imperfectly realised, of legal foresighting.²⁶

To complete the normative framework currently in force, it would be advisable to maintain a soft law design to provide support to regulatory bodies to maintain updated proceedings as well as the flexibility to accompany the advances of science. Finally, it would be prudent to count on a federal law that regulates clinical research, and fundamentally to provide the regulatory authority a robust policy power to stop the advance of eventual unproven treatments across the country as a legal warranty for the protection of patients and research human subjects.

33.7 Conclusion

The design and adoption of a governance framework for regenerative medicine research and ATMPs in the Argentine Republic has been a decade-long undertaking that has relied on the strengths and commitment of key institutions like MOST, MOH, ANMAT and INCUCAI and on the ongoing engagement with a range of stakeholders.

To achieve the current normative framework, it was necessary to amend existing legal instruments and issue new laws and regulations.

The new framework exemplifies a more joined-up regime that is harmonised with other important regulatory agencies like EMA and the FDA. This is important because the development of ATMPs is increasingly global in nature, and it is expected that Argentine regulators will work closely with international partners in multiple ways to support safe and effective innovation that will benefit a wider segment of the population, including, importantly, traditionally marginalised groups.