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Administrative data

Link to relevant study record(s)

Reference
Endpoint:
viscosity
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
19 January 2019
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
Toxicity Estimation Software Tool

2. MODEL (incl. version number)
T.E.S.T. Version 4.2.1

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
CCOCCOCCOC

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
T.E.S.T allows you to estimate toxicity values using several different advanced QSAR methodologies 2:
 Hierarchical method: The toxicity for a given query compound is estimated using the weighted average of the predictions from several different models. The different models are obtained by using Ward’s method to divide the training set into a series of structurally similar clusters. A genetic algorithm based technique is used to generate models for each cluster. The models are generated prior to runtime.
 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) using a genetic algorithm based approach. The regression model is generated prior to runtime.
 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). The regression model is generated prior to runtime.
 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.
 Consensus method: The predicted toxicity is estimated by taking an average of the predicted toxicities from the above QSAR methods (provided the predictions are within the respective applicability domains).
 Random forest method: The predicted toxicity is estimated using a decision tree which bins a chemical into a certain toxicity score (i.e. positive or negative developmental toxicity) using a set of molecular descriptors as decision variables. The random forest method is currently only available for the developmental toxicity endpoint. The random forest models for the developmental toxicity endpoint were developed by researchers at Mario Negri Institute for Pharmacological Research as part of the CAESAR project 3.
 Mode of action method: The predicted toxicity is estimated using a two-step process. In the first step the mode of action is determined from the linear discriminant analysis model with the highest score. In the second step the toxicity is estimated using the multilinear regression model corresponding to the predicted mode of action. The mode of action method is currently only available for the 96 hour fathead minnow LC50 endpoint.
T.E.S.T provides multiple prediction methodologies so one can have greater confidence in the predicted toxicities (assuming the predicted toxicities are similar from different methods).

5. APPLICABILITY DOMAIN
Viscosity is a measure of the resistance of a fluid to flow in cP defined as the proportionality constant between shear rate and shear stress). The viscosity at 25°C for 557 chemicals was obtained from Viswanath and Riddick. The viscosity values were obtained from Viswanath and Riddick were obtained as follows:
1. If a value is available at 25°C this value is used
2. If an experimental value is not available, a value is extrapolated to 25°C (as long as the closest data point is within 10°C of 25°C) using the following empirical correlation:
log10 viscosity A+B/T
Extrapolation was used in order to expand size of the overall dataset. The modeled property was log10(viscosity cP).

6. ADEQUACY OF THE RESULT
For this property, the consensus method gives the best results if you consider both prediction accuracy and coverage. The low k values for this endpoint can be attributed to the two possible outliers in the test set that fall below the Y=X line.. Further details are attached.
Principles of method if other than guideline:
QSAR estmiation by imput of SMILES Code Toxicity Estimation Software Tool developed by US EPA
GLP compliance:
no
Type of method:
other: QSAR assessment
Key result
Temp.:
20°C
Parameter:
dynamic viscosity (in mPa s)
Value:
1.15
Conclusions:
The viscosity is predicted to be 1.15
Executive summary:

The Viscosity has been estimated using the Toxicity Estimation Software Tool developed by US EPA. The viscosity if predicted to be 1.15

Description of key information

The Viscosity has been estimated using the Toxicity Estimation Software Tool developed by US EPA. The viscosity if predicted to be 1.15

Key value for chemical safety assessment

Viscosity:
1.15 mPa · s (dynamic)
at the temperature of:
20 °C

Additional information