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EC number: 947-818-2 | 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
Bioaccumulation: aquatic / sediment
Administrative data
Link to relevant study record(s)
- Endpoint:
- bioaccumulation in aquatic species: fish
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- 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 adequate and reliable documentation / justification
- Justification for type of information:
- 1. SOFTWARE
: CATALOGIC 5.13.1
2. MODEL (incl. version number) : BCF base-line model v.03.10
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
dodecan-2-yl acrylate: CCCCCCCCCCC(C)OC(=O)C=C
dodecan-3-yl acrylate: CCCCCCCCCC(CC)OC(=O)C=C
dodecan-4-yl acrylate: CCCCCCCCC(CCC)OC(=O)C=C
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: The BCF base-line model consists of two major components: a model for predicting the maximum potential for bioaccumulation based solely on chemicals’ lipophilicity (based on multi-compartment diffusion), and a set of mitigating factors that account for the reduction of the bioaccumulation potential of chemicals based on chemical (e.g., molecular size, ionization, etc.) and organism-dependent factors (e.g., metabolism). In the BCF base-line model the tissue metabolism simulator is used to account for the effect of metabolism.
- Unambiguous algorithm:
- Defined domain of applicability: The applicability domain of the BCF base-line model contains four layers:
General properties requirements
Structural domain
Mechanistic domain (discriminates between modes of bioaccumulation - passive (partitioning in lipid phase) or active (based on protein binding). Only chemicals with expected passive diffusion driven bioaccumulation are considered to be in the mechanistic domain of the model)
Metabolic domain (describes how well the metabolism is simulated based on the available observed metabolism in the database of the model)
- Appropriate measures of goodness-of-fit and robustness and predictivity:
Residual Sum of Squares = 197
Coefficient of Correlation, R = 0.92
Root mean square error, 0.51
Distribution of residual error: ca. 88% of residuals of the fitted data are <0.75 log units
- Mechanistic interpretation: The BCF base-line model reflects the current understanding of the process by which lipophilic organic chemicals are bioaccumulated in fish through the respiratory organs only. Chemicals, bioaccumulating by other mechanisms (e.g., binding to proteins) are considered out of the mechanistic domain of the model. The BCFmax model is a theoretical model based on the assumption that the only driving force of bioconcentration is lipophilicity and the effect of any other factors are insignificant. Its mathematical formalism is derived considering multi-compartment diffusion. The bioconcentration predicted by BCFmax model could be limited by variety of mitigating factors that account for the reduction of the bioaccumulation potential of chemicals based on chemical and organism-dependent factors. The effect of mitigating factors mathematically is quantified by probabilities: to penetrate through the cell membrane, to be ionized, to be metabolised, etc. In the BCF base-line model the tissue metabolism simulator is used to account for the effect of metabolism. It consists of a sequence of spontaneous abiotic and enzyme controlled steps. Probabilities of these molecular transformations are assessed by fitting the training set data.
5. APPLICABILITY DOMAIN
- Descriptor domain: General properties requirements (log Kow, MW, WS) are in domain.
- Structural domain:
Correct fragments = 88%
Incorrect fragments = 0%
Unknown fragments = 12%. "Unknown" structural features are atom centered fragments which do not have a prediction. However, the "unknown" features in MTDID 44430 relate to the acrylate unit, which is represented in the training set and which has a specific transformation in the metabolic model. The assignment as unknown is therefore considered an artifact of atom-centered fragment generation and the structure is considered to be in domain.
- Mechanistic domain: Active bioaccumulation not expected.
- Similarity with analogues in the training set: Three analogs found, see Any other information on results including tables.
6. ADEQUACY OF THE RESULT
The modeled result fulfills the need for a valid assessment of bioconcentration potential of the substance. Due to extensive metabolism, n-octanol:water partition coefficient substantially overpredicts bioconcentration. The results are used in risk assessment and PBT analysis. - Qualifier:
- according to guideline
- Guideline:
- other: REACH Guidance on QSARs R.6
- Principles of method if other than guideline:
- - Software tool(s) used including version:
CATALOGIC 5.13.1
- Model(s) used: BCF base-line model v.03.10
- Model description: see field 'Attached justification'
- Justification of QSAR prediction: 'Attached justification' - GLP compliance:
- no
- Remarks:
- QSAR model
- Specific details on test material used for the study:
- SMILES:
SMILES.1: CCCCCCCCCCC(C)OC(=O)C=C, dodecan-2-yl acrylate
SMILES.2: CCCCCCCCCC(CC)OC(=O)C=C, dodecan-3-yl acrylate
SMILES.3: CCCCCCCCC(CCC)OC(=O)C=C, dodecan-4-yl acrylate - Type:
- BCF
- Value:
- ca. 32 - ca. 33 dimensionless
- Remarks on result:
- other: QSAR model results for the three predominant isomers
- Validity criteria fulfilled:
- not applicable
- Conclusions:
- Estimated BCF values for the main constituents of MTDID 44430 range from 32-33.
- Executive summary:
MTDID 44430 concentrations are not stable in water. QSAR modeling in the BCF base-line model v.03.10 of CATALOGIC 5.13.1 was done to address bioconcentration instead. This model is a validated QSAR with extensive parameterization to take molecular size, metabolism, and other parameters into account. The three main constituents are within the applicability domain of the model with regard to physical/chemical properties, structural features, mechanism of bioaccumulation (passive v. active accumulation) and metabolism. The resulting BCF values span a range of 32-33. This result is in keeping with the extensive in vivo metabolism that has been observed for acrylate esters. The result is therefore considered reliable with restrictions and is suitable for Risk Assessment, Classification & Labelling, and PBT Analysis.
Reference
Table 1, specific results of BCF model
Isomer | log BCF | BCF |
dodecan-2-yl acrylate | 1.52±0.175 | 33 |
dodecan-3-yl acrylate | 1.50±0.237 | 32 |
dodecan-4-yl acrylate | 1.50±0.237 | 32 |
Table 2, predicted v. observed BCF values for validation set substances
Substance | predicted log BCF | predicted BCF | observed log BCF | observed BCF |
2-ethylhexyl methacrylate | 0.94 | 8.7 | 1.57 | 37 |
methyl (E)-3-methoxy-2-{2-[6- (trifluoromethyl) pyridin-2-yloxymethyl] phenyl}acrylate | 2.06 | 115 | 2.46 | 288 |
pentabromobenzyl acrylate | 1.36 | 23 | 0.690 | 4.9 |
Description of key information
MTDID 44430 is not expected to bioaccumulate in aquatic organisms
Key value for chemical safety assessment
- BCF (aquatic species):
- 33 dimensionless
Additional information
Testing on Bioconcentration Factor is not required at this tonnage band under REACH. However, BCF testing was initiated for compliance with other regulatory requirements. The contract research organization engage to provide GLP-compliant studies showed that stable MTDID 44430 concentrations could not be maintained using the static exposure system available to that CRO. Accordingly, a estimation of BCF using a QSAR was done. The model, BCF Baseline model v.03.10 as implemented OASIS LMC Catalogic v.5.13.1.156, is a validated QSAR modeling fulfilling the OECD five criteria.
In detail:
SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: The BCF base-line model consists of two major components: a model for predicting the maximum potential for bioaccumulation based solely on chemicals’ lipophilicity (based on multi-compartment diffusion), and a set of mitigating factors that account for the reduction of the bioaccumulation potential of chemicals based on chemical (e.g., molecular size, ionization, etc.) and organism-dependent factors (e.g., metabolism). In the BCF base-line model the tissue metabolism simulator is used to account for the effect of metabolism.
- Unambiguous algorithm:
- Defined domain of applicability: The applicability domain of the BCF base-line model contains four layers:
General properties requirements
Structural domain
Mechanistic domain (discriminates between modes of bioaccumulation - passive (partitioning in lipid phase) or active (based on protein binding). Only chemicals with expected passive diffusion driven bioaccumulation are considered to be in the mechanistic domain of the model)
Metabolic domain (describes how well the metabolism is simulated based on the available observed metabolism in the database of the model)
- Appropriate measures of goodness-of-fit and robustness and predictivity:
Residual Sum of Squares = 197
Coefficient of Correlation, R = 0.92
Root mean square error, 0.51
Distribution of residual error: ca. 88% of residuals of the fitted data are <0.75 log units
- Mechanistic interpretation: The BCF base-line model reflects the current understanding of the process by which lipophilic organic chemicals are bioaccumulated in fish through the respiratory organs only. Chemicals, bioaccumulating by other mechanisms (e.g., binding to proteins) are considered out of the mechanistic domain of the model. The BCFmax model is a theoretical model based on the assumption that the only driving force of bioconcentration is lipophilicity and the effect of any other factors are insignificant. Its mathematical formalism is derived considering multi-compartment diffusion. The bioconcentration predicted by BCFmax model could be limited by variety of mitigating factors that account for the reduction of the bioaccumulation potential of chemicals based on chemical and organism-dependent factors. The effect of mitigating factors mathematically is quantified by probabilities: to penetrate through the cell membrane, to be ionized, to be metabolised, etc. In the BCF baseline model the tissue metabolism simulator is used to account for the effect of metabolism. It consists of a sequence of spontaneous abiotic and enzyme controlled steps. Probabilities of these molecular transformations are assessed by fitting the training set data.
Further, MTDID 44430 is within the applicability domain of the model. In detail:
- Descriptor domain: General properties requirements (log Kow, MW, WS) are in domain.
- Structural domain:
Correct fragments = 88%
Incorrect fragments = 0%
Unknown fragments = 12%. "Unknown" structural features are atom centered fragments which do not have a prediction. However, the "unknown" features in MTDID 44430 relate to the acrylate unit, which is represented in the training set and which has a specific transformation in the metabolic model. The assignment as unknown is therefore considered an artifact of atom-centered fragment generation and the structure is considered to be in domain.
- Mechanistic domain: Active bioaccumulation not expected.
- Similarity with analogues in the training set: Three analogs found. Predictions were within 0.7 log unit of measured values.
The modeled result fulfills the need for a valid assessment of bioconcentration potential of the substance. Due to extensive metabolism, n-octanol:water partition coefficient substantially overpredicts bioconcentration. The results are used in risk assessment and PBT analysis.
Information on Registered Substances comes from registration dossiers which have been assigned a registration number. The assignment of a registration number does however not guarantee that the information in the dossier is correct or that the dossier is compliant with Regulation (EC) No 1907/2006 (the REACH Regulation). This information has not been reviewed or verified by the Agency or any other authority. The content is subject to change without prior notice.
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