Oral Presentation SETAC Asia-Pacific Virtual Conference 2022

Quantitative Adverse Outcome Pathway (qAOP) assisted next generation risk assessment of mitochondrial toxicants (#12)

You Song 1 , Adam Lillicrap 1 , Camila Esguerra 2 , Daniel Villeneuve 3 , Daniel Ng 4 , Jan Thomas Rundberget 1 , S. Jannicke Moe 1 , Jorke Kamstra 5 , Knut Erik Tollefsen 1 , Li Xie 1 , Maria Christou 1 , Maria Hultman 1 , Riccardo de Bin 2 , Taisen Iguchi 6 , Yang Cao 7
  1. Norwegian Institute for Water Research (NIVA), Oslo, OSLO, Norway
  2. University of Oslo, Oslo, Norway
  3. U.S. EPA Great Lakes Toxicology and Ecology Division, Duluth, USA
  4. International Food and Water Research Centre, Singapore
  5. Utrecht University, Utrecht, the Netherlands
  6. Yokohama City University, Yokohama, Japan
  7. Örebro University, Örebro, Sweden

Adverse outcome pathway (AOP) is a conceptual framework to assist next generation risk assessment (NGRA) of chemicals, with better incorporation of animal alternative testing strategies and new approach methodologies (NAMs) into regulatory decision making. While a qualitative AOP may improve mechanistic understanding and aid the prioritization and assessment of chemicals, a quantitative AOP (qAOP) allows in silico prediction of hazard and risk based on information generated by cost-efficient NAMs such as in vitro high-throughput screening. This presentation will refresh these concepts and approaches to facilitate the expansion of the AOP community of practice in Asia-Pacific and introduce our recent AOP project, RiskAOP (https://www.niva.no/en/projectweb/riskaop). The ongoing RiskAOP project is a proof-of-concept research initiative to demonstrate how qAOPs in combination with NAMs can facilitate NGRA, with mitochondrial toxicants as the prototypes. In this project, we are developing a novel high-throughput in vitro (zebrafish 2D and 3D cell systems) and a multi-trophic level in vivo (zebrafish embryo, daphnia and lemna) test battery for cost-efficient assessment of mitochondrial toxicants causing growth inhibition, as well as a strategy to reduce laboratory animal tests. We are also employing state-of-the-art modeling approaches such as structural equation modeling (SEM) and Bayesian network (BN) for construction of qAOP models based on new data generated by laboratory studies. Our conceptual AOP network for mitochondrial toxicity is currently included in OECD’s AOP work program and one of the linear AOPs (https://aopwiki.org/aops/263) is in the final phase of endorsement by OECD. This project is funded by the Research Council of Norway (grant 301397) and supported by the NIVA Computational Toxicology Program (https://www.niva.no/en/projectweb/nctp).