Mistrust of the black box: the public auditing of private models in the chemicals regulatory space

ABSTRACT

Metrics foster trust in governing bodies, but their uncertainty can elicit an opposite sentiment of mistrust. In chemicals governance, most of the conversations concerning computational models revolve around their uncertainty, and the extent to which simulations of safe doses can be transposed in regulatory decisions. To understand the source of this mistrust in models, research in science and technology studies on policy modeling, particularly research that looks at models as an interface between science and policy, must be extended to consider the private production of predictions. Looking at the full set of actors involved in predictive regulatory knowledge – companies, regulatory agencies, modelers working with one or the other – and their concurrent articulations of uncertainty, it appears that regulators audit physiologically based pharmacokinetic models (PBPK, a key class of models used to compute safe chemical doses), because the chemical industry initially introduced them to challenge its methods of risk assessment. Regulators and their modelers established model auditing, to be able to negotiate the predictive claims of companies and their consultants. At the end of the day, neither companies nor regulators appear to dominate the production of predictive knowledge. It is the product of the shifting distribution of expertise in the regulatory space, and of the outcomes of the recurrent trials of credibility that this distribution enables.

KEYWORDS:

• Computational modeling
• risk assessment
• chemical regulation
• industry
• PBPK

Acknowledgments

I thank all of the persons who accepted to be interviewed for the purpose of this research, particularly Melvin Andersen and Harvey Clewell.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Source: PBPK modeler, UK Health & Safety Executive, interview with the author.

2 A factor of 10 is applied to account for differences between animals and humans. An additional factor of 10 may be applied (i.e., 100 in total) if humans are exposed to the substance through multiple routes. Yet another factor of 10 (i.e., 1000 in total) will be applied if vulnerable populations are exposed to the substance (children or pregnant women, for instance).

3 Source: interview with the author.

4 Source: interview with the author.

5 Source: interview with the author.

6 The publications were retrieved from the Web of Science-Clavirate database, using a request that compounded a number of terms used for PBPK (PB-PK, physiologically based pharmacokinetic, PBTK, PB-TK, physiologically based toxicokinetics, etc.), in the areas of toxicology, environmental sciences or public health (WOS categories). The corpus was analyzed thanks to the CorText Manager, which allows for computing the frequency with which two authors publish together, using a distributional statistical test (Breucker et al., 2016). All other scientometric analyses presented in this article were performed using CorText Manager.

7 Source: interview with the author.

8 Source: PBPK modeler, Environmental Protection Agency, interview with the author.

9 Source: PBPK modeler, Environmental Protection Agency, interview with the author.

Additional information

Funding

This work was supported by Agence Nationale de la Recherche [13-SOIN-0005].

Notes on contributors

David Demortain

David Demortain is a sociologist and researcher in science and technology studies, with interest in the politics of knowledge and expertise, specifically in the area of risk and chemical regulation. He is an INRAE research professor and director of the Laboratoire Interdisciplinaire Sciences Innovations Sociétés (LISIS) in France.