Bis[2-[2-(2-butoxyethoxy)ethoxy]ethyl] adipate

Endpoint summary

Key value for chemical safety assessment

Genetic toxicity in vitro

Description of key information

The whole dataset of mutagenicity data (comprising read-across and QSAR studies), lead to the conclusion that bis[2-[2-(2-butoxyethoxy)ethoxy]ethyl]adipate is not of concern for mutagenicity.

Link to relevant study records

Reference

Reference 1

Endpoint:

genetic toxicity in vitro

Remarks:

Type of genotoxicity: other: in silico prediction

Type of information:

(Q)SAR

Adequacy of study:

supporting study

Study period:

2013

Reliability:

2 (reliable with restrictions)

Justification for type of information:

QSAR prediction: migrated from IUCLID 5.6

Principles of method if other than guideline:

QSAR approach: Different tools were used, when possible, in order to apply a consensus approach and thus enhance the reliability of the predictions. In fact, a single in silico prediction model may provide acceptable results. However, by definition all models are simulation of reality, and therefore they will never be completely accurate; sometimes a single model will not work. When multiple models and multiple approaches are combined in a single consensus score, more accurate predictions can be achieved.
If two prediction methods that use data and different approaches are consistent, the reliability of prediction is better. The errors of a model/approach should be different from another, and therefore compensate.

Several computational tools are nowadays available for applying in silico approaches. Among them, for QSAR predictions the following was selected and used for the endpoint:
ACD/Percepta (Advanced Chemistry Development, Inc., Pharma Algorithms, Inc.) (release 2012) is a suite of comprehensive tools for the prediction of basic toxicity endpoints, including hERG Inhibition, CYP3A4 Inhibition, Genotoxicity, Acute Toxicity, Aquatic Toxicity, Eye/Skin Irritation, Endocrine System Disruption, and Health Effects. Predictions are made from chemical structure and based upon large validated databases and QSAR models, in combination with expert knowledge of organic chemistry and toxicology. It also allows to evaluate the robustness of the prediction by examining compounds similar to the target from the training set, together with literature data and reference. The models also provide an estimation of the reliability of the prediction, by a reliability index (RI). This index provides values in a range from 0 to 1 and gives an evaluation of whether a submitted compound falls within the Model Applicability Domain. Estimation of the RI takes into account the following two aspects: similarity of the tested compound to the training set and the consistency of experimental values for similar compounds. If the RI is less than 0.3 the prediction has to be considered not reliable while if RI is more than 0.5 the prediction results are considered reliable.
Toxtree (Ideaconsultant, version 2.5.1) is a flexible and user-friendly open-source application that places chemicals into categories and predicts various kinds of toxic effect by applying decision tree approaches. The following decision trees are currently implemented: the Cramer classification scheme, Verhaar scheme for aquatic modes of action, rulebases for skin and eye irritation and corrosion, Benigni-Bossa rulebase for mutagenicity and carcinogenicity, structural alerts for identification of Michael Acceptors, START rulebase for persistance / biodegradation potential.
Vega Application (Virtual Models for evaluating the properties of chemicals within a global architecture) (VegaNIC application, Laboratory of Environmental Chemistry and Toxicology of Mario Negri Institute of Pharmacological Research, version 1.0.8) is a platform developed on the basis of contributions from the EU projects CAESAR, ORCHESTRA and ANTARES. It includes CAESAR QSAR model for mutagenicity based on a data set that includes 4225 compounds. It is an integrated model made of two complementary techniques: a machine learning algorithm (SVM), to build an early model with the best statistical accuracy, equipped with an expert facility for false negatives removal based on known structural alerts, to refine its predictions. Thus, the mutagenicity model could classify a compound as mutagen even if it is formally out of the applicability domain. This behaviour is normal for this model and it is related to the use of structural alerts. It also include the CAESAR skin sensitization model, which provides a qualitative prediction of skin sensitisation on mouse (local lymph node assay). The model consists in an Adaptive Fuzzy Partition (AFP) based on 8 descriptors. The AFP produces as output two values positive and negative that represent the belonging degree respectively to the sensitiser and non-sensitise classes. The applicability domain of predictions is assessed using an Applicability Domain Index (ADI) that has values from 0 (worst case) to 1 (best case). The ADI is calculated by grouping several other indices, each one taking into account a particular issue of the applicability domain.
Leadscope Model Applier (Leadscope, Inc.) (version 1.4.6-2) is a chemoinformatic platform that provides QSAR for the prediction of potential toxicity and adverse human clinical effects of pharmaceuticals, cosmetics, food ingredients and other chemicals. The Models are constructed by FDA scientists based on both proprietary and non-proprietary data. Predictions are provided together with several parameters which can be used to assess the prediction in terms of applicability domain. The robustness of the prediction can be further evaluated by examining compounds similar to the target from the training set.

GLP compliance:

no

Type of assay:

other: Ames test in silico

Remarks on result:

no mutagenic potential (based on QSAR/QSPR prediction)

ACD/Percepta mutagenicity predictions.

Chemical	ACD/Percepta Positive probability	ACD/Percepta Prediction call	Reliability index	Reliability assessment
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	0.04	NEGATIVE	0.80	HIGH

Leadscope mutagenicity predictions.

Chemical	Leadscope Prediction call	Leadscope Positive Prediction probability	Prediction reliability parameters
			Model Fragment Count	30% Sim. Training Neighbors Count	Reliability assessment
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	0.04	12	67	RELIABLE

Vega mutagenicity predictions

Chemical	Vega prediction call	Vega AD index
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	0.91

Conclusions:

Interpretation of results: negative

The test item is not mutagenic.

Executive summary:

A consensus approach, illustrated in Table 16, was applied which led to the conclusion that bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate is NOT MUTAGEN.

 

Chemical	ACD/Percepta	Leadscope	Vega	Toxtree	CONSENSUS
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	NEGATIVE	NEGATIVE	NEGATIVE	NEGATIVE

Reference 2

Endpoint:

genetic toxicity in vitro

Remarks:

Type of genotoxicity: other: in silico prediction

Type of information:

(Q)SAR

Adequacy of study:

supporting study

Study period:

2013

Reliability:

2 (reliable with restrictions)

Justification for type of information:

QSAR prediction: migrated from IUCLID 5.6

Principles of method if other than guideline:

QSAR approach: Different tools were used, when possible, in order to apply a consensus approach and thus enhance the reliability of the predictions. In fact, a single in silico prediction model may provide acceptable results. However, by definition all models are simulation of reality, and therefore they will never be completely accurate; sometimes a single model will not work. When multiple models and multiple approaches are combined in a single consensus score, more accurate predictions can be achieved.
If two prediction methods that use data and different approaches are consistent, the reliability of prediction is better. The errors of a model/approach should be different from another, and therefore compensate.

Several computational tools are nowadays available for applying in silico approaches. Among them, for QSAR predictions the following was selected and used for the endpoint:
ACD/Percepta (Advanced Chemistry Development, Inc., Pharma Algorithms, Inc.) (release 2012) is a suite of comprehensive tools for the prediction of basic toxicity endpoints, including hERG Inhibition, CYP3A4 Inhibition, Genotoxicity, Acute Toxicity, Aquatic Toxicity, Eye/Skin Irritation, Endocrine System Disruption, and Health Effects. Predictions are made from chemical structure and based upon large validated databases and QSAR models, in combination with expert knowledge of organic chemistry and toxicology. It also allows to evaluate the robustness of the prediction by examining compounds similar to the target from the training set, together with literature data and reference. The models also provide an estimation of the reliability of the prediction, by a reliability index (RI). This index provides values in a range from 0 to 1 and gives an evaluation of whether a submitted compound falls within the Model Applicability Domain. Estimation of the RI takes into account the following two aspects: similarity of the tested compound to the training set and the consistency of experimental values for similar compounds. If the RI is less than 0.3 the prediction has to be considered not reliable while if RI is more than 0.5 the prediction results are considered reliable.
Leadscope Model Applier (Leadscope, Inc.) (version 1.4.6-2) is a chemoinformatic platform that provides QSAR for the prediction of potential toxicity and adverse human clinical effects of pharmaceuticals, cosmetics, food ingredients and other chemicals. The Models are constructed by FDA scientists based on both proprietary and non-proprietary data. Predictions are provided together with several parameters which can be used to assess the prediction in terms of applicability domain. The robustness of the prediction can be further evaluated by examining compounds similar to the target from the training set.

GLP compliance:

no

Type of assay:

other: mouse lymphoma in silico

Remarks on result:

no mutagenic potential (based on QSAR/QSPR prediction)

ACD/Percepta genotoxicity on Mouse Lymphoma predictions.

Chemical	ACD/Percepta Prediction call	Reliability index	Reliability assessment
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	OUT OF DOMAIN	-	NOT RELIABLE

Leadscope genotoxicity on Mouse Lymphoma predictions.

Chemical	Leadscope Prediction call	Leadscope Positive Prediction probability	Prediction reliability parameters
			Model Fragment Count	30% Sim. Training Neighbors Count	Reliability assessment
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	0.06	17	10	RELIABLE

Conclusions:

Interpretation of results (migrated information):
negative

The test item is not genotoxic.

Executive summary:

A consensus approach was applied, which led to the conclusion that bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate is NOT GENOTOXIC on Mouse Lymphoma. Since in the consensus assessment only reliable predictions were taken into account, in this case the consensus predictions rely only on Leadscope predictions.

Chemical	ACD/Percepta	Leadscope	CONSENSUS
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	OUT OF DOMAIN	NEGATIVE	NEGATIVE

Reference 3

Endpoint:

genetic toxicity in vitro

Remarks:

Type of genotoxicity: other: in silico prediction

Type of information:

(Q)SAR

Adequacy of study:

supporting study

Study period:

2013

Reliability:

2 (reliable with restrictions)

Justification for type of information:

QSAR prediction: migrated from IUCLID 5.6

Principles of method if other than guideline:

QSAR approach: Different tools were used, when possible, in order to apply a consensus approach and thus enhance the reliability of the predictions. In fact, a single in silico prediction model may provide acceptable results. However, by definition all models are simulation of reality, and therefore they will never be completely accurate; sometimes a single model will not work. When multiple models and multiple approaches are combined in a single consensus score, more accurate predictions can be achieved.
If two prediction methods that use data and different approaches are consistent, the reliability of prediction is better. The errors of a model/approach should be different from another, and therefore compensate.

Several computational tools are nowadays available for applying in silico approaches. Among them, for QSAR predictions the following was selected and used for the endpoint:
ACD/Percepta (Advanced Chemistry Development, Inc., Pharma Algorithms, Inc.) (release 2012) is a suite of comprehensive tools for the prediction of basic toxicity endpoints, including hERG Inhibition, CYP3A4 Inhibition, Genotoxicity, Acute Toxicity, Aquatic Toxicity, Eye/Skin Irritation, Endocrine System Disruption, and Health Effects. Predictions are made from chemical structure and based upon large validated databases and QSAR models, in combination with expert knowledge of organic chemistry and toxicology. It also allows to evaluate the robustness of the prediction by examining compounds similar to the target from the training set, together with literature data and reference. The models also provide an estimation of the reliability of the prediction, by a reliability index (RI). This index provides values in a range from 0 to 1 and gives an evaluation of whether a submitted compound falls within the Model Applicability Domain. Estimation of the RI takes into account the following two aspects: similarity of the tested compound to the training set and the consistency of experimental values for similar compounds. If the RI is less than 0.3 the prediction has to be considered not reliable while if RI is more than 0.5 the prediction results are considered reliable.
Leadscope Model Applier (Leadscope, Inc.) (version 1.4.6-2) is a chemoinformatic platform that provides QSAR for the prediction of potential toxicity and adverse human clinical effects of pharmaceuticals, cosmetics, food ingredients and other chemicals. The Models are constructed by FDA scientists based on both proprietary and non-proprietary data. Predictions are provided together with several parameters which can be used to assess the prediction in terms of applicability domain. The robustness of the prediction can be further evaluated by examining compounds similar to the target from the training set.

GLP compliance:

no

Type of assay:

other: chromosome aberration in silico

Remarks on result:

no mutagenic potential (based on QSAR/QSPR prediction)

ACD/Percepta chromosome aberration in vivo composite predictions

Chemical	ACD/Percepta Prediction call	Reliability index	Reliability assessment
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	0.44	BORDERLINE RELIABLE

Leadscope chromosome aberration in vivo composite predictions

Chemical	Leadscope Prediction call	Leadscope Positive Prediction probability	Prediction reliability parameters
			Model Fragment Count	30% Sim. Training Neighbors Count	Reliability assessment
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	0.08	20	34	RELIABLE

Conclusions:

Interpretation of results: negative

Based on Leadscope predictions it was concluded that bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate is NEGATIVE for chromosome aberration in vitro composite.

Executive summary:

bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate is NEGATIVE for chromosome aberration in vitro composite.

Chemical	ACD/Percepta	Reliability assessment	Leadscope	CONSENSUS
bis(2-(2-(2-butoxyethoxy)ethoxy)ethyl) adipate	NEGATIVE	BORDERLINE RELIABLE	NEGATIVE	NEGATIVE

Reference 4

Endpoint:

genetic toxicity in vitro, other

Type of information:

read-across based on grouping of substances (category approach)

Adequacy of study:

weight of evidence

Justification for type of information:

Adipic acid diesters category. See attached report.

Key result

Remarks on result:

other: no mutagrenic potential (based on read-across)

Conclusions:

According to the category read-across approach, no genotoxic potential is expected for the adipic acid diesters category.

Endpoint conclusion

Endpoint conclusion:

no adverse effect observed (negative)

Genetic toxicity in vivo

Description of key information

QSAR studies support the conclusion of in vitro mutagenicity dataset.

Endpoint conclusion

Endpoint conclusion:

no adverse effect observed (negative)

Justification for classification or non-classification

Basing on the available data, bis[2-[2-(2-butoxyethoxy)ethoxy]ethyl]adipate is not classified for mutagenicity according to Regulation (EC) n. 1272/2008.