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Diss Factsheets
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EC number: 701-259-9 | CAS number: -
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
Skin sensitisation
Administrative data
- Endpoint:
- skin sensitisation, other
- Remarks:
- QSAR
- Type of information:
- (Q)SAR
- Adequacy of study:
- supporting study
- Study period:
- Not stated
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
Data source
Reference
- Reference Type:
- publication
- Title:
- A quantitative structure-toxicity relationships model for the dermal sensitization guinea pig maximisation assay
- Author:
- Enslien, K., Gombar,V.K., Blake, B.W., Maibach, H.I., Hostynek,J.J., Sigman, C.G. and Bagheri, D.
- Year:
- 1 997
- Bibliographic source:
- Food and Chemcal Toxicology 35 (1997) 1091-1098
Materials and methods
Test guideline
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- The authors developed quantitative structure-toxicity relationship (QSTR) models for assessing dermal sensitization using guinea pig maximization test (GPMT) results. The models are derived from 315 carefully evaluated chemicals. There are two models, one for aromatics (excluding one-benzene-ring compounds), and the other for aliphatics and one-benzene-ring compounds. For sensitizers, the models can resolve whether they are weak/moderate or severe sensitizers. The statistical methodology, based on linear discriminant analysis, incorporates an optimum prediction space (OPS) algorithm. This algorithm ensures that the QSTR model will be used only to make predictions on query structures which fall within its domain. Calculation of the similarities between a query structure and the database compounds from which the applicable model was developed are used to validate each skin sensitization assessment, the cross-validated specificity of the equations ranges between 81 and 91%, and the sensitivity between 85 and 95%. For an independent test set, specificity is 79%, and sensitivity 82%.
- GLP compliance:
- not specified
Test material
- Reference substance name:
- 2-ethylhexyl palmitate
- EC Number:
- 249-862-1
- EC Name:
- 2-ethylhexyl palmitate
- Cas Number:
- 29806-73-3
- Molecular formula:
- C24H48O2
- IUPAC Name:
- 2-ethylhexyl palmitate
- Details on test material:
- 315 chemicals were assessed for sensitising potential - divided into two groups - aliphatics and single benzene ring compounds and aromatics excluding single benzene ring structures. One of te test materials used to assess the predictivity ofthe QSAR model compared with maximisation results from a guinea pig Magnuson & Kligman design study was, 2-ethylhexyl palmitate. No further test material details are available
Constituent 1
In vivo test system
Test animals
- Species:
- other: QSAR modelling
- Strain:
- not specified
- Sex:
- not specified
- Details on test animals and environmental conditions:
- The QSAR results are compared with data from guinea pig studies entered into TOPKAT - no further details available
Results and discussion
- Positive control results:
- Not applicable
In vivo (non-LLNA)
Results
- Reading:
- other: QSAR evaluation
- Group:
- other: QSAR
- Remarks on result:
- other: Reading: other: QSAR evaluation. Group: other: QSAR.
Any other information on results incl. tables
Ethylhexyl palmitate was identified as a non-sensitiser.
Applicant's summary and conclusion
- Interpretation of results:
- not sensitising
- Remarks:
- Migrated information
- Conclusions:
- Ethylhexyl palmitate was identified as a non-sensitiser in literature and this evaluation was confirmed by the QSAR model described in this paper
- Executive summary:
The salient differences of this QSTR model for skin sensitization based on the GPMT assay compared with prior publications include: (1) a considerably larger training set, and thus broader application domain encompassing wider chemical diversity.
(2) that the model resolves the strength of sensitization into weak/moderate and strong categories
(3) that the use of OPS ensures that only query compounds that fit within the model's domain will be assessed, thus avoiding the production and distribution of invalid results--this capability does not, and cannot, exist in expert systems such as DEREK.
The limitations of this QSTR model are basically:
(I) that the GPMT, due to its very nature, tends to overpredict sensitization compared with assays in humans,
(2) that the training set, extensive though it may be, does not encompass as many compounds and as much chemical diversity as one might wish --the release of proprietary data by manufacturers would greatly remediate this problem; and
(3) no account has been taken of previously identified modes of a c t i o n - - b e t t e r models would probably result if submodels were limited to compounds with a single mode of action
Despite these relative pros and cons, the QSAR model did predict the nonsensitising nature of Ethylhexyl palmitate, as indicated in prior literature.
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