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Integrated in silico strategy for PBT assessment and prioritization under REACH

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dc.contributor.authorPizzo, Fabiola
dc.contributor.authorLombardo, Anna
dc.contributor.authorManganaro, Alberto
dc.contributor.authorBrandt, Marc
dc.contributor.authorCappelli, Claudia I.
dc.contributor.authorPetoumenou, Maria I.
dc.contributor.authorAlbanese, Federica
dc.contributor.authorRoncaglioni, Alessandra
dc.contributor.authorBenfenati, Emilio
dc.date.accessioned2024-06-16T15:55:01Z
dc.date.available2024-06-16T15:55:01Z
dc.date.issued2016
dc.description.abstractChemicals may persist in the environment, bioaccumulate and be toxic for humans and wildlife, posing great concern. These three properties, persistence (P), bioaccumulation (B), and toxicity (T) are the key targets of the PBT-hazard assessment. The European regulation for the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) requires assessment of PBT-properties for all chemicals that are produced or imported in Europe in amounts exceeding 10 tonnes per year, checking whether the criteria set out in REACH Annex XIII are met, so the substance should therefore be considered to have properties of very high concern. Considering how many substances can fall under the REACH regulation, there is a pressing need for new strategies to identify and screen large numbers fast and inexpensively. An efficient non-testing screening approach to identify PBT candidates is necessary, as a valuable alternative to money- and time-consuming laboratory tests and a good start for prioritization since few tools exist (e.g. the PBT profiler developed by USEPA).<BR>The aim of this work was to offer a conceptual scheme for identifying and prioritizing chemicals for further assessment and if appropriate further testing, based on their PBT-potential, using a non-testing screening approach. We integrated in silico models (using existing and developing new ones) in a final algorithm for screening and ranking PBT-potential, which uses experimental and predicted values as well as associated uncertainties. The Multi-Criteria Decision-Making (MCDM) theory was used to integrate the different values. Then we compiled a new set of data containing known PBT and non-PBT substances, in order to check how well our approach clearly differentiated compounds labeled as PBT from those labeled as non-PBT. This indicated that the integrated model distinguished between PBT from non-PBT compounds.<BR>Quelle: http://www.sciencedirect.com<BR>en
dc.format.extent1 Onlineressource (Seiten 478-492)
dc.format.mediumonline resource
dc.identifier.doihttps://doi.org/10.60810/openumwelt-220
dc.identifier.urihttps://openumwelt.de/handle/123456789/7487
dc.language.isoeng
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectPersistenz
dc.subjectBioakkumulation
dc.subjectToxizität
dc.titleIntegrated in silico strategy for PBT assessment and prioritization under REACH
dc.typeWissenschaftlicher Artikel
dc.type.dcmitext
dc.type.mediumcomputer
dspace.entity.typePublication
local.bibliographicCitation.journalTitleEnvironmental Research
local.bibliographicCitation.originalDOI10.1016/j.envres.2016.08.014
local.bibliographicCitation.volume151 (2016)
local.collectionAufsätze
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local.contributor.authorId02174458
local.contributor.authorId02174459
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local.contributor.authorId02174461
local.contributor.authorId00355061
local.identifier.catalogId02437327
local.ingest.leader06532naa a2200000uu 4500
local.jointTitleINTEGRATED IN SILICO STRATEGY FOR PBT ASSESSMENT AND PRIORITIZATION UNDER REACH
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