Research

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.

Info

Journal Article, 2019

UN SDG Classification
DK Main Research Area

    Science/Technology

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