You are here:
A Framework to Build Scientific Confidence in Read-across
Citation:
Patlewicz, G. A Framework to Build Scientific Confidence in Read-across. Presented at Chinese Society of Toxicology Webinar, RTP, NC, March 29, 2019. https://doi.org/10.23645/epacomptox.8291774
Impact/Purpose:
Presentation on Generalized Read-Across to be given to the Chinese Society of Toxicology Continuing Education course in March 2019
Description:
Read-across describes one of the techniques for filling data gaps in either the analogue or category approaches. The analogue approach refers to grouping based on a very limited number of chemicals (e.g. target substance + source substance). The category approach is used when grouping is based on a more extensive range of analogues (e.g. 3 or more members). A key issue thwarting acceptance relates to the “uncertainty of the read-across”. As such there have been many efforts to identify the sources of uncertainty in read-across, characterise them in a consistent manner and identify practical strategies to address and reduce those uncertainties. Notable in these efforts have been the development of frameworks for the assessment of read-across. These allow for a structured assessment of the read-across justification. Although there is much guidance for developing read-across assessment, acceptance still remains an issue, especially for regulatory purposes. The next steps in ongoing research are 1) summarizing and aggregating the toxicity effect predictions to guide end users – what are the effects to be concerned about and which effect predictions are we most confident about, and 2) consideration of other information to define and refine the analogue selection – e.g. physicochemical similarity, metabolic similarity, reactivity similarity. The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the US EPA.
URLs/Downloads:
DOI: A Framework to Build Scientific Confidence in Read-across
PATLEWICZ_CSOT_220319.PDF (PDF, NA pp, 3876.533 KB, about PDF)