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. (shrink)

We live in the Age of Big Data. In medicine, artificial intelligence and machine learning algorithms, fueled by big data, promise to change how physicians make diagnoses, determine prognoses, and develop new treatments. An exponential rise in articles on these topics is seen in the medical literature. Recent applications range from the use of deep learning neural networks to diagnose diabetic retinopathy and skin cancer from image databases, to the use of various machine learning algorithms for prognostication in cancer and (...) cardiovascular disease. Many factors are driving the adoption of AI in health care, from... (shrink)

It is unknown to what extent medical researchers generalize study findings beyond their samples when their sample size, sample diversity, or knowledge of conditions that support external validity do not warrant it. It is also unknown to what extent medical researchers describe their results with precise quantifications or unquantified generalizations, i.e., generics, that can obscure variations between individuals. We therefore systematically reviewed all prospective studies (n = 533) published in the top four highest ranking medical journals, Lancet, New England Journal (...) of Medicine (NEJM), Journal of the American Medical Association (JAMA), and the British Medical Journal (BMJ), from January 2022 to May 2023. We additionally reviewed all NEJM Journal Watch clinical research summaries (n = 143) published during the same time. Of all research articles reporting prospective studies, 52.5% included generalizations beyond specific national study populations, with the numbers of articles with generics varying significantly between journals (JAMA = 12%; Lancet = 77%) (p < 0.001, V = 0.48). There was no evidence that articles containing broader generalizations or generics were correlated with larger or more nationally diverse samples. Moreover, only 10.2% of articles with generalizations beyond specific national populations reported external validity strengthening factors that could potentially support such extrapolations. There was no evidence that original research articles and NEJM Journal Watch summaries intended for practitioners differed in their use of broad generalizations, including generics. Finally, from the journal with the highest citation impact, articles containing broader conclusions were correlated with more citations. Since there was no evidence that studies with generalizations beyond specific national study populations or with generics were associated with larger, more nationally diverse samples, or with reports of population similarity that may permit extensions of conclusions, our findings suggest that the generalizations in many articles were insufficiently supported. Caution against overly broad generalizations in medical research is warranted. (shrink)

“Actionability” is a key concept in precision oncology. Its precise definition, however, remains contested. This article undertakes a philosophical analysis of “actionability” to aid in conceptual clarification. We map distinct concepts of actionability, arguing that each is best understood as a contextually objective category articulated to mitigate risk of “conceptual slippage.” We defend “interactive pluralism,” acknowledging the need for distinct concepts but also for conceptual interaction in practice. This article thus offers insights for both practitioners and philosophers, clarifying approaches to (...) actionability for scientists and clinicians and serving as a case study to test competing views on scientific pluralism. (shrink)

Naturalistic theories of disease appeal to concepts of biological function, and use the notion of dysfunction as the basis of their definitions. Debates in the philosophy of biology demonstrate how attributing functions in organisms and establishing the function-dysfunction distinction is by no means straightforward. This problematization of functional ascription has undermined naturalistic theories and led some authors to abandon the concept of dysfunction, favoring instead definitions based in normative criteria or phenomenological approaches. Although this work has enhanced our understanding of (...) disease and illness, we need not necessarily abandon naturalistic concepts of function and dysfunction in the disease debate. This article attempts to move towards a new naturalistic theory of disease that overcomes the limitations of previous definitions and offers advantages in the clinical setting. Our approach involves a re-evaluation of concepts of biological function employed by naturalistic theories. Drawing on recent insights from the philosophy of biology, we develop a contextual and evaluative account of function that is better suited to clinical medicine and remains consistent with contemporary naturalism. We also show how an updated naturalistic view shares important affinities with normativist and phenomenological positions, suggesting a possibility for consilience in the disease debate. (shrink)

Cancer has garnered increasing interest among philosophers. This chapter focuses on cancer medicine and precision oncology, an influential approach to cancer which seeks to individualize treatment on the basis of genetic or molecular features of disease. It reviews a range of ontological, epistemic, and ethical questions raised by precision oncology, relating developments in cancer medicine to broader issues in the philosophy of science and medicine.

ABSTRACT: Generalizations in medical research can be informative, but also misleading. Building on recent work in the philosophy of science and ethics of communication, I offer a novel analysis of common generalizations in clinical trials as generics in natural language. Generics, which express generalizations without terms of quantification, have attracted considerable attention from philosophers, psychologists, and linguists. My analysis draws on probabilistic and contextual features of generics to diagnose how these generalizations function and malfunction across communicative contexts in medicine. Given (...) a high risk of misinterpretation ("slippage"), I recommend avoidance of generic claims about medical interventions in public contexts, exemplified by clinical trials and medical research more generally. Generics should only be used with vigilance in private contexts, exemplified by the physician–patient encounter. My analysis provides tools to support vigilance when communicating with generics, suggests new norms for public science communication, and raises deeper questions in the ethics of clinical communication. (shrink)

Minimal residual disease (MRD), a measure of residual cancer cells, is a concept increasingly employed in precision oncology, touted as a key predictive biomarker to guide treatment decisions. This paper critically analyzes the expanding role of MRD as a predictive biomarker in hematologic cancers. I outline the argument for MRD as a predictive biomarker, articulating its premises and the empirical conditions that must hold for them to be true. I show how these conditions, while met in paradigmatic cases of MRD (...) use in cancer, may not hold across other cancers where MRD is currently being applied, weakening the argument that MRD serves as an effective predictive biomarker across cancer medicine. (shrink)

The COVID-19 global pandemic has stretched the capacities of public health institutions and health systems around the world, opening the door to a range of technologically-driven solutions. In this article, we seek to historicize the expanding role of digital health technologies and examine the political-economic context from which they have emerged. Drawing on critical insights from science and technology studies, we maintain that the rise of digital health technologies has been catalyzed by broad shifts in global health governance that have (...) expanded the role of market forces in public health and a unique set of political and economic crises that have accelerated the adoption of digital technologies—often under the guise of appeals to technological innovation to address “unprecedented” crises. These interrelated historical trends, we contend, are critical for understanding current state responses to the pandemic and possibilities for more equitable and democratic applications of technology in public health. (shrink)