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Diss Factsheets
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EC number: 952-496-1 | 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
Biodegradation in water: screening tests
Administrative data
- Endpoint:
- biodegradation in water: ready biodegradability
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 17th April 2020
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a (Q)SAR model, with limited documentation / justification, but validity of model and reliability of prediction considered adequate based on a generally acknowledged source
- Justification for type of information:
- 1. SOFTWARE
EPI SUITE BioWin v4.10
2. MODEL (incl. version number)
BioWin v4.10
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES : C1(CC2C(CC1C2)CNC(=O)(CC(#N)))CNC(=O)(CC(#N))
CHEM : LME 11526
MOL FOR: C15 H20 N4 O2
MOL WT : 288.35
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: Biodegradation
Biowin1 (Linear Model Prediction)
Biowin2 (Non-Linear Model Prediction)
Biowin3 (Ultimate Biodegradation Timeframe)
Biowin4 (Primary Biodegradation Timeframe)
Biowin5 (MITI Linear Model Prediction)
Biowin6 (MITI Non-Linear Model Prediction)
Biowin7 (Anaerobic Model Prediction)
Ready Biodegradability Prediction
- Unambiguous algorithm/ Methodology and Structural Domains
This model uses a fragment-based approach that is similar to several other biodegradation models, such as those within the Biodegradation Probability Program (BIOWIN) estimation program. In the present study, a half-life in days is estimated using a multiple linear regression against counts of 31 distinct molecular fragments. The model was developed using a data set consisting of 175 compounds with environmentally-relevant experimental data that was divided into training and validation sets. The original fragments from the Ministry of International Trade and Industry BIOWIN model were used initially as structural descriptors and additional fragments were then added to better describe the ring systems found in petroleum hydrocarbons and to adjust for nonlinearity within the experimental data. The training and validation sets had r2 values of 0.91 and 0.81, respectively.
A description of the BIOWIN Biodegradation Probability Program is available in the on-line BIOWIN Help File. More complete information is available in the Howard et al. (2005) journal article.
The Biodegradation Probability Program (BIOWIN) estimation program, a suite of 7 different models (which is part of the EPI Suite), is currently used by the U.S. EPA and the European Union Working Group addressing persistent, bioaccumulative, and toxic compounds as an initial persistence screen when reliable experimental biodegradation data in environmentally relevant media are not available. These models provide an estimate for the probability of biodegradation based on fragment methodology.
- Defined domain of applicability:
Graphical represenation of the estimation accuracy of the tool is available in the Biowin user guide. Information is provided on the compilation of the range and unique number of compounds in each class, the absolute mean error (deviation) and log half life of each compond class in the training set. The minimum and maximum values for molecular weight are listed below. Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that biodegradability estimates are less accurate for compounds outside the MW range of the training set compounds, those that contain differing combinations of functional groups, and/or that have more instances of a given fragment than the maximum for all training set compounds. It is also possible that a compound may have a functional group(s) or other structural features not represented in the training set, and for which no fragment coefficient was developed; and that a compound has none of the fragments in the model’s fragment library. These points should be taken into consideration when interpreting model results.
Molecular Weight Range of Training Set:
Minimum MW: 70.14
Maximum MW: 478.94
The present substance falls within the appropriate molecular weight range. The compound does have the majority of it's functional groups represented in the training set however, there are a limited number of these. The biodegradability prediction should be used with caution and in conjunction with expert judgement. First, biodegradation half-lives are quite variable in the environment and this is not caused solely by experimental error. This variation reflects differences in environmental media, temperature, pH, moisture conditions, differences in microbial populations, any previous acclimation to petroleum or petroleum-like compounds, and so on. Therefore, the biodegradation of any hydrocarbon in the environment is better described by a distribution of half-lives and not as a single value.
Secondly, modeling of biodegradation is an inexact process. In fragment-based methodology, the underlying assumption is that the data are linear. By developing the model to give actual half-life predictions, non-linear regression of the selected fragments was not possible. However, the data collected during this study show that for two of the best studied structural classes found in petroleum hydrocarbons (n-alkanes and PAHs, both parent and alkyl substituted), the available biodegradation data are not linear. The biodegradation data for the n-alkanes were not linear even within their structural group, although the PAHs and alkyl-substituted PAHs generally were. The non-linearity of the collected biodegradation data means that the utility of a fragment-based model is limited. Additional fragments or more traditional mathematical corrections applied to the fragment coefficients are included in the BioHCwin model to correct for this non-linearity when possible, but these must be made based on scientific data.
6. ADEQUACY OF THE RESULT
The biodegradability of a substance is used in conjuction with ecotoxicity data to undertstand risk to the environment and terrestrial/aquatic life. While the prediction does provide useful information, it is not concusive and is of limited reliability. When no useful data on degradability, either experimentally determined or estimated data, the substance should be regarded is not rapidly degradable as stated under UN GHS classification guidance reccommendations.
Data source
Reference
- Reference Type:
- other company data
- Title:
- Unnamed
- Year:
- 2 020
- Report date:
- 2020
Materials and methods
Test guideline
- Qualifier:
- no guideline available
- Principles of method if other than guideline:
- - Software tool(s) used including version:
US EPA EPISUITE v4.3
- Model(s) used: Biowin
- Model description: see field 'Justification for non-standard information'
Test material
- Reference substance name:
- N,N'-[bicyclo[2.2.1]heptane-2,6-diylbis(methylene)]bis(2-cyanoacetamide)
- Molecular formula:
- C15H20N4O2
- IUPAC Name:
- N,N'-[bicyclo[2.2.1]heptane-2,6-diylbis(methylene)]bis(2-cyanoacetamide)
- Reference substance name:
- Ethyl cyanoacetate
- EC Number:
- 203-309-0
- EC Name:
- Ethyl cyanoacetate
- Cas Number:
- 105-56-6
- Molecular formula:
- C5H7NO2
- IUPAC Name:
- ethyl cyanoacetate
- Test material form:
- solid
Constituent 1
impurity 1
Results and discussion
% Degradation
- Key result
- Remarks on result:
- not readily biodegradable based on QSAR/QSPR prediction
Applicant's summary and conclusion
- Validity criteria fulfilled:
- not applicable
- Interpretation of results:
- not inherently biodegradable
- Conclusions:
- US EPA EPUSITE Biowin software was used to predict the biodegradability of the substance.
The biodegradability of a substance is used in conjuction with ecotoxicity data to undertstand risk to the environment and terrestrial/aquatic life. While the prediction does provide useful information, it is not concusive and is of limited reliability. When no useful data on degradability, either experimentally determined or estimated data, the substance should be regarded is not rapidly degradable as stated under UN GHS classification guidance reccommendations.
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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