Matches in SemOpenAlex for { <https://semopenalex.org/work/W2967681619> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W2967681619 endingPage "100106" @default.
- W2967681619 startingPage "100106" @default.
- W2967681619 abstract "Abstract Traditionally, chemical risk assessment in humans aims to derive safe levels of exposure to chemicals using toxicological data in test species while applying a default 100-fold uncertainty factor (UF) to allow for both interspecies differences (10) and human variability (10) in toxicokinetic (TK) and toxicodynamic (TD) processes. Over the last two decades, meta-analysis methods have allowed to perform quantitative analysis of population variability in kinetics and dynamics to replace these default UFs with data-based UFs. Pathway-related UFs can now be derived using population variability in kinetics for known metabolic pathways. This study presents a new hierarchical Bayesian model for the meta-analysis of human population variability in TK parameters, along with its application to the derivation of UFs. Data standardisation and data gaps are also discussed, as well as model implementation, selection and validation. Applications of the generic model in human risk assessment are illustrated through a case study quantifying inter-phenotypic differences in TK for substances metabolised via the CYP2D6 polymorphic enzyme. Model implementations in open-source software are provided and future refinements and applications of the model are proposed." @default.
- W2967681619 created "2019-08-22" @default.
- W2967681619 creator A5008339206 @default.
- W2967681619 creator A5026681845 @default.
- W2967681619 creator A5038415036 @default.
- W2967681619 creator A5078234115 @default.
- W2967681619 creator A5087438305 @default.
- W2967681619 date "2019-11-01" @default.
- W2967681619 modified "2023-10-06" @default.
- W2967681619 title "A generic Bayesian hierarchical model for the meta-analysis of human population variability in kinetics and its applications in chemical risk assessment" @default.
- W2967681619 cites W1536497620 @default.
- W2967681619 cites W1537972189 @default.
- W2967681619 cites W1967866094 @default.
- W2967681619 cites W1977948051 @default.
- W2967681619 cites W1978273829 @default.
- W2967681619 cites W1979666222 @default.
- W2967681619 cites W1985186601 @default.
- W2967681619 cites W1999807086 @default.
- W2967681619 cites W2001855995 @default.
- W2967681619 cites W2039853711 @default.
- W2967681619 cites W2050146333 @default.
- W2967681619 cites W2078701250 @default.
- W2967681619 cites W2081243063 @default.
- W2967681619 cites W2088627293 @default.
- W2967681619 cites W2091875030 @default.
- W2967681619 cites W2092397950 @default.
- W2967681619 cites W2097958053 @default.
- W2967681619 cites W2113712526 @default.
- W2967681619 cites W2123828545 @default.
- W2967681619 cites W2129567559 @default.
- W2967681619 cites W2135773360 @default.
- W2967681619 cites W2148534890 @default.
- W2967681619 cites W2155988679 @default.
- W2967681619 cites W2529036059 @default.
- W2967681619 cites W2586102130 @default.
- W2967681619 cites W2783564415 @default.
- W2967681619 cites W2892325866 @default.
- W2967681619 cites W2922497780 @default.
- W2967681619 cites W2949274465 @default.
- W2967681619 doi "https://doi.org/10.1016/j.comtox.2019.100106" @default.
- W2967681619 hasPublicationYear "2019" @default.
- W2967681619 type Work @default.
- W2967681619 sameAs 2967681619 @default.
- W2967681619 citedByCount "8" @default.
- W2967681619 countsByYear W29676816192020 @default.
- W2967681619 countsByYear W29676816192021 @default.
- W2967681619 countsByYear W29676816192022 @default.
- W2967681619 crossrefType "journal-article" @default.
- W2967681619 hasAuthorship W2967681619A5008339206 @default.
- W2967681619 hasAuthorship W2967681619A5026681845 @default.
- W2967681619 hasAuthorship W2967681619A5038415036 @default.
- W2967681619 hasAuthorship W2967681619A5078234115 @default.
- W2967681619 hasAuthorship W2967681619A5087438305 @default.
- W2967681619 hasConcept C107673813 @default.
- W2967681619 hasConcept C119857082 @default.
- W2967681619 hasConcept C124101348 @default.
- W2967681619 hasConcept C154945302 @default.
- W2967681619 hasConcept C2908647359 @default.
- W2967681619 hasConcept C41008148 @default.
- W2967681619 hasConcept C70721500 @default.
- W2967681619 hasConcept C71924100 @default.
- W2967681619 hasConcept C86803240 @default.
- W2967681619 hasConcept C99454951 @default.
- W2967681619 hasConceptScore W2967681619C107673813 @default.
- W2967681619 hasConceptScore W2967681619C119857082 @default.
- W2967681619 hasConceptScore W2967681619C124101348 @default.
- W2967681619 hasConceptScore W2967681619C154945302 @default.
- W2967681619 hasConceptScore W2967681619C2908647359 @default.
- W2967681619 hasConceptScore W2967681619C41008148 @default.
- W2967681619 hasConceptScore W2967681619C70721500 @default.
- W2967681619 hasConceptScore W2967681619C71924100 @default.
- W2967681619 hasConceptScore W2967681619C86803240 @default.
- W2967681619 hasConceptScore W2967681619C99454951 @default.
- W2967681619 hasFunder F4320315318 @default.
- W2967681619 hasLocation W29676816191 @default.
- W2967681619 hasOpenAccess W2967681619 @default.
- W2967681619 hasPrimaryLocation W29676816191 @default.
- W2967681619 hasRelatedWork W2961085424 @default.
- W2967681619 hasRelatedWork W3046775127 @default.
- W2967681619 hasRelatedWork W3107474891 @default.
- W2967681619 hasRelatedWork W3170094116 @default.
- W2967681619 hasRelatedWork W3209574120 @default.
- W2967681619 hasRelatedWork W4205958290 @default.
- W2967681619 hasRelatedWork W4286629047 @default.
- W2967681619 hasRelatedWork W4306321456 @default.
- W2967681619 hasRelatedWork W4306674287 @default.
- W2967681619 hasRelatedWork W4224009465 @default.
- W2967681619 hasVolume "12" @default.
- W2967681619 isParatext "false" @default.
- W2967681619 isRetracted "false" @default.
- W2967681619 magId "2967681619" @default.
- W2967681619 workType "article" @default.