Methyl 2-[(2-methylundecylidene)amino]benzoate

Density

Administrative data

Endpoint:

density, other

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

July 2018

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

Data source

Reference

Reference Type:

study report

Title:

Unnamed

Year:

2018

Report date:

2019

Materials and methods

Test guideline

Test guideline 1

Qualifier:

no guideline required

Test guideline 2

Qualifier:

equivalent or similar to guideline

Guideline:

OECD Guideline 109 (Density of Liquids and Solids)

Deviations:

not applicable

Principles of method if other than guideline:

Following QSAR model was applied to predict the density for
Methyl 2-[(2-methylundecylidene)amino]benzoate:
US EPA T.E.S.T. v4.2.1
The density of the query substance was predicted using the following approaches and a consensus of their results
was derived:
• Hierarchical clustering
• Group contribution method
• Nearest Neighbour approach

GLP compliance:

not specified

Remarks:

Not relevant for QSAR calculations. Full reports ensuring transparency and allowing total reproducibility of the results are provided.

Test material

Test material information

Constituent 1

Reference substance name:

Methyl 2-[(2-methylundecylidene)amino]benzoate

EC Number:

267-104-8

EC Name:

Methyl 2-[(2-methylundecylidene)amino]benzoate

Cas Number:

67800-80-0

Molecular formula:

C20H31NO2

IUPAC Name:

methyl 2-[(2-methylundecylidene)amino]benzoate

Test material form:

liquid

Results and discussion

Density

Key result

Type:

density

Density:

ca. 0.95 g/cm³

Remarks on result:

other: No mention of the temperature in the reports

Any other information on results incl. tables

Results with US EPA T.E.S.T. v4.2.1

 

 

Method	Predicted Density
Hierarchical clustering	N/A
Group Contribution	0.91 g/cm3
Nearest Neighbours	0.98 g/cm3
Consensus/battery result	0.95 g/cm3

 

 

 

Based on the methodology discussed in section 2 of this report and combining the results derived from individual models discussed earlier in this section

Applicant's summary and conclusion

Conclusions:

The final Density predicted for Methyl 2-[(2-methylundecylidene)amino]benzoate assigned by the study investigator: 0.95 g/cm3
(Average of the final results from two different methods in the applied model).
Klimisch score assigned by the study investigator for the final prediction: K2
Remarks / Additional Comments (optional): No remarks or comments.

Executive summary:

Introduction. A Quantitative Structure Activity Relationship (QSAR) model were used to predict the Density of the test item Methyl 2-[(2-methylundecylidene)amino]benzoate. This QSAR model has been designed to be used for regulatory purposes and based on the QSAR results, this report predicts the consensus endpoint value which would be expected when testing the substance under experimental conditions in a laboratory following the OECD Guideline for Testing of Chemicals No.109: “Density of Liquids and Solids”.

Methods. The purpose of the in silico study was to predict the Density of the test item Methyl 2-[(2-methylundecylidene)amino]benzoate. This prediction was performed using the following QSAR model:

• US EPA T.E.S.T v4.2.1 (via Chemistry Dashboard)

Results.

Based on the QSAR used, the final Density for Methyl 2-[(2-methylundecylidene)amino]benzoate was predicted as 0.95 g/cm3.

The final Density was derived by applying a consensus method on the reliable results derived from the two methodologies. The final QSAR result can be associated with a Klimisch score: K2

KREATiS explanation for Klimisch 2 :

Final QSAR result is reliable and can reliably replace an experimental result with the OECD Guideline for Testing of Chemicals No.109: Density of Liquids and Solids. The query substance falls within the applicablity domain of all the models used in predicting the final consensus result. However, this model cannot generate all the documentation such as QMRF and QPRF required under REACH.