According to a widely held view, scientific modelling consists in entertaining a set of model descriptions that specify a model. Rather than studying the phenomenon of interest directly, scientists investigate the phenomenon indirectly via a model in the hope of learning about some of the phenomenon’s features. I call this view the description-driven modelling (DDM) account. I argue that although an accurate description of much of scientific research, the DDM account is found wanting as regards the mechanistic modelling found in (...) many branches of biology. By analysing research practices in cancer immunology concerning the development of mechanistic models of the process of cancer metastasis, this paper presents and argues for a complementary account of scientific modelling, herein called the experimentation-driven modelling (EDM) account. In EDM, scientists investigate a set of experimental systems and then integrate the results obtained from experiments into a mechanistic model. While EDM shares some key features with DDM, the two are epistemically very different approaches to research. (shrink)

There has been much discussion of the moral, legal and prudential implications of geoengineering, and of governance structures for both the research and deployment of such technologies. However, insufficient attention has been paid to how such measures might affect geoengineering in terms of the incentive structures which underwrite scientific progress. There is a tension between the features that make science productive, and the need to govern geoengineering research, which has thus far gone underappreciated. I emphasize how geoengineering research requires governance (...) which reaches beyond science’s traditional boundaries, and moreover requires knowledge which itself reaches beyond what we traditionally expect scientists to know about. How we govern emerging technologies should be sensitive to the incentive structures which drive science. (shrink)

Despite its vagueness Personalized, Precision, P4, P5, individualized, stratified medicine—or p-medicine in short—has become an increasingly popular term in biomedical literature. Philosophers have attempted to analyze what these various terms involve and have discussed consequences for medical practices. In this article, I argue that an important question remains unaddressed: what has made this project of p-medicine convincing to so many? My argument is that without real achievements, it would never have been. I also make the case that these achievements stem (...) from the domain of monoclonal antibodies, a new type of drug that justifies talks of personalized, precise, stratified, etc., medicine. In conclusion, while it may be possible to label any projection in the future of medicine as ‘p-medicine’, it is impossible to overlook mab-medicine as the spearhead. (shrink)