N,N'-[bicyclo[2.2.1]heptane-2,6-diylbis(methylene)]bis(2-cyanoacetamide)

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:

2020

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

Test material information

Constituent 1

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)

impurity 1

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

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.