5 research outputs found
When is it Safe to Edit the Human Germline
In the fall of 2018 Jiankui He shocked the international community with the following announcement: two female babies, “Lulu” and “Nana,” whose germlines had been modified by the cutting edge, yet profoundly unsafe CRISPR-Cas9 technology had been born. This event galvanized policy makers and scientists to advocate for more explicit and firm regulation of human germline gene editing (GGE). Recent policy proposals attempt to integrate safety considerations and public input to identify specific types of diseases that may be safe targets for human GGE (Sarkar forthcoming; Guttinger 2019; Lander et al. 2019). This paper argues these policy proposals are inadequate in different ways. While Sarkar (forthcoming) intends to incorporate input from the disability community for the purpose of deciding the value of human GGE, I argue that his strategy for doing so is inadequate. I’ll argue that an iterative, deliberative process is a more appropriate framework for allowing the disability community to inform policy on human GGE. Further policy proposals have been framed in terms of monogenetic or single-gene diseases (Guttinger 2019; Lander et al. 2019). I argue that this way of conceptualizing disease is not what matters for deciding which disorders are viable candidates for human GGE. Instead, what matters is that (1) the disease in question must have (among its set of causes) genes that have a high degree of causal control with respect to the disease and (2) alternative nucleic acid sequences variants that are likely to produce traits deemed desirable must be identified. Previous policy proposals leave (2) unspecified. What conditions must be met for satisfying condition (2) should not be left to individual scientists to decide for themselves. The present proposal offers some guidance on this issue
CRISPR-Cas Changing Biology?
Eugene V. Koonin argues that fundamental research of CRISPR-Cas mechanisms has (among other things) illuminated “fundamental principles of genome manipulation.” Koonin's discussion provides important philosophical insights for how we should understand the significance of CRISPR-Cas systems. Yet the analysis he provides is only part of a larger story. There is also a human element to the CRISPR-Cas story that concerns its development as a technology. Accounting for this part of CRISPR's history reveals that the story Koonin provides requires greater nuance. I'll show how CRISPR-Cas technologies are not “natural” genome editing systems, but (in part) artifacts of human ingenuity. Furthermore, I'll argue that the story of CRISPR-Cas is not “primarily about research into fundamental biological mechanisms”, but is instead about the intertwining of applied and fundamental research programs
Engineering Novel Proteins with Orthogonal tRNA: Artificial Causes that make a Difference
Model organisms, the use of green fluorescent proteins, and orthogonal transfer RNA (tRNA) are examples of artificial causes being used in biology. Recent work characterizing the research interests of biologists in terms of a common set of values has ruled out artificial causes as biologically interesting. For instance, Kenneth Waters argues that biologists are primarily interested in causes that actually obtain. Similarly, Marcel Weber argues that biologists are primarily concerned with biologically normal interventions. Both views express a widely received attitude about the interests and goals of biologists as being primarily concerned with the contingent facts of our world. While I agree with this general attitude about the contingent nature of biology, I argue that neither view fully accounts for the diversity that distinguishes the discipline. Along with actual and biologically normal causes, biologists are also interested in artificial causes for technological and observational purposes. I maintain that research interest in artificial causes provides some pragmatic reasons for thinking that research programs in cellular biology aren’t driven by a common core set of values
The Scope of Biology
When new technology pushes the frontier of a scientific discipline, often our understanding of the nature of that discipline needs to be revised. My dissertation explores how biological technologies challenge common views about the nature of causal selection in biology as discussed in the philosophy of biology literature. Causal selection is the practice of ontologically privileging some causal conditions over others for investigative and explanatory reasons. For causal selection to be justified, two conditions must be met. First, the causal conditions that get singled out as ontologically significant must possess a causal or explanatory property that sets them apart from others. Second, the property identified must be one whose biologists regard as genuinely illuminating and particularly relevant to their domain of inquiry. The first condition justifies causal selection on ontological grounds; the second accounts for what is unique to the domain of biology. I consider two recently proposed accounts of causal selection: the actual difference making approach and the biologically normal approach. Although both adequately satisfy the first condition, they fall short in meeting the second. I demonstrate that the causal selection literature gets the full scope of biology wrong by failing to account for how biologists make genuinely new things happen with technology. When developing new technologies like orthogonal transfer RNA, green fluorescent protein, the CRISPR-Cas gene editing system, and DREADDs, biologists must often imagine and hypothesize the nonactual and the non-normal. This practice suggests that biologists expect their domain of inquiry to extend significantly beyond both the actual and the biologically normal. I defend a more nuanced account of causal selection that better accommodates biological technology. The core of this account is that factors capable of having fine-grained influence over processes characteristic to life and living things are ontologically significant causes in biology