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Application of conformal prediction for in silico definition of molecular initiating events linked to endocrine disruption
Umeå University, Chemistry Department, Umeå, Sweden.
Örebro University, School of Science and Technology. Stockholm University, Computer and Systems Sciences Department, Kista, Sweden. (MTM Research Centre)ORCID iD: 0000-0003-3107-331X
Umeå University, Chemistry Department, Umeå, Sweden.
2021 (English)In: Toxicology Letters, ISSN 0378-4274, E-ISSN 1879-3169, Vol. 350, no Suppl., p. S86-S86Article in journal, Meeting abstract (Other academic) Published
Abstract [en]

The adverse outcome pathway (AOP) paradigm has brought mechanism of action in the spotlight of regulatory toxicology, linking biochemical interactions on cellular level (i.e. molecular initiating event, MIE) via key events to adverse outcomes (AOs) on population level. Developments on mechanistic understanding of endocrine disruption (ED) has brought forward MIEs associated with early neurode-velopmental interference  [1] and metabolic disruption [2], describing agonistic and antagonistic interactions with receptors such as constitutive androstane receptor (CAR), estrogen receptor alpha (ERα), farsenoid X receptor (FXR), and glucocorticoid receptor (GR). High confidence on in silico predictions is dictated by high quality training data  on  mechanistically  relevant  endpoints,  where  well-defined  chemistry is covered. Based on Tox21 in vitro assays describing events of agonism and antagonism for 13 receptors linked to ED, 23 in silico models were developed using Random Forest Classification. To quantify measures of uncertainty per prediction a Conformal Prediction framework was employed. In order to assess whether currently available models can confidently predict endocrine disrupting chemicals (EDCs), screening of EURION reference chemicals was conducted. The EURION cluster is a constellation of 8 research consortia aiming to improve endocrine disruption identification. Preliminary results revealed strengths in the use of in silico models for screening of current ED chemical landscape, and data gaps that need to be considered for next steps.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 350, no Suppl., p. S86-S86
National Category
Pharmacology and Toxicology
Identifiers
URN: urn:nbn:se:oru:diva-95627ISI: 000714098000219OAI: oai:DiVA.org:oru-95627DiVA, id: diva2:1614999
Conference
56th Congress of the European Societies of Toxicology (EUROTOX 2021), Virtual Congress, September 27 – October 1, 2021
Funder
EU, Horizon 2020, 825759Available from: 2021-11-29 Created: 2021-11-29 Last updated: 2024-01-16Bibliographically approved

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Norinder, Ulf

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