Precision medicine is frequently described as a revolutionary approach that will transform medical research and healthcare by focussing on “individual differences in people’s genes, environments, and lifestyles” (White House, 2015). However, scholars in history, philosophy, and social studies of biomedicine have questioned whether this is more than hype and good PR (Maughan, 2017). While tailoring treatments to individual preferences promises a more humanised, holistic approach (Vogt & Green, 2020), critics warn of overdiagnosis, overpromising and, medicalization (Vogt et al., 2019), and argue that precision medicine may paradoxically increase uncertainty in medicine (Kimmelman & Tannock, 2018).
In this session, we want to take up these critical lines of inquiry, but give them a specific twist. We want to ask to what extent the described negative aspects and perils of precision medicine are intrinsic to its approach. In particular, we want to explore to what extent precision medicine exhibits “deconstructivist tendencies” in several respects, namely in terms of the deconstruction of (1) evidence standards in research and healthcare, (2) traditional disease categories, (3) biological materiality, and (4) the doctor-patient relationship.
In order to explore these issues and related implications for precision medicine and healthcare, this symposium will bring together an international group of interdisciplinary scholars who will analyse these questions from historical, philosophical, and STS perspectives.
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Uncertainty has recently been highlighted as a paradoxical consequence of precision medicine (PM). In science and medicine, uncertainty is often conceptualized as something that can be clearly delimited; it is framed as a lack of information or insufficient understanding that can be reduced or overcome by more research, better tools etc. Applied to the context of PM, this would mean that PM can ultimately solve its own uncertainty-related problems. We want to put pressure on this assumption and defend the claim that uncertainty in PM cannot always be avoided or eliminated. Differentiating between socio-technical, epistemic and ontological uncertainty, we point to evidence that uncertainty does not only result from missing or incomplete information, but also from insights into biomedical complexity. It is, at least in some respects, non-transient – in others, a reduction of uncertainty will entail epistemic trade-offs.
We will explore three aspects of PM responsible for the (possibly fundamental) irreducibility of uncertainty. (1) PM is a self-propelling uncertainty generator as it accelerates the usual scientific development logic enormously in that newly discovered findings reveal ever more new layers of gaps in knowledge (e.g. questioning the traditional organ-based disease classification by newly discovered pathophysiological pathways). (2) It is highly inter- and transdisciplinary, challenging the synthesis of conclusive information from the different types of evidence in the biomedical laboratory, the clinic, epidemiological studies “in the real world” etc. because these research areas work according to different research frameworks, practices, styles of reasoning and epistemological affinities. (3) PM has deconstructivist tendencies, as it breaks down biological materiality into patterns, numbers and correlations that cannot be reintegrated to form a holistic and meaningful picture.
These observations lead to a fundamental reorientation in the way uncertainty needs to be understood and navigated in clinical practice.
Current discourse on the ethical and epistemological challenges of AI-supported medical decision support tends to put the (essential) epistemic opacity of the decision support algorithm center stage. Central arguments in favor of explainability interfaces focus on sustaining the medical personnel’s capacity to assume responsibility and engage in shared decision-making practice. Within the latter, interfaces supporting explainability should facilitate the contestation of outputs of medical decision support systems with reasoning that can be based on patient-individual factors, such as subjective value trade-offs and life-worldly constraints and conditions. To some extent these factors will (and perhaps even should) plausibly remain exterior to the AI-based decision support logic. However, this entire line of thought typically follows the assumption that the medical subject matter—correlations and causality when following symptoms or classification features to diagnoses to possible treatments—is itself sufficiently well-understood to be conveyed within conversations between physicians and patients, in which adequate actions can be contested and jointly deliberated. If precision medicine will indeed exhibit deconstructivist tendencies of evidence standards, disease categories and statements about biologically material entities as suggested by Borck/Lohse, the issue of epistemic opacity extends well into the medical subject matter and it remains unclear what communicable items are left to guide shared decision-making. The proposed presentation revisits key arguments from the explainability debate under the assumption of partial or increasingly deconstructivist tendencies that suggests two options: (1) Gradually surrendering the ideal of patient-centric medicine to precision medicine’s inference machine, whose curative and preventive power must, in turn, be all the more ascertained, or (2) acknowledging that precision medicine must finally take seriously its interface with patient-centric shared decision-making practices as a relevant pitfall for effective and ethical translation. The contribution will critically discuss both options.
An emerging area of application for precision medicine is digital technologies, as suggested by Engelmann in this session. For instance medical wearable devices are designed to be worn constantly and can provide an indication of individual parameters. The possibility of using these devices for monitoring an personal physiology and obtain a continuous, precise, and personalised data collection, resulting in a continuous stream of clinical and health data from a single patient without spending time and money for medical visits, is very promising for tailored healthcare, and has been presented and marketed as a new medical revolution.
However, the use of these technologies can lead to the possible deconstruction of crucial conceptual differences, including evidence standards and doctor-patient relations. We present two reasons that suggest caution in this direction.
The first deconstruction has to do with the fact that wearables are simultaneously consumer and clinical tools. Wearables are increasingly blurring the the lines between what is medically advisable and what is commercially profitable, thus creating the need to come up with new conceptual and regulatory approaches to understanding what counts as a medical device. The second deconstruction is related to increased dangers of overdiagnosis. Wearables monitor a whole array of biomarkers without interruption and this can lead to interpreting as pathological biological variations that would hardly be noticed and might not carry clinical interest. This blurs the lines between what counts as abnormal and pathological, and calls for a redefinition of risk factors – also in connection to the distinction between disease and illness discussed by Friedman later in the session.
Our analysis shows that deconstructive tendencies of precision medicine extend through digital technology and points to the risks that such deconstructions can erode trust relationships, with troubling similarities to reasons for hesitancy in other areas of medicine.
In this paper, I argue that PM extensive use of medical technologies like (tracking) wearables deconstructs the epistemic division of labor between doctors and patients, the relations between patients and their bodies, and malady narratives.
Traditionally, patients are epistemically responsible for diagnosing illness, and doctors are epistemically responsible for diagnosing disease. However, with the wish to promote patient empowerment, PM makes extensive use of wearable technologies that encourage patients to diagnose diseases over illness, which results in multi-diagnoses of disease; diagnosis of a disease is no longer made exclusively by biomedical professionals, and what counts as biomedically pathological is not exclusively determined by the biomedical community but affected and deconstructed by the algorithms in use and commercial interests. This new division of labor epistemically limits doctors and patients from sharing their knowledge and, therefore, restricts health promotion.
Additionally, although wearables can allow more personalized care by saving the time spent performing measurements in clinical settings, they can also create alienation that hinders this effort. The use of wearable technologies can distort the patient's connection to her own body. By that, wearables can also contribute to the deconstruction of patients' experience of symptoms, which can affect medical research.
Furthermore, these technologies, in combination with AI, distance the doctor from the patient. The reliance of doctors and patients on the analysis provided by wearables deconstructs narratives of maladies that no longer belong to them. These deconstructive tendencies result in ‘synthetic narratives’, that can reduce doctors' sense of accountability for patients' health and create an illusion of autonomy and participation. Although medical-related technologies have always shaped how we talk and describe medical conditions, I argue that wearables in the context of PM not only shape but deconstruct narratives. This can result in the distortion of the clinical interaction and, therefore, warrants special attention.
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