Quantitative Structure Use Relationships: Highlights from a technical summit meeting.

Alternatives assessment Chemical safety Consumer products Exposure assessment Exposure models Formulated products High-throughput exposure assessment Non-targeted analysis Quantitative Structure Use Relationships (QSURs) Risk assessment

Journal

Regulatory toxicology and pharmacology : RTP
ISSN: 1096-0295
Titre abrégé: Regul Toxicol Pharmacol
Pays: Netherlands
ID NLM: 8214983

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 18 09 2023
accepted: 11 10 2023
medline: 4 12 2023
pubmed: 15 10 2023
entrez: 14 10 2023
Statut: ppublish

Résumé

The Quantitative Structure Use Relationship (QSUR) Summit, held on November 2-4, 2022, focused on advancing the development, refinement, and use of QSURs to support chemical substance prioritization and risk assessment and mitigation. QSURs utilize chemical structures to predict the function of a chemical within a formulated product or an industrial process. This presumed function can then be used to develop chemical use categories or other information necessary to refine exposure assessments. The invited expert meeting was attended by 38 scientists from Canada, Finland, France, the UK, and the USA, representing government, business, and academia, with expertise in exposure science, chemical engineering, risk assessment, formulation chemistry, and machine learning. Workshop discussions emphasized the importance of collection and sharing of data and quantification of relative chemical quantities to progress QSUR development. Participants proposed collaborative approaches to address key challenges, including mechanisms for aggregating information while still protecting proprietary product composition and other confidential business information. Discussions also led to proposals for applications beyond exposure and risk modeling, including sustainable formulation discovery. In addition, discussions continue to construct, conduct, and circulate case studies tied to various specific problem formulations in which QSURs supply or derive information on chemical functions, concentrations, and exposures.

Identifiants

pubmed: 37838348
pii: S0273-2300(23)00184-8
doi: 10.1016/j.yrtph.2023.105516
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105516

Informations de copyright

Copyright © 2023. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of competing interest Some authors received ACC-LRI funding as described above. A number of authors participated in the workshop and in the preparation of the manuscript as a part of their regular research activities supported by their employers. US government representatives received no ACC funding for this initiative. The contents of this manuscript are solely the responsibility of the authors and do not necessarily reflect the views or policies of their employers.

Auteurs

Rosemary T Zaleski (RT)

Lumina Consulting, L.L.C, USA. Electronic address: rzaleski10@gmail.com.

Andreas Ahrens (A)

European Chemicals Agency (ECHA), Finland.

Jon A Arnot (JA)

ARC Arnot Research and Consulting Inc, Canada.

Richard A Becker (RA)

American Chemistry Council (ACC), USA.

Mark Bonnell (M)

Environment and Climate Change Canada (ECCC), Canada.

Sean Collins (S)

Health Canada (HC), Canada.

Paul DeLeo (P)

American Chemistry Council (ACC), USA.

Peter Egeghy (P)

EPA, Office of Research and Development (ORD), Center for Computational Toxicology and Exposure (CCTE), USA.

Michelle Embry (M)

Health and Environmental Sciences Institute (HESI), USA.

Todd Gouin (T)

TG Environmental Research, UK.

Kristin Isaacs (K)

EPA, Office of Research and Development (ORD), Center for Computational Toxicology and Exposure (CCTE), USA.

Elke Jensen (E)

Dow Chemical Company, USA.

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Classifications MeSH