Moving towards a holistic approach for human health risk assessment – Is the current approach fit for purpose?

Abstract

It is recognised that new scientific improvements and their integration in risk assessment, as outlined in the National Academies of Sciences, Engineering and Medicine 2017 report, have the potential to improve human health risk assessments by enabling a mechanistic understanding of adverse effects and more accurate predictions of biological responses. Here, I discuss why such improvements are needed and can ease a paradigm shift in human health risk assessment. The current approach to human health risk assessment is limited by several elements: (1) the relevance of data is debatable, as they are largely based on in vivo animal models that are poorly predictive for complex endpoints, raise challenges with regard to interspecies extrapolations, and are seldom informative of the mechanism underlying the observed effects; (2) lack of flexibility in data requirements by regulators, which limits the uptake of new scientific developments in a timely manner; and (3) lack of data accessibility, which makes data integration difficult. However, mechanistic-based assessments are currently conducted for the identification of endocrine disruptors and are developed for addressing developmental neurotoxicity. Such assessments can serve as examples for changing the paradigm of risk assessment. There are several opportunities for improvement, such as: make regulatory standard requirements less prescriptive; enhance and use the opportunities for read-across; analyse and quantify uncertainties in order to benchmark new approach methods to the current system; better integrate screening methods early in regulatory assessments and decision-making; and develop more adverse outcome pathways in order to link new approach methods with the current approach and ultimately make it possible to base regulatory decisions on early key events of a toxicity pathway.

Vision of a near future: Bridging the human health–environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment

“…It is recognized that new scientific improvements and their integration in risk assessment have the potential to improve human health risk assessments by enabling a mechanistic understanding of adverse effects and more accurate predictions of biological responses (Bennekou 2019). Current regulatory-accepted approaches to assess chemical safety are often based on a battery of in vivo methods and a limited number of accepted in silico or in vitro approaches.…”

Assessment of the endocrine disrupting properties of bisphenol AF: a case study applying the European regulatory criteria and guidance

“…Information requirements for BPs include repeated dose toxicity tests (28 day and/or 90 day), chronic exposure and reproductive toxicity tests; pre-natal developmental toxicity studies, and/or a two-generation reproductive toxicity test [ 30 ]. Still, it is foreseen that this information may not always be sufficient to complete the assessment of ED potential and the lack of in vitro and in vivo mechanistic data may be specifically critical since apical findings from in vivo data often do not enable a mechanistic understanding of the observed AO [ 31 ]. Mechanistic information is only available from a few required studies for pesticides and may especially be insufficient if the study was conducted according to older test guidelines.…”

The eTRANSAFE Project on Translational Safety Assessment through Integrative Knowledge Management: Achievements and Perspectives

“…The need to move towards a mechanistic-based risk assessment is widely recognized, since it will strengthen the causality connection between compound exposure and the occurrence of adverse outcomes [ 22 ]. Systems Toxicology approaches, based on network science and machine learning and embracing different types of data (omics as well as clinical and biomedical data), are especially suited to the study of the perturbations elicited by drugs within the context of cellular networks and in this way provide insight into the molecular mechanisms leading to drug adverse outcomes.…”