Public announcements of breakthroughs in diagnosing Alzheimerās disease regularly appear in newspapers, radio and television programmes, and on the web. The types of diagnostic tests recommended range from MRI and PET scans of the brain, to spinal taps, blood tests, simple eye cell tests, and even smelling peanut butter. Most of these tests measure so-called ābiomarkersā: certain molecules in the body that are linked with the pathology thought to underlie Alzheimerās disease. The usual claim is that these tests are more reliable, less burdensome, faster and/or cheaper than existing diagnostic procedures. But most importantly, the novel tests are thought to reveal Alzheimerās at an early stage, possibly even years before the onset of symptoms.
Early diagnosis of Alzheimerās disease (or AD) is indeed an important, worldwide goal of current research and development in the Alzheimer field (Lock 2013). However, this goal raises controversy, in society, in healthcare, even among those active in Alzheimer research themselves. Proponents argue that an early diagnosis may help to plan oneās future lifeāfor example, by deciding whether to continue living in oneās own house, by making care arrangements in a timely manner, and possibly, by signing a living will guiding decision making with regard to end of life. Moreover, medication is thought to be possibly more effective when started early. An early diagnosis, followed by early medication, might then help to keep the disease at bay. However, opponents counter that this hope is futile. Current medication slows down the disease, but does not cure it. Early diagnosis and early medication, thus, probably will just extend the time spent on worrying about oneās mental capacities. What is the use of an early diagnosis, critics argue, if nothing can be done about the disease? Some even suspect that the whole search for early diagnostics is largely driven by an attempt of ābig pharmaā to increase the market for their AD drugs. Whatever the motives driving R&D, the response to news items or blogs announcing diagnostic breakthroughs shows that people do indeed hold different views about the desirability of early diagnosis for AD.
The Desirability of Biomarker Diagnostics of Alzheimerās Disease
From an ethical and societal perspective, the desirability of early diagnostics for AD is, then, not self-evident. As in other cases of emerging technologies, novel tests for AD raise the question whether we should do everything we can. Should early diagnostics for AD be introduced in society? This book delves into the issues raised by the promises of early diagnostics for AD by asking under which conditions emerging diagnostic technologies for AD could be considered a responsible innovation. This question entails more than a reflection on the ethical and/or social acceptability of novel tests. In our view, the question whether it is ethically and socially acceptable to introduce early diagnosis for AD is important, but not sufficient. Three additional questions need to be addressed as well. First, we need to inquire how āAlzheimerās diseaseā gets defined in discussions about early diagnostics in the first place, since it refers to an equivocal, poorly delineated phenomenon. Second, it is important to critically assess the plausibility of the promises and expectations about the new diagnostic technologies to avoid speculative ethics. And last but not least, if we are interested in the ethical and social acceptability of these emerging technologies, we should not only identify and weigh social and ethical values, but we should also examine the capacity of contemporary society to productively respond to the diversity of viewpoints, concerns, and interests voiced with regard to these technologies. We will briefly discuss these three questions, and then, return to the ambition of responsible innovation.
According to historians and philosophers of medicine, the phenomenon of AD is notoriously elusive. The German psychiatrist Alois Alzheimer, in 1906, during an autopsy, identified āplaques and tanglesā in the brains of a patient who had suffered from what was then known as āsenile dementiaā at a relatively young age. Whereas the plaques had been seen before, the tangles were a new phenomenon. It was actually Alzheimerās boss, Emil Kraepelin, whoāin the 1910 edition of his famous classification of psychiatric diseasesācoined the term āAlzheimerās diseaseā. AD was defined as a specific form of dementia, diagnosed in the case of a young age of onset of the dementia symptoms and when, at autopsy, both plaques and tangles were found. (The presence of plaques and tangles has been part of the gold standard for diagnosing AD ever since.) The disease has been distinguished from other forms of dementia, that is, by its pathological features. Since its inception, however, the assumed relation between clinical features and pathological signs of the disease has been shifting time and again. As the historian Jesse Ballenger (2006) has shown, both the definition of the clinical picture and of the pathology of AD have evolved. Even more importantly, whatever the definitions used, the relation between clinical and pathological phenomena has never been unambiguous. Plaques and tangles can be absent in persons clinically diagnosed with AD, whereas they may be present in the brain of people who did not experience any trouble during their lifetime.
Clarifying the relationship between clinical features and pathology is complicated, for various reasons. First, usually, there is a time lag between clinical observations (during life) and pathological observations (at autopsy). During life, we can only see the dementia symptoms, not the AD pathology. Part of the promise of current research is that molecular biomarkers will help to overcome this lag, because they can show pathology in vivo. However, ageing is a confounding influence. Are the clinical and pathological observations characteristic of ānormal ageingā or of a disease? Moreover, the clinical symptoms of AD are various and not very specific. They may signify others types of dementia. And in particular, older patients often suffer from other diseases (they have āco-morbidityā). To what extent current candidate biomarkers are specific for AD is as yet unclear. All this variety has brought some researchers to the conclusion that AD should not be seen as a unified disease, but as a diffuse syndrome of several phenomena (Richards and Brayne 2010; Richard et al. 2012). These phenomena, moreover, are not just present or absent, but can show different grades of severity. This goes both for the clinical and the pathological manifestations. In sum, suggesting that biomarker testing can reveal AD is a vague claim, to say the least. Without further clarification, such claims ignore the ambiguity of the label and the complexity of the associated phenomena. Since assessing the desirability of diagnosing AD is impossible if we do not know what is being diagnosed, this volume will pay ample attention to the different meanings of the AD label in different contexts. This is also the reason we do not limit attention to AD, but focus on emerging AD diagnostics in the broader context of diagnosing and dealing with dementia.
The second task is to critically assess the promises or expectations about how easy, convenient, early, and reliable diagnosing AD will be in the future, due to new technologies. Clearly, clarifying the meaning of AD in such claims is a first step, as well as asking what exactly is made visible by the new technology, and what this tells about the prospects of the individuals tested. The rhetoric of breakthroughs and revolutions is typical for emerging science and technology in general, but the field of AD research seems particularly prone to it. AD is perceived by many as an awful disease that they dread, and this anxiety is reinforced by predictions about rising numbers of AD patients in the near futureāfrequently expressed in terms of an Alzheimer ātsunamiā or an āepidemicā. With the awareness that decades of R&D have not resulted in an effective cure, any positive news from the R&D trenches is easily framed (by researchers, media, politics, policymakers, and public alike) as a reason for optimism and hope. For discussions about the desirability of early diagnosis, however, it is crucial to determine what these promises and expectations are actually based on. If a targeted biomarker is tested only in mice, it may be rather premature to claim that early diagnosis is near. In a similar vein, if the candidate biomarker is considered to be a predecessor of the plaques associated with AD, what does that mean for people suffering from complaints, but not displaying plaques and tangles? And will biomarker diagnostics be a āstand-aloneā test offering a yes/no verdict, as often suggested, or will it rather be an āadd onā to the existing diagnostic repertoire? Assessing the plausibility of the promises and expectations raised on behalf of emerging diagnostic technologies helps to avoid what has been called āspeculative ethicsā (Nordmann 2007; Nordmann and Rip 2009; Lucivero et al. 2011). It is a prerequisite for down-to-earth reflection and debate on the ethical and societal desirability of emerging biomarker tools.
Third, asking about the ethical and social acceptability of introducing emerging technologies for diagnosing AD suggests that after weighing the pros and cons, only two answers are possible: yes or no; end of story. Moreover, the implicit assumption is that society canāand willāact on such an ethical verdict, as if there is a central gatekeeper determining whether the technology should be allowed. This seems an overestimation of both the willingness and the ability of current societies to steer innovation, or, if you prefer, an underestimation of the complexity of innovation processes. It is not very likely, for example, that contemporary governments will forbid industry from pursuing specific goals in R&D, unless there are serious concerns to health, environment, and safety. Diagnostic test providers can also easily avoid self-regulation by doctors (e.g., in the form of clinical guidelines for diagnosing AD) by offering direct-to-consumer-testing via the internet. More importantly, aiming for a yes/no verdict neglects opportunities for shaping innovation processes and their products in a more desirable direction. It may result in an unproductive sequence of emerging innovations and ethical or societal rejection of such innovations. Asking about conditions for responsible innovation allows us to bring into focus ways of shaping emerging technologies to align with society and its values, and at the same time to identify the actors (or actor groups) responsible for doing so.
Responsible Innovation
Our choice to reflect on the desirability of emerging biomarker diagnostics for AD in terms of responsible innovation is in line with (and a product of) a growing interest in āresponsible innovationā more generally. The notion of responsible research and innovation (for reasons of brevity, from now on, referred to as āresponsible innovationā) has recently emerged as a guiding concept in discussions about the scienceāsociety relationshipāin particular in Europe and to a lesser extent in the USA. It is rooted in the observation that scientific and technological advances not only produce benefits, but may have unintended and undesirable impacts, and that regulating the products of these advances (e.g., by requiring risk assessment) is insufficient, and sometimes, impossible because of the uncertainties involved. By aiming for āresponsible innovationā, attention is sought not only for the potential negative impacts of innovation, but also for the positive ones. To achieve an overall positive result, both the process and the products of scientific research, technology development, and implementation should be designed in such a way that they contribute to relevant and acceptable societal goals. To make science and technology align better with society, its values should be integrated into the full innovation trajectory. Finally, the concept of responsible innovation explicitly puts on the agenda the question who, in the largely collective and complex endeavour of innovation, should take care of what to work towards relevant and acceptable benefits.
The notion of responsible innovation, thus, refers to an overarching concern and a set of partly overlapping approaches and concomitant definitions. Currently, two definitions and frameworks are widely cited. The first is by Von Schomberg:
Responsible Research and Innovation is a transparent, interactive process by which societal actors and innovators become mutually responsive to each other with a view to the (ethical) acceptability, sustainability and societal desirability of the innovation process and its marketable products (in order to allow a proper embedding of scientific and technological advances in our society). (Von Schomberg 2013, p. 63)
In this definition, responsible research and innovation designates the search for the right impacts of science and technology. Von Schomberg observes that shared criteria to determine what these āright impactsā are, are not easy to identify in current pluralistic societies. However, he argues that the values democratically agreed upon in the Treaty of the European Union might serve as normative anchor points to decide what is ethically acceptable and socially desirable. These include scientific and technological advance, sustainable development, competitive social market economy, social justice, equality, solidarity, fundamental rights, and a high level of quality of life. As the definition indicates, both the process and the products of innovation need to be assessed in terms of these anchor points to ensure responsible research and innovation.
Von Schomberg developed his take on responsible research and innovation in the context of European research funding and research policymaking, and his approach addresses this level of policymaking in the first place. Some scholars have argued that these rather abstract principles offer less guidance for specific R&D projects (Stilgoe et al. 2013, p. 1577). It is, for instance, not clear how to identify which principles are at stake in a specific setting, nor how to interpret their meaning when it comes to decisions in a specific innovation trajectory, or how to balance them. The approach of responsible innovation proposed by Stilgoe, Owen, and Macnaghten is, therefore, more concerned with particular domains in science and technology. It was developed on the basis of an inventory of concerns recurring in public debates about new domains of science and technology. These target the products, the process, and the purpose of innovation, and responsible innovation in this approach is a way to embed deliberation on thes...