Abstract
The paper deals with the introduction of nanotechnology in biochips. Based on interviews and theoretical reflections, it explores blind spots left by technology assessment and ethical investigations. These have focused on possible consequences of increased diffusability of a diagnostic device, neglecting both the context of research as well as increased accuracy, despite it being a more essential feature of nanobiochip projects. Also, rather than one of many parallel aspects (technical, legal and social) in innovation processes, ethics is considered here as a ubiquitous system of choices between sometimes antagonistic values. Thus, the paper investigates what is at stake when accuracy is balanced with other practical values in different contexts. Dramatic nanotechnological increase of accuracy in biochips can raise ethical issues, since it is at odds with other values such as diffusability and reliability. But those issues will not be as revolutionary as is often claimed: neither in diagnostics, because accuracy of measurements is not accuracy of diagnostics; nor in research, because a boost in measurement accuracy is not sufficient to overcome significance-chasing malpractices. The conclusion extends to methodological recommendations.
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Notes
For the view that “value conflict is (…) at the heart of the design process”, see Van de Poel (2009).
A case-by-case approach has been advocated by Hoet et al. (2009).
This study took place between 2010 and 2012. It included visits to laboratories, interviews, and a survey of published and grey literature.
The gene that codes for enzyme CYP2D6 (or Cytochrome P450 2D6), which is involved in the metabolization of a certain number of drugs. The parameter measured by the test is the possibility and speed of metabolization, which will be returned as one of four values (poor, intermediate, extensive or ultrarapid metabolizer). Previous tests involved injecting the patient with a substrate of the enzyme, and a subsequent plasma assay. DNA chip measures the expression of the gene and its copies.
“Roche’s microarray tests US FDA’s diagnostic policy”, Nature Biotechnology, 21/9, News, 2003, p. 959.
Interview with Thierry Livache, Commissariat à l’Énergie Atomique (CEA), Grenoble, France, April 5th, 2011.
“Despite wide usage, microarray data frequently contain at least 5 % missing values and in most datasets, at least 60 % of genes have one or more missing values. Once microarray images have been scanned, the problematic spots are identified as missing values with the reason for such occurrences include slide scratches, spotting problems, blemishes on the chip, hybridization error, image corruption or simply dust on the slide. (…) missing values can seriously impact upon subsequent data analysis (…)”.
However, the situation remains equivalent for the sequencing of DNA, since the replication of its structure (still a feature of modern sequencers) is a source of error whatever the method. The so-called “third (or “next-next”) generation sequencing” is likely to rely on nano-based processes to perform sequencing from native DNA strands. One of these projects even pretends to potentially achieve absolute error-free sequencing (Blow 2008).
And, by the way, they need an accurate balance to compare values.
Official criteria of regulatory agencies are not necessarily named after some of their underlying or component values. For the FDA, see for instance Russek-Cohen et al. (2011).
Pietzsch and Paté-Cornell (2008) suggest that early HTA shall take evidence “from previous generations of the technology” (p. 37). This should therefore include the context of use.
Other quantitative techniques can be mentioned, such as FISH and ELISA. To some extent, FISH has similar drawbacks when compared to IHC as flow cytometry (expensive, time-consuming and more technical to interpret), while ELISA lacks sensitivity and is rather a complementary test. See for instance Yeh (2002).
Interview with Pr. Frédérique Spyratos, Institut Curie, Saint-Cloud, France, March 12th, 2012.
Interviewed scientists “were clearly worried about the quality of their own and their colleagues’ data but they were not overly concerned with data that are purposively manipulated. Rather they were troubled by problems with data that lie in what they see as a “gray area”, problems that arise from being too busy or from the difficulty of finding the line between “cleaning” data and “cooking” data. (…) It is not always easy for researchers to decide when uncorrected errors in the data become outright falsification. How do scientists actually clean their data? They often rely on their experience, cleaning out unanticipated findings and preserving what they “know” they would find”.
Devices do not come void of any values before they enter the validation process. Designers have embedded values into it.
However, it seems excessive to speak of a “morality of artifacts”, as these authors do. Indeed, the propagation of normative constraints through artifacts does not imply that users will bend their behavior for moral reasons: it may even be the opposite, since they cannot choose anymore how to behave.
Following authors who advocate that ethical investigation should not remain exterior to technological design (see for instance Feenberg 2004, and Van de Poel and Verbeek 2006), it can be asked how upstream in the innovation process (leading from innovative design in high-throughput instruments to the clinical interpretation of data at the bedside, including intermediate stages of clinical trials, association studies and model-building) it is possible to identify ethical issues. In the case of the present research project, interviews did not reveal such issues among instrument designers (Nurock and Pellé 2012): either their interest in ethics dealt with debates that were not connected with their own field or, when they were so connected, the designer’s commitment (against genetic determinism) had no practical impact on the technological details of his biochip projects. Ethical commitment was explicit in the work of model-builders (who explain that the choice of fundamental properties of their model stems directly from their personal rejection of genetic determinism); but this model does not translate into technological or methodological specifications for biomarker detection.
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Acknowledgments
This work was carried out within the Nano2E (“Nanotechnologies : Épistémologie et Éthique”) project n°ANR-09-NANO-001 funded by the French National Research Agency (ANR) in the frame of its 2009 programme in Nanosciences, Nanotechnologies and Nanosystems (P3N2009). The author would like to thank the Nano2E project team (X. Guchet, B. Bensaude-Vincent, V. Nurock, S. Pellé, S. Loève), and the anonymous reviewers for their helpful comments and criticism.
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Le Roux, R. A Matter of Accuracy. Nanobiochips in Diagnostics and in Research: Ethical Issues as Value Trade-Offs. Sci Eng Ethics 21, 343–358 (2015). https://doi.org/10.1007/s11948-014-9550-z
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DOI: https://doi.org/10.1007/s11948-014-9550-z