Bridging knowledge gaps in human chemical exposure via drinking water with non-target screening

Davide Ciccarelli, Saer Samanipour, Helena Rapp-Wright, Stefan Bieber, Thomas Letzel, Jake W. O’Brien, Tim Marczylo, Timothy W. Gant, Paolo Vineis, Leon P. Barron*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Fundamental knowledge gaps still exist in the exposome, especially regarding analytical space coverage, mapping and prioritization of a very large number of diverse chemical structures. This review focuses on the contributions of suspect and non-target screening (NTS) to contaminants characterization and toxicity assessment in drinking water. A comprehensive review of publications from 2013-2024 revealed only 172 substances identified with certainty using NTS and in 17 countries. The analytical approaches, their complementarity, effectiveness and use with compound identification frameworks are discussed. The use of ‘intelligent’ tools (including machine learning) to aid with substance identification, prioritization and toxicity assessment is emerging. Strategies for integration of NTS in epidemiology are also considered, including re-use of existing data. NTS holds great potential for chemical exposure assessment from drinking water and its contribution to the exposome.

Original languageEnglish
Pages (from-to)190-214
Number of pages25
JournalCritical Reviews in Environmental Science and Technology
Volume55
Issue number3
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

Keywords

  • Hongbo Li
  • Suspect screening
  • chemical identification
  • exposome
  • machine learning
  • non-target screening
  • prioritization

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