It is assumed that scientific models contain no superfluous model elements in scientific representation. A representational model is constructed with all the model elements serving the representational purpose. The received view has it that there are no redundant model elements which are non-representational. Contrary to this received view, I argue that there exist some non-representational model elements which are essential in scientific representation. I call them representation-supporting model elements in virtue of the fact that they play the role to support (...) the representational role of representational model elements. Representation-supporting model elements, which have a characteristic of dependability, are not to be eliminated in the process of modeling although they are playing second fiddle to representational model elements in scientific representation. (shrink)

According to Haber and Benham (2012), a sufficient condition for full moral consideration is that a creature bears a genealogical relation to the Homo sapiens lineage. Since part-humans do not bear such a relation, they are not due full moral consideration on that basis. Given this argument, my aim in this commentary is twofold. First, I want to challenge its soundness by showing that it is possible for part-humans to bear a genealogical relation to the H. sapiens lineage. Second, I (...) want to argue that Haber and Benham's attempt at avoiding moral confusion by reframing ethical concerns about part-humans doesn’t work. (shrink)

Human–nonhuman chimeras have been the focus of ethical controversies for more than a decade, yet some related issues remain unaddressed. For example, little has been said about the relationship between the origin of transferred cells and the morally relevant capacities to which they may give rise. Consider, for example, a developing mouse fetus that receives a brain stem cell transplant from a human and another that receives a brain stem cell transplant from a dolphin. If both chimeras acquire morally relevant (...) capacities as a result of transplantation, and if those capacities are indistinguishable, should the difference in cell origin matter to how we classify these creatures? I argue that if morally relevant capacities are easy to detect, cell origin is irrelevant to how the chimera ought to be treated. However, if such capacities are hard to detect, cell origin should play a role in considerations about how to treat the chimera. (shrink)

Much of the book is aimed at persuading the reader that genes are not ‘the prime movers in all biological processes’ and that ‘postgenomic genes’ are better understood in a functional sense, as ‘things an organism can do with its genome.' With the main argument in place, the authors examine its impact on a number of philosophical debates. I will discuss three of them: causation, information, and reduction.

Although neurological disease and mental illness can cause terrible human suffering, strategies for researching their causes and cures are not obvious. Invasive brain research on actual human being...

The American Journal of Bioethics, Volume 12, Issue 9, Page 30-32, September 2012.

In 2015 scientists called for a partial ban on genome editing in human germline cells. This call was a response to the rapid development of the CRISPR–Cas9 system, a molecular tool that allows researchers to modify genomic DNA in living organisms with high precision and ease of use. Importantly, the ban was meant to be a trust-building exercise that promises a ‘prudent’ way forward. The goal of this paper is to analyse whether the ban can deliver on this promise. To (...) do so the focus will be put on the precedent on which the current ban is modelled, namely the Asilomar ban on recombinant DNA technology. The analysis of this case will show (a) that the Asilomar ban was successful because of a specific two-step containment strategy it employed and (b) that this two-step approach is also key to making the current ban work. It will be argued, however, that the Asilomar strategy cannot be transferred to human genome editing and that the current ban therefore fails to deliver on its promise. The paper will close with a reflection on the reasons for this failure and on what can be learned from it about the regulation of novel molecular tools. (shrink)

The ways in which other animal species can be informative about human biology are not exhausted by the traditional picture of the animal model. In this paper, I propose to distinguish two roles which laboratory organisms can have in biomedical research. In the more traditional case, organisms act as surrogates for human beings, and as such are expected to be more manageable replicas of humans. However, animal models can inform us about human biology in a much less straightforward way, by (...) being used as measuring devices—what I call their instrumental role. I first characterize this role and provide criteria for it, before illustrating it with some examples from biomedical research, especially cancer research. In such an instrumental role, phenotypes are not expected to phenocopy human phenomena, but instead have the purely instrumental value of detecting or measuring differences. I argue that the instrumental role is more prevalent than might first be suspected, and that some characteristics of contemporary biomedical research are increasingly shifting the use of laboratory organisms to the instrumental role. Finally, in light of the distinction proposed, I discuss the meaning of the expression “animal model”. (shrink)

Leading animal models are powerful tools for translational research, but they also present obstacles. Poorly conducted preclinical research in animals is a common cause of translational failure, but even when such research is well-designed and carefully executed, challenges remain. In particular, dominant models may bias research directions, elide essential aspects of human disease, omit important context, or subtly shift research targets. Recognizing these stumbling blocks can help us find ways to avoid them: employing a wider range of models, incorporating more (...) realistic environmental conditions, better aligning studies between animals and patients, and focusing on human biology and therapeutic goals. Such changes are costly; but insisting it would be impractical or unrealistic to change strategies offers no way out of the current impasse. Rather, we must acknowledge the obstacles as well as the advantages presented by core models, and direct some of our investments in translational research toward getting around them. The dominance of biomedical research by a handful of animal models introduces subtle but significant obstacles to translation. Recognizing these obstacles is a critical first step toward finding ways around them; this paper describes how dominant models can create roadblocks, and suggests strategies to improve the efficiency of translation from animal models to humans. (shrink)

Both clinical research and basic science rely 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. 1 Introduction2 Surrogate Models2.1 What exactly is a surrogate model?2.2 Why use surrogate models?3 Prior Validation of Surrogate Models3.1 The validation and ranking of surrogate models in the early stages of basic research3.2 The validation of surrogate models in later stages of basic research and in clinical research4 ‘Big Picture’ Accounts and the Extrapolations Underpinning Them4.1 The mosaic nature of mechanistic descriptions in basic science4.2 Challenges for mechanistic-similarity-based validation protocols5 Retrospective Testing of Extrapolated Knowledge5.1 Holistic confirmation5.2 Fallback strategies6 Conclusions. (shrink)

A survey of models in immunology is conducted and distinct kinds of models are characterized based on whether models are material or conceptual, the distinctiveness of their epistemic purpose, and the criteria for evaluating the goodness of a model relative to its intended purpose. I argue that the diversity of models in interdisciplinary fields such as immunology reflects the fact that information about the phenomena of interest is gathered from different sources using multiple methods of investigation. To each model is (...) attached a description specifying how information about a phenomenon of interest has been acquired, highlighting points of commonality and difference between the methodological and epistemic histories of the information encapsulated in different models. These points of commonality and difference allow investigators to integrate findings from different models into more comprehensive explanatory accounts, as well as to troubleshoot anomalies and faulty accounts by going back to the original building blocks. (shrink)