International Society for History, Philosophy, and Social Studies of Biology

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FRIDAY, JULY 10  /  11:00 - 12:30  /  DS-R515
Individual papers
Modeling and Mechanisms in Medicine

How Newtonian was Newtonian medicine?

Kirsten Walsh** (University of Otago, Canada)

With the publication of the Principia in 1687, Newton introduced a powerful new methodology. He combined the solid foundation of experiment and observation with the rigour of mathematical reasoning. By the 1690s, the ‘Newtonian method’ had spread beyond mechanics to other branches of natural and even general philosophy. In Scotland, there emerged a ‘Newtonian medicine’—a starkly mathematical approach to medicine that viewed the human body as a machine, to be explained by geometrical and mechanical principles. This mathematical form of Newtonian medicine all but disappeared in the 1730s, to be replaced by an aethereal Newtonian medicine, based on the queries introduced in the 1717 edition of Newton’s Opticks. Focusing on Newtonian theories of disease, I follow this transition from mathematical to aethereal Newtonianism, asking: How Newtonian was Newtonian medicine?

Extrapolation and its challenges: How explanatory accounts are pieced together from multiple experimental models

Tudor Baetu (Universidade do Vale do Rio dos Sinos, Brazil)

Not only clinical research, but also basic science systematically relies on the epistemic practice of extrapolation from surrogate models, to the point that explanatory accounts presented in review papers and biology textbooks are in fact composite pictures reconstituted from data gathered in a variety of distinct experimental setups. This raises two new challenges to previously proposed mechanistic-similarity solutions to the problem of extrapolation, one pertaining to the absence of mechanistic knowledge in the early stages of research and the second to the large number of extrapolations underpinning explanatory accounts. An analysis of the strategies deployed in experimental research supports the conclusion that, while results from validated surrogate models are treated as a legitimate line of evidence supporting claims about target systems, the overall structure of research projects also demonstrates that extrapolative inferences are not considered ‘definitive’ or ‘sufficient’ evidence, but only partially justified hypotheses subjected to further testing. Almost two decades ago, LaFollette and Shanks mounted a strong case against the use of animal surrogate models in clinical research, on the grounds that extrapolative inferences are useful only as means to generate new hypotheses. In response, Daniel Steel pointed out that there is no sharp divide between the contexts of discovery and justification, arguing that, when properly regimented by validation protocols, extrapolations are a common and reliable method of generating new knowledge. An analysis of the experimental practice of basic science suggests that the truth is somewhere in the middle. Steel is right in claiming that the use of surrogate models is both a common and a reliable scientific method, and that extrapolations from surrogate to target can be justified by means of a variety of theoretical and experimental considerations. I argue that, given the systematic use of extrapolative inferences and the overall absence of strong indicators of relevant similarity in basic science, the justificatory evidence supporting extrapolations is not deemed definitive, as demonstrated by the subsequent efforts deployed to further test knowledge gained by juxtaposing results from different experimental setups. Extrapolations are merely one epistemic tool to be used in conjunction with other methods of investigation, ranging from cross-referencing findings in complementary surrogate models to clinical trials of treatments. Understanding why extrapolation is an acceptable epistemic practice requires thinking beyond the reliability of individual extrapolations, and understanding how extrapolations are used in the context of a much more comprehensive research strategy that combines both a bottom-up process of inferring mechanistic accounts based on experimental data–a process that relies heavily on extrapolations across different experimental setup –, and a subsequent top-down testing of predictions made by these accounts. More specifically, I propose that extrapolations are an acceptable epistemic practice not only in light of model validation attempts, but also because they are part of an overall research strategy ensuring that relatively poorly justified extrapolations in the initial stages of research are tested in later stages of research, and that fallback positions make possible the troubleshooting of faulty extrapolations.

Identity and unity: Challenges for the “immune self”

Anna Frammartino Wilks (Acadia University, Canada)

As the self/other dichotomy continues to come under attack by contemporary immunologists, the possibility of a coherent notion of the immune self appears increasingly less plausible. Recent findings from both the ecological perspective (Cohen 2013) and the molecular perspective (Matzinger 2002) offer substantial evidence for the view that “there can be no circumscribed, self-defined entity that is designated – the self” (Tauber 2012). Alternative and diverse models of immunology are currently being developed which aim to accommodate the ample evidence that we now have of the continual and complex interactions between the inner workings of the host organism and the material it encounters in its environment. Consequently, the notion of immune identity has been supplanted by the notion of immune reactivity (Tauber 2012). Moreover the specific kind of reactivity manifested by immunological function indicates that the immune system is a cognitive system. While this paper generally defends the cognitive paradigm of immunology, it rejects one of its central precepts. Specifically, it rejects the view that the non-identity of the immune self implies its lack of unity. My defense of this position is rooted in the account of cognition of Immanuel Kant, which views the function of unity as the fundamental feature of cognition (Brook 1994). I argue that if the immune self were not able to function as a unity, it would not be able to function as a cognitive system. The reason is that a cognitive system, like any system, involves the synthesis or working together of “many” as “one.” Thus an intelligible account of the cognitive view of immunology may dispense with the notion of the identity of the immune self (Pradeu 2012), but it may not dispense with at least a functional notion of the unity of the immune self.