Title
Supporting read-across using biological data
Author
Zhu, H.
Bouhifd, M.
Donley, E.
Egnash, L.
Kleinstreuer, N.
Kroese, E.D.
Liu, Z.
Luechtefeld, T.
Palmer, J.
Pamies, D.
Shen, J.
Strauss, V.
Wu, S.
Hartung, T.
Publication year
2016
Abstract
Read-across, i.e., filling toxicological data gaps by relating to similar chemicals for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, biological similarity based on biological data adds extra strength to this process. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of, e.g., genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances are becoming available, enabling big data approaches in read-across studies. In the context of developing Good Read-Across Practice guidance, a number of case studies using various big data sources were evaluated to assess the contribution of biological data to enriching read-across. An example is given for the US EPA's ToxCast dataset which allows read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example is given for REACH registration data that enhances read-across for acute toxicity studies. A different approach is taken using omics data to establish biological similarity: Examples are given for in vitro stem cell models and short-term in vivo repeated dose studies in rats used to support read-across and category formation. These preliminary biological data-driven read-across studies show the way towards the generation of new read-across approaches that can inform chemical safety assessment. Funding Details: T32 ES007141, NIEHS, National Institute of Environmental Health Sciences
Subject
ELSS - Earth, Life and Social Sciences
Life
Healthy Living
Biomedical Innovation
Big data
Biological similarity
Read-across
Safety assessment
RAPID - Risk Analysis for Products in Development
To reference this document use:
http://resolver.tudelft.nl/uuid:79cef248-ddaf-4fb0-99f7-4c0357e57eb8
DOI
https://doi.org/10.14573/altex.1601252
TNO identifier
534873
ISSN
1868-596X
Source
Altex, 33 (33), 167-182
Document type
article