ArgumentThis article uses four historical case studies to address epistemological issues related to the animal model of human diseases and its use in medical research on human diseases. The knowledge derived from animal models is widely assumed to be highly valid and predictive of reactions by human organisms. In this contribution, I use three significant historical cases of failure (ca. 1890, 1960, 2006), and a closer look at the emergence of the concept around 1860/70, to elucidate core assumptions related to (...) the specific practices of animal-human knowledge transfer, and to analyze the explanations provided by historical actors after each of the failures. Based on these examples, I argue that the epistemological status of the animal model changed from that of a helpful methodological tool for addressing specific questions, but with precarious validity, to an obligatory method for the production of strong knowledge on human diseases. As a result, there now exists a culture of biomedical research in human disease that, for more than a century, has taken the value of this methodological tool as self-evident, and more or less beyond question. (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)

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)