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This research was funded by PARC, 101057014, HORIZON-HLTH-2021-ENVHLTH-03HE.

Analysis of institutional authors

Kumar, VikasAuthor

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Computational Tools to Facilitate Early Warning of New Emerging Risk Chemicals

Publicated to:Toxics. 12 (10): 736- - 2024-10-01 12(10), DOI: 10.3390/toxics12100736

Authors: Tariq, Farina; Ahrens, Lutz; Alygizakis, Nikiforos A; Audouze, Karine; Benfenati, Emilio; Carvalho, Pedro N; Chelcea, Ioana; Karakitsios, Spyros; Karakoltzidis, Achilleas; Kumar, Vikas; Mora Lagares, Liadys; Sarigiannis, Dimosthenis; Selvestrel, Gianluca; Taboureau, Olivier; Vorkamp, Katrin; Andersson, Patrik L

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Abstract

Innovative tools suitable for chemical risk assessment are being developed in numerous domains, such as non-target chemical analysis, omics, and computational approaches. These methods will also be critical components in an efficient early warning system (EWS) for the identification of potentially hazardous chemicals. Much knowledge is missing for current use chemicals and thus computational methodologies complemented with fast screening techniques will be critical. This paper reviews current computational tools, emphasizing those that are accessible and suitable for the screening of new and emerging risk chemicals (NERCs). The initial step in a computational EWS is an automatic and systematic search for NERCs in literature and database sources including grey literature, patents, experimental data, and various inventories. This step aims at reaching curated molecular structure data along with existing exposure and hazard data. Next, a parallel assessment of exposure and effects will be performed, which will input information into the weighting of an overall hazard score and, finally, the identification of a potential NERC. Several challenges are identified and discussed, such as the integration and scoring of several types of hazard data, ranging from chemical fate and distribution to subtle impacts in specific species and tissues. To conclude, there are many computational systems, and these can be used as a basis for an integrated computational EWS workflow that identifies NERCs automatically.

Keywords

Artificial intelligence (ai)Computational toxicologyEarly warning system (ews)EcotoxicityEffect assessmenEffect assessmentExposureExposure assessmentFrameworkModelMultimediaNew and emerging risk chemicals (nercs)PollutioPredictionQsarRisk assessmentSubstancesToxicityWater

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Toxics due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 120/358, thus managing to position itself as a Q1 (Primer Cuartil), in the category Environmental Sciences.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-06-01:

  • Scopus: 1

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-06-01:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 15 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

    • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
    • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: http://hdl.handle.net/20.500.11797/imarina9390026

    Leadership analysis of institutional authors

    This work has been carried out with international collaboration, specifically with researchers from: Denmark; France; Germany; Greece; Italy; Slovenia; Sweden.