Reaction mass of meso-2-{[4-(2-{4-[(oxiran-2-yl)methoxy]phenyl}-1,1-dichloroethylidene-2 yl)phenoxy]methyl}oxirane and 2RS)-2-({4-[2-(4-{[(2RS)-oxiran-2-yl]methoxy}phenyl)-1,1-dichloroethylidene-2-yl]phenoxy}methyl)oxirane

Density

Link to relevant study record(s)

Reference

Endpoint:

relative density

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

QSAR Report 3rd September 2020

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification

Justification for type of information:

1. SOFTWARE
US EPA T.E.S.T

2. MODEL (incl. version number)
Toxicity Estimation Software Tool

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
Cl/C(Cl)=C(/c2ccc(OCC1CO1)cc2)c4ccc(OCC3CO3)cc4

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL and APPLICABILITY TO THE TEST CHEMICAL
- Defined endpoint: Density
- Unambiguous algorithm:
Consensus method was utilised as it provides the most accurate prediction. In the consensus method, the predicted toxicity is simply the average of the predicted toxicities from the other QSAR methodologies (taking into account the applicability domain of each method)23. If only a single QSAR methodology can make a prediction, the predicted value is deemed unreliable and not used. This method typically provides the highest prediction accuracy since errant predictions are dampened by the predictions from the other methods. In addition, this method provides the highest prediction coverage because several methods with slightly different applicability domains are used to make a prediction. The predicted toxicity is estimated by taking an average of the predicted toxicities from the below QSAR methods

Hierarchical method
The toxicity for a given query compound is estimated using the weighted average of the predictions from several different cluster models.
FDA method
The prediction for each test chemical is made using a new model that is fit to the chemicals that are most similar to the test compound. Each model is generated at runtime.
Single model method
Predictions are made using a multilinear regression model that is fit to the training set (using molecular descriptors as independent variables).
Group contribution method
Predictions are made using a multilinear regression model that is fit to the training set (using molecular fragment counts as independent variables).
Nearest neighbor method
The predicted toxicity is estimated by taking an average of the 3 chemicals in the training set that are most similar to the test chemical.


- Defined domain of applicability and similarity with analogues in the data set:
The applicability domain is defined using several different constraints. The first constraint, the model ellipsoid constraint, checks if the test chemical is within the multidimensional ellipsoid defined by the ranges of descriptor values for the chemicals in the cluster (for the descriptors appearing the cluster model). The model ellipsoid constraint is satisfied if the leverage of the test compound (h00) is less than the maximum leverage value for all the compounds used in the model 17. The second constraint, the Rmax constraint, checks if the distance from the test chemical to the centroid of the cluster is less than the maximum distance for any chemical in the cluster to the cluster centroid. The distance is defined in terms of the entire pool of descriptors (instead of just the descriptors appearing in the model), the equation for which is available in the User Guide.

The last constraint, the fragment constraint, is that the compounds in the cluster have to have at least one example of each of the fragments contained in the test chemical. For example if one was trying to make a prediction for ethanol, the cluster must contain at least one compound with a methyl fragment (-CH3 [aliphatic attach]), one compound with a methylene fragment (-CH2 [aliphatic attach]), and one compound with a hydroxyl fragment (-OH [aliphatic attach]). This constraint was added to avoid situations where a chemical might have a similar backbone structure to the chemicals in a given cluster but has a different functional group attached. For example if a given cluster contained only short-chained aliphatic amines one would not want to use it to predict the toxicity of ethanol. If a chemical contains a fragment that is not present in the training set, the toxicity cannot be predicted.
- Appropriate measures of goodness-of-fit and robustness and predictivity:
Predictions for the test chemical were based on the most similar chemicals in the training set. Those used had similarity coefficient values of 0.71-0.60 and a mean absolute effor for these similarity coefficients of 0.02.

-Test Set Data Description and appropriateness
The density is defined as mass per unit volume. The data set for this endpoint was obtained from the density data contained in LookChem 84. The data set was restricted to chemicals with boiling points greater than 25°C (or the boiling point was unavailable). The data set was further restricted to chemical with densities > 0.5 and < 5 g/cm3. The final dataset consisted of 8909 chemicals. Data from LookChem are not peer reviewed but the set is very large and thus provides a large degree of structural diversity. The modeled property was density in g/cm3.

6. ADEQUACY OF THE RESULT
The density is defined as mass per unit volume. It is not used for classification and labelling but is fundamental to understanding the intrinsic properties of the substances.

Qualifier:

no guideline available

Principles of method if other than guideline:

- Software tool(s) used including version: US EPA T.E.S.T
- Model(s) used: V4.2
- Model description: see field 'Justification for non-standard information'

Specific details on test material used for the study:

Model id C20H18O4Cl2_1599141652391
SMILES Code: Cl/C(Cl)=C(/c2ccc(OCC1CO1)cc2)c4ccc(OCC3CO3)cc4

Key result

Type:

relative density

Density:

1.3 other: relative

Remarks on result:

other: in silico QSAR predicted value

Conclusions:

The relative density of the substance is predicted as 1.3.

Description of key information

The relative density of the substance is predicted as 1.3.

Key value for chemical safety assessment

Relative density at 20C:

1.3