Constructing a developmental and reproductive toxicity database of chemicals (DART NIHS DB) for integrated approaches to testing and assessment
| Autor: | Tomoko Kawamura, Akihiko Hirose, Makiko Kuwagata, Kaoru Inoue, Kazuo Ushida, Minoru Miura, Takashi Yamada, Naruo Katsutani |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Alternative methods
Dart Database Databases Factual Drug-Related Side Effects and Adverse Reactions Reproduction Predictive toxicology Biology Toxicology computer.software_genre Risk Assessment Individual study Pregnancy Toxicity Tests Humans Female Reproductive toxicity human activities computer Perinatal period computer.programming_language |
| Zdroj: | The Journal of toxicological sciences. 46(11) |
| ISSN: | 1880-3989 |
| Popis: | Developmental and reproductive toxicity (DART) is an important endpoint, and databases (DBs) are essential for evaluating the risk of untested substances using alternative methods. We have constructed a reliable and transparent DART DB, which we named DART NIHS DB, using the publicly available datasets of DART studies of industrial chemicals conducted by Japanese government ministries in accordance with the corresponding OECD test guidelines (OECD TG421 and TG422). This DB is unique because its dataset chemicals have little overlap with those of ToxRefDB, which compiles large-scale DART data, and it is reliable because the included datasets were created after reviewing the individual study reports. In DART NIHS DB, 171 of 404 substances exhibited signs of DART, which occurred during fertility and early embryonic development (49 substances), organogenesis (59 substances), and the perinatal period (161 substances). When the lowest-observed-adverse-effect level (LOAEL) of DART was compared with that of repeated-dose toxicity (RDT), 15 substances (12%) had a lower LOAEL for DART than for RDT. Of these, five substances displayed significant DART at doses of ≤ 50 mg/kg bw/day. The chemical and toxicity information in this DB will be useful for the development of stage-specific adverse outcome pathways (AOPs) via integration with mechanistic information. The whole datasets of the DB can be implemented in read-across support tools such as the OECD QSAR Toolbox, which will further lead to future integrated approaches to testing and assessment based on AOPs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|