Elodie Giroux

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

This chapter views philosophy of medicine as a domain within philosophy of science as opposed to a province of bioethics. Thus, it first deals with the philosophical analysis of health, disease, and illness concepts and with the scientific nature of medicine. Relative to the second theme, it addresses questions relative to the causes and explanations of disease and the status of theories in biomedical science. A central concern here is the status and nature of _proof_ in medicine and the relationship between theory and practice at the heart of evidence-based medicine. Finally, the chapter focuses on the specific problems raised by causal analysis and experimentation in medicine and on the nature of clinical reasoning.

Au cours de la pandémie de Covid-19, les idées d’“écouter la science” ou de “suivre les scientifiques” ont été fréquemment mobilisées comme arme rhétorique pour asseoir la légitimité ou la supériorité de décisions politiques. Dans cet article, nous partons de ce cas d’étude pour discuter de l’emploi adéquat des connaissances scientifiques dans la prise de décision politique. Nous faisons d'abord une discussion critique du "modèle linéaire", vision où le consensus scientifique dicte les décisions politiques. Ce modèle s'avère contre-productif et stérile pour les situations décisionnelles complexes, telles que la pandémie de Covid-19. A partir de ces critiques, nous articulons un modèle pluraliste, où les options politiques sont construites et informées par un dialogue entre une science pluraliste des valeurs (non-)épistémiques. Nous montrons enfin que les obstacles identifiés à l'application pratique de ce modèle sont soit infondés ou impropres au pluralisme en particulier.

The notion of risk questions our dominant and traditional medical approach to health phenomena: a binary normal-pathological model anchored in the pathophysiological framework. For risk factors which are continuous biological variables such as hypertension or hypercholesterolemia, the demarcation line between a level which would be ‘normal’, ‘at risk’, or ‘pathological’ is drawn in a conventional and non-fixed manner. Above all, these risk factors, which are the subject of preventive treatment, are increasingly considered as diseases in their own right. This shift would reinforce the pathologisation of human life and the associated problems of overdiagnosis and overtreatment. However, while it is easy to see the value of clarifying and specifying the distinction between ‘risk’ and ‘disease’ when dealing with those problems, finding the best way to do so remains challenging. In this chapter, I begin by describing the confusion between these two categories. I then show that the conceptual analysis, in particular, the naturalistic definition of disease, fails to provide a satisfactory distinction. Finally, I argue that this distinction can be better established if we understand the epidemiological risk approach as a different way of modelling health phenomena than the binary and categorical approach of pathophysiology.

Since the completion of the Human Genome Project (HGP), biomedical sciences have moved away from a gene-centred view and towards a multi-factorial one in which environment, broadly speaking, plays a central role in the determination of human health and disease. Environmental exposures have been shown to be highly prevalent in disease causation. They are considered as complementary to genetic factors in the etiology of diseases, hence the introduction of the concept of the “exposome” as encompassing the totality of human environmental exposures, from conception onwards (Wild in Cancer Epidemiol Biomark Prev 14:1847–1850, 2005), and the launch of the Human Exposome Project (HEP) which aims to complement the HGP. At first sight, and seen as complementary to the genome, the exposome could thus appear as contributing to the rise of novel postgenomic deterministic narratives which place the environment at their core. Is this really the case? If so, what sort of determinism is at work in exposomics research? Is it a case of environmental determinism, and if so, in what sense? Or is it a new sort of deterministic view? In this paper, we first show that causal narratives in exposomics are still very similar to gene-centred deterministic narratives. They correspond to a form of Laplacian determinism and, above all, to what Claude Bernard called the “determinism of a phenomenon”. Second, we introduce the notion of “reversed heuristic determinism” to characterize the specific deterministic narratives present in exposomics. Indeed, the accepted sorts of external environmental exposures conceived as being at the origins of diseases are determined, methodologically speaking, by their identifiable internal and biological markers. We conclude by highlighting the most relevant implications of the presence of this heuristic determinism in exposomics research.

Staging and stratification are two diagnostic approaches that have introduced a more dynamic outlook on the development of diseases, thus participating in blurring the line between the normal and the pathological. First, diagnostic staging, aiming to capture how diseases evolve in time and/or space through identifiable and gradually more severe stages, may be said to lean on an underlying assumption of “temporal determinism”. Stratification, on the other hand, allows for the identification of various prognostic or predictive subgroups based on specific markers, relying on a more “mechanistic” or “statistical” form of determinism. There are two medical fields in which these developments have played a significant role and have given rise to sometimes profound nosological transformations: oncology and psychiatry. Drawing on examples from these two fields, this paper aims to provide much needed conceptual clarifications on both staging and stratification in order to outline how several epistemological and ethical issues may, in turn, arise. We argue that diagnostic staging ought to be detached from the assumption of temporal determinism, though it should still play an essential role in adapting interventions to stage. In doing so, it would help counterbalance stratification’s own epistemological and ethical shortcomings. In this sense, the reflections and propositions developed in psychiatry can offer invaluable insights regarding how adopting a more transdiagnostic and cross-cutting perspective on temporality and disease dynamics may help combine both staging and stratification in clinical practice.

L’exposome réfère à un domaine émergent de recherche qui a pour visée de développer une science intégrée de l’ensemble des expositions auxquelles est soumis un individu tout au long de sa vie et qui influencent sa santé. Deux principales orientations se font jour. L’une se concentre sur l’étude de l’exposome interne qui permettrait d’identifier l’essentiel des expositions impactant la santé en mesurant avec précision les effets au niveau de l’environnement biochimique du corps. L’autre entend intégrer les expositions sociales, écologiques et les expositions biologiques et internes, ou autrement dit, faire davantage de place à l’étude de l’exposome externe et ainsi développer un modèle holiste de la santé environnementale. À partir de l’examen de la littérature scientifique, de l’analyse de la première génération d’études exposomiques (2010-2020) et d’entretiens menés auprès d’épidémiologistes engagés dans ces recherches, cet article propose un état des lieux des promesses et réalisations de ce domaine émergent quant à l’intégration des expositions, tout en ayant l’ambition d’apporter un regard critique sur ces dernières. Après avoir présenté l’exposome et ses diverses interprétations, nous examinerons quel type d’intégration est en jeu dans chacune de ces deux orientations et nous en questionnerons l’intérêt et la pertinence. Notre analyse se concentre plus particulièrement sur la seconde orientation : quels gages cette tendance la plus holiste donne-t-elle en vue d’un renouvellement de nos manières d’intégrer les facteurs environnementaux et génétiques, sociaux et biologiques, dans notre approche des expositions et de l’explication des maladies?

Evidence-Based Medicine (EBM) and Personalized Medicine (PM) share a common goal: reducing the gap between the results of biomedical research and their clinical application. PM is, however, often presented as a “new paradigm” for medicine, just as EBM was in the 1990s. It covers a wide variety of projects but the core idea that generally unites them is the ambition of better taking account of individual specificities than did EBM with its statistical and population-centred approach. In this article, I concentrate on PM in cancerology, the essence of which is to target treatments based on the molecular profile of the patient. This targeting is made possible by gaining better knowledge about the molecular mechanisms of cancers. The classification of patients as a function of their molecular profile entails the creation of patient sub-groups. This creates a problem for the traditional evaluation of therapeutic treatment promoted by EBM, in particular the use of randomized trials using sizeable cohorts. But a better understanding of the mechanisms and the greater precision of treatments could reduce the need for these trials. Does PM thus represent the revenge of a physio-pathological and mechanistic culture in clinical research against the statistical and empirical one of EBM? My objective is to show how current practices of PM leads to epistemological changes in our estimation of what count as relevant types of information and proof in medicine, in particular in the field of therapeutic evaluation. I defend the idea that PM, far from obviating the need for statistical approaches and the search for correlations, ultimately poses new challenges for EBM. PM drives EBM to strengthen the articulation and the integration of statistical and mechanistic data with a view to providing a better service for each patient.

The goal of this chapter is to describe the philosophical style of Jean Gayon through my own experience as a Ph.D. student. I show how Gayon’s work represents a unique synthesis of two main traditions in philosophy of science: analytical Anglo-American philosophy of sciencePhilosophy of science (Anglo-American) and biology and French historical epistemologyGayon, JeanOn historical epistemology. HisHistorical epistemology openness and curiosity towards the Anglo-American tradition led him to believe that a genuine dialogue between these traditions could benefit both. Jean also encouraged his graduate students to draw on multiple philosophical approaches, with an eye toward the sciences. In this chapter, I propose to characterize his own style as a historically grounded analysis of concepts. The analytical style he promoted is underpinned by historical reflection in which it finds a concrete and living substratum.

This article presents a comparative analysis between Georges Canguilhem’sEssay on Some Problems Concerning the Normal and the Pathological, published in 1943 and the English language debate that started in the 1970s between the naturalists and the normativists. Seemingly, this comparison illustrates the opposition between the French historical epistemology and the Anglo-American philosophy of sciences. However, I put into perspective what is generally considered an opposition between the two traditions by analyzing certain conceptual similarities.

Christopher Boorse’s bio-statistical theory of health and disease argues that the central discipline on which theoretical medicine relies is physiology. His theory has been much discussed but little has been said about its focus on physiology or, conversely, about the role that other biomedical disciplines may play in establishing a theoretical concept of health. Since at least the 1950s, epidemiology has gained in strength and legitimacy as an independent medical science that contributes to our knowledge of health and disease. Indeed, it not only provides important information about disease distribution and aetiology, but the risk-factor approach it employs seems to challenge BST’s binary conception of health and disease. The objective of the article is to show, firstly, how important information deriving from descriptive and analytical epidemiology forms part of our contemporary medical concepts of health and disease, and secondly, that these elements are not taken into account by BST in a satisfactory way. The article’s central contention, therefore, is that if the project of defining the theoretical concept of health is to be maintained, more importance should be accorded to the contribution made by epidemiology—alongside physiology—in defining health

La possibilité d’une définition naturaliste de la santé et d’une distinction entre le normal et le pathologique qui ne repose pas sur des normes culturelles, sociales ou subjectives est au cœur des débats en philosophie de la médecine. Or le concept statistique de la normalité, fondamental pour une définition objective de la santé, soulève d’importantes difficultés. Christopher Boorse défend une « théorie bio-statistique » qui, en articulant ce concept à une notion non normative de fonction biologique, résoudrait ces difficultés. L’identification de la santé et de la normalité au sens statistique demeure toutefois centrale dans sa définition. Après avoir précisé le rôle que joue la normalité statistique dans la BST, nous dégageons, à partir de l’épidémiologie contemporaine, un certain nombre de problèmes et questions que cette définition naturaliste soulève.The liability for a naturalist definition of health and for a value-free distinction between the normal and the pathological is at the core of discussions on health and disease in philosophy of medicine. But the statistical concept of normality, a central one for any objective definition of health, raises numerous problems. Christopher Boorse argues for a « biostatistical theory » which aims at solving these difficulties by articulating a statistical concept of normality and a non-normative concept of biological function. However the BST is still based on identifying normality and health with the most frequent. After analyzing in details the true role of statistical normality in BST, I will show how results and data from modern epidemiology can be mobilized to reveal several limits and difficulties with respect to this naturalist definition of health and disease.