Research Article: t4 report*: Toward Good Read-Across Practice (GRAP) Guidance

Date Published: August 16, 2017


Author(s): Nicholas Ball, Mark T. D. Cronin, Jie Shen, Karen Blackburn, Ewan D. Booth, Mounir Bouhifd, Elizabeth Donley, Laura Egnash, Charles Hastings, Daland R. Juberg, Andre Kleensang, Nicole Kleinstreuer, E. Dinant Kroese, Adam C. Lee, Thomas Luechtefeld, Alexandra Maertens, Sue Marty, Jorge M. Naciff, Jessica Palmer, David Pamies, Mike Penman, Andrea-Nicole Richarz, Daniel P. Russo, Sharon B. Stuard, Grace Patlewicz, Bennard van Ravenzwaay, Shengde Wu, Hao Zhu, Thomas Hartung.


Grouping of substances and utilizing read-across of data within those groups represents an important data gap filling technique for chemical safety assessments. Categories/analogue groups are typically developed based on structural similarity and, increasingly often, also on mechanistic (biological) similarity. While read-across can play a key role in complying with legislation such as the European REACH regulation, the lack of consensus regarding the extent and type of evidence necessary to support it often hampers its successful application and acceptance by regulatory authorities. Despite a potentially broad user community, expertise is still concentrated across a handful of organizations and individuals. In order to facilitate the effective use of read-across, this document presents the state of the art, summarizes insights learned from reviewing ECHA published decisions regarding the relative successes/pitfalls surrounding read-across under REACH, and compiles the relevant activities and guidance documents. Special emphasis is given to the available existing tools and approaches, an analysis of ECHA’s published final decisions associated with all levels of compliance checks and testing proposals, the consideration and expression of uncertainty, the use of biological support data, and the impact of the ECHA Read-Across Assessment Framework (RAAF) published in 2015.

Partial Text

Over the last decade, the world has witnessed the introduction of new regulations on chemicals in several geographic regions and countries (for example EU, China, Taiwan, Korea, Turkey) that require companies to meet safety data requirements for their already marketed chemicals, often resulting in the generation of new toxicological data and the execution of a risk assessment to address any hazards identified. Within these regulations, the data needs are driven by some form of proxy for potential exposure (e.g., manufacturing or import volume) and as a consequence of the hazard and risk assessments undertaken, chemicals may be subject to restrictions on how they are used or, alternatively, phased out.

There is no single answer to the question of what the current state of the art of read-across is. To determine the success, or otherwise, of read-across as an alternative technique to animal testing for toxicological assessment, a non-exhaustive list of criteria was established to identify key points of reference. These are detailed below.

The acceptance of read-across varies between regions. For instance, read-across and analogous techniques are widely used as part of US EPA’s Pre-Manufacture Notification Process (Cronin et al., 2003a,b). Within the EU, the acceptance of read-across for toxicity prediction in the regulatory context requires more understanding, and this topic forms the basis of much of the remainder of this paper. Notably, the EU REACH legislation explicitly calls for the use of non-animal alternative methods and thus opens up the use of read-across and ECHA’s recently published Read-Across Assessment Framework (RAAF) is the first of its kind, strongly impacting on how read-across will be performed and evaluated in the future.

With an understanding of the state of the art of read-across and some important experience gained through the REACH Regulation, we find ourselves in a position where there is some understanding of the available tools and where we appear to be failing/succeeding. The question therefore remains, how can the tools be better applied to increase the quality of read-across justifications (not just for EU REACH but also beyond)?

Having reviewed the current start of the art in terms of read-across, biological profiling and experiences to date with the regulatory acceptance of read-across, it is important to consider where this field should move in order to take advantage of this tool to the fullest extent.

This paper has attempted to lay out the current state of the art of read-across and, based on the analysis of its effectiveness under the EU REACH Regulation, highlights the areas that now should become a priority for further work to ensure that read-across continues to be an effective way to characterize the hazards of substances without triggering the need for extensive testing programs. Several areas now appear to be clear focal points for more work:
– Finding an effective way to make use of the ECHA RAAF to guide the creation of categories/analog groupings and support read-across within these: The RAAF is an extensive modular document detailing the critical scientific aspects associated with different types of read-across hypotheses. Developing a companion tool with a reporting function that could serve as a category/analogue approach justification document would be of significant utility to a broad range of read-across practitioners. This tool may also assist in a better assessment of uncertainty within the use of read-across and allow practitioners to be more proactive in identifying ways to address uncertainty (e.g., through risk assessment or triggering additional data generation).– Continued analysis and reporting of case studies, including those that have been successfully accepted by regulatory authorities: Availability of positive examples of robust read-across case studies can serve as effective models to help drive consistency in read-across assessments developed by industry. We must continue to learn from the experiences of others.– Identify the best practices for using biological profiling/bio-informatics tools to support establishing similarity of source and target chemicals in read-across and, potentially, for predicting endpoints in their own right: There is a lot of movement in the area of biological profiling, and ensuring that these techniques are used in a robust manner that is reliable and transparent is critical. Failure to derive some best practices for their use will likely lead to significant uncertainty on how to use these tools effectively and also create some mistrust in the data where they are not used appropriately.




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