Cancer research is experiencing ‘paradigm instability’, since there are two rival theories of carcinogenesis which confront themselves, namely the somatic mutation theory and the tissue organization field theory. Despite this theoretical uncertainty, a huge quantity of data is available thanks to the improvement of genome sequencing techniques. Some authors think that the development of new statistical tools will be able to overcome the lack of a shared theoretical perspective on cancer by amalgamating as many data as possible. We think instead (...) that a deeper understanding of cancer can be achieved by means of more theoretical work, rather than by merely accumulating more data. To support our thesis, we introduce the analytic view of theory development, which rests on the concept of plausibility, and make clear in what sense plausibility and probability are distinct concepts. Then, the concept of plausibility is used to point out the ineliminable role played by the epistemic subject in the development of statistical tools and in the process of theory assessment. We then move to address a central issue in cancer research, namely the relevance of computational tools developed by bioinformaticists to detect driver mutations in the debate between the two main rival theories of carcinogenesis. Finally, we briefly extend our considerations on the role that plausibility plays in evidence amalgamation from cancer research to the more general issue of the divergences between frequentists and Bayesians in the philosophy of medicine and statistics. We argue that taking into account plausibility-based considerations can lead to clarify some epistemological shortcomings that afflict both these perspectives. (shrink)
In the last few decades, philosophy of science has increasingly focused on multilevel models and causal mechanistic explanations to account for complex biological phenomena. On the one hand, biological and biomedical works make extensive use of mechanistic concepts; on the other hand, philosophers have analyzed an increasing range of examples taken from different domains in the life sciences to test—support or criticize—the adequacy of mechanistic accounts. The article highlights some challenges in the elaboration of mechanistic explanations with a focus on (...) cancer research and neuropsychiatry. It jointly considers fields, which are usually dealt with separately, and keeps a close eye on scientific practice. The article has a twofold aim. First, it shows that identification of the explananda is a key issue when looking at dynamic processes and their implications in medical research and clinical practice. Second, it discusses the relevance of organizational accounts of mechanisms, and questions whether thorough self-sustaining mechanistic explanations can actually be provided when addressing cancer and psychiatric diseases. While acknowledging the merits of the wide ongoing debate on mechanistic models, the article challenges the mechanistic approach to explanation by discussing, in particular, explanatory and conceptual terms in the light of stances from medical cases. (shrink)
In the process of scientific discovery, knowledge ampliation is pursued by means of non-deductive inferences. When ampliative reasoning is performed, probabilities cannot be assigned objectively. One of the reasons is that we face the problem of the unconceived alternatives: we are unable to explore the space of all the possible alternatives to a given hypothesis, because we do not know how this space is shaped. So, if we want to adequately account for the process of knowledge ampliation, we need to (...) develop an account of the process of scientific discovery which is not exclusively based on probability calculus. We argue that the analytic view of the method of science advocated by Cellucci is interestingly suited to this goal, since it rests on the concept of plausibility. In this perspective, in order to account for how probabilities are in fact assigned in uncertain contexts and knowledge ampliation is really pursued, we have to take into account plausibility-based considerations. (shrink)
In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological realm entities are defined primarily by (...) the context they are embedded within—and hence by the web of relations they are part of. (shrink)
Cancer research has been at the forefront of biomedical activity in recent decades, and advances in molecular biology have provided a growing amount of information on the mechanisms involved in the etiopathogenesis of tumors. Nevertheless, despite these advances, the complexity of cancer is more evident, especially as different levels of phenomena are considered to explain the heterogeneity of the neoplastic process. A synthetic analysis of advances in cancer research illustrates these changes. In attempting to overcome the limits of epistemological reductionism, (...) there is a move from a view of a genetic basis for cancer to a more comprehensive perspective aiming to integrate a large amount of information and to understand the neoplastic phenomenon at higher levels of biological complexity through a new interpretative framework. (shrink)
La biodiversidad suele reconocerse en diferentes disciplinas como un valor universal. Ésta apunta a la heterogeneidad de las propiedades que caracterizan al mundo biológico. Sin embargo, a pesar de su uso común, el análisis crítico de la literatura filosófica pone en evidencia cierta dificultad a conceptualizar la biodiversidad, dada una aparente dicotomía entre los elementos normativos y descriptivos del término mismo. En este artículo se sostiene que es necesario considerar el aspecto relacional de la biodiversidad con el n de resolver (...) esta dicotomía. Esto significa que para ser un valor, cualquier diferencia en el mundo natural que sea definida en términos de biodiversidad implicará, a nivel conceptual y explicativo, la relación intrínseca entre lo que tenga en común con las entidades y lo que sea específico de éstas. De esta manera la biodiversidad será un concepto explicativo por sí mismo. Una visión relacional de la biodiversidad también hace reconocer el carácter multidimensional de dicha noción, lo que ha probado ser realmente útil en diferentes contextos, pudiéndose caracterizar propiamente en términos de “riqueza” implicada por el concepto de la biodiversidad. (shrink)
In this article, we argue, first, that there are very different research projects that fall under the heading of “systems biology of cancer.” While they share some general features, they differ in their aims and theoretical commitments. Second, we argue that some explanations in systems biology of cancer are concerned with properties of signaling networks and how they may play an important causal role in patterns of vulnerability to cancer. Further, some systems biological explanations are compelling illustrations of how “top-down” (...) and “bottom-up” approaches to the same phenomena may be integrated. (shrink)
The philosophical discussion of emergence is often focused on properties of ‘wholes’ that are evaluated as emergent with respect to the properties of ‘parts’. Downward causation is, consequently, evaluated as some kind of causal influence of whole properties over parts properties. Yet, several important cases in scientific practice seem to be pursuing hypotheses of parts properties emerging from wholes properties, inverting the instinctive association of emergence with wholes. Furthermore, some areas of reflection which are very important for emergence, e.g., the (...) philosophy of consciousness, do not allow mapping properties onto part-whole organizations. The conceptual puzzle is solved by constructing a framework that disentangles the mereological dimension from the superventional dimension. By liberalizing the spatio-temporal allocation of emergent properties, the proposed dual framework could better capture the way in which emergence and downward causation are addressed in scientific practice. (shrink)
This book offers a multidisciplinary look at the much-debated concept of “personalized medicine”. By combining a humanistic and a scientific approach, the book builds up a multidimensional way to understand the limits and potentialities of a personalized approach in medicine and healthcare. The book reflects on personalized medicine and complex diseases, the relationship between personalized medicine and the new bio-technologies, personalized medicine and personalized nutrition, and on some ethical, political, economic, and social implications of personalized medicine. This volume is of (...) interest to researchers from several disciplines including philosophy, bio-medicine, and the social sciences. (shrink)
This volume reviews examples and notions of robustness at several levels of biological organization. It tackles many philosophical and conceptual issues and casts an outlook on the future challenges of robustness studies in the context of a practice-oriented philosophy of science. The focus of discussion is on concrete case studies. These highlight the necessity of a level-dependent description of robust biological behaviors.Experts from the neurosciences, biochemistry, ecology, biology, and the history and the philosophy of life sciences provide a multiplex perspective (...) on the topic. Contributions span from protein folding, to cell-level robustness, to organismal and developmental robustness, to sensorimotor systems, up to the robustness of ecological systems.Several chapters detail neurobiological case-studies. The brain, the poster child of plasticity in biology, offers multiple examples of robustness. Neurobiology explores the importance of temporal organization and multiscalarity in making this robustness-with-plasticity possible. The discussion also includes structures well beyond the brain, such as muscles and the complex feedback loops involved in the peculiar robustness of music perception. Overall, the volume grounds general reflections upon concrete case studies, opening to all the life sciences but also to non-biological and bio-inspired fields such as post-modern engineering. It will appeal to researchers, students, as well as non-expert readers. (shrink)
Drawing on shared research experiences and collaborative projects, this book offers a broad and timely perspective on research on the hand and its current challenges. It especially emphasizes the interdisciplinary context in which researchers need to be trained in contemporary science. From language to psychology, from neurology to the social sciences, and from art to philosophy and religion, the chapters discuss various aspects involved in hand research and therapy. On the basis of concrete and validated case studies, they approach hand (...) function and gestures from different perspectives – not only neurological and medical, but also philosophical, evolutionary and anthropological. By highlighting the overlaps between different areas of research, the book seeks to foster better communication between researchers, and ultimately a better understanding of hand function and its recovery. It offers essential information and inspirations for students, researchers and practitioners in the fields of psychology, epistemology, bioengineering, neuroscience, anthropology and bioethics. (shrink)
This book provides a critical reflection on automated science and addresses the question whether the computational tools we developed in last decades are changing the way we humans do science. More concretely: Can machines replace scientists in crucial aspects of scientific practice? The contributors to this book rethink and refine some of the main concepts by which science is understood, drawing a fascinating picture of the developments we expect over the next decades of human-machine co-evolution. The volume covers examples from (...) various fields and areas, such as molecular biology, climate modeling, clinical medicine, and artificial intelligence. The explosion of technological tools and drivers for scientific research calls for a renewed understanding of the human character of science. This book aims precisely to contribute to such a renewed understanding of science. (shrink)
If well-designed, the results of a Randomised Clinical Trial can justify a causal claim between treatment and effect in the study population; however, additional information might be needed to carry over this result to another population. RCTs have been criticized exactly on grounds of failing to provide this sort of information Evidence, inference and enquiry. Oxford University Press, New York, 2011), as well as to black-box important details regarding the mechanisms underpinning the causal law instantiated by the RCT result. On (...) the other side, so-called In Silico Clinical Trials face the same criticisms addressed against standard modelling and simulation techniques, and cannot be equated to experiments Philosophy of molecular medicine: foundational issues in research and practice, Routledge, New York, 2017; Parker in Synthese 169:483–496, 2009; Parke in Philos Sci 81:516–536, 2014; Diez Roux in Am J Epidemiol 181:100–102, 2015 and related discussions in Frigg and Reiss in Synthese 169:593–613, 2009; Winsberg in Synthese 169:575–592, 2009; Beisbart and Norton in Int Stud Philos Sci 26:403–422, 2012). We undertake a formal analysis of both methods in order to identify their distinct contribution to causal inference in the clinical setting. Britton et al.’s study :E2098–E2105, 2013) on the impact of ion current variability on cardiac electrophysiology is used for illustrative purposes. We deduce that, by predicting variability through interpolation, ISCTs aid with problems regarding extrapolation of RCTs results, and therefore in assessing their external validity. Furthermore, ISCTs can be said to encode “thick” causal knowledge —as opposed to “thin” difference-making information inferred from RCTs. Hence, ISCTs and RCTs cannot replace one another but rather, they are complementary in that the former provide information about the determinants of variability of causal effects, while the latter can, under certain conditions, establish causality in the first place. (shrink)
Robustness has lately become a bridging notion, in particular across the sciences of the natural and the artificial, crucial for prediction and control of natural and artificial systems in recent scientific practice, in biomedicine, neurobiology and engineering, as well as for risk management, planning and policy in ecology, healthcare, markets and economy. From biological, neurological and societal systems, arising by the interplay of self-organizing dynamics and environmental pressures, to the current sophisticated engineering that aims at artificially reproducing the adaptability and (...) resilience of living systems in front of perturbations in man-made devices, robustness seems to hold the key for orchestrating stability and change. This introduction offers a general survey of the contribution that the notion of robustness is providing to reframing major concepts within the life sciences, such as development, evolution, time and environment, and to reframing the relationship between biology and engineering, as well as between biology and physics. (shrink)