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Description of key information

(-)-alpha-Pinene is predicted as moderate sensitiser to the skin (predicted LLNA EC3%: 9.6) using Derek Nexus v5.0.2.

(-)-alpha-Pinene is predicted as skin sensitiser using the VEGA skin sensitisation model (CAESAR).

Key value for chemical safety assessment

Skin sensitisation

Link to relevant study records

Referenceopen allclose all

Endpoint:
skin sensitisation, other
Remarks:
QSAR model
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
25/08/2017
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:
Nexus v2.1.1

2. MODEL:
Derek Nexus v5.0.2

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL:
CC1=CC[C@H]2C[C@@H]1C2(C)C


4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL:
See attached QMRF

5. APPLICABILITY DOMAIN:
See attached prediction report

6. ADEQUACY OF THE RESULT:
See attached prediction report
Qualifier:
no guideline required
Principles of method if other than guideline:
Derek Nexus is a proprietary, rule-based expert system for the prediction of toxicity. Its knowledge base is composed of alerts, examples and reasoning rules which may each contribute to the predictions made by the system. Each alert in Derek describes a chemical substructure believed to be responsible for inducing a specific toxicological outcome (often referred to as a toxicophore). Alerts are derived by experts, using toxicological data and information regarding the biological mechanism of action. Where relevant, metabolism data may be incorporated into an alert, enabling the prediction of compounds which are not directly toxicity but are metabolised to an active species. The derivation of each alert is described in the alert comments along with supporting references and example compounds where possible. By reporting this information to the user, Derek provides highly transparent predictions. The use of structural alerts for the prediction of toxicity is both widely understood and the subject of many publications. Derek Nexus makes predictions for and against toxicity through reasoning. For the endpoint of skin sensitisation, predictions for toxicity decrease in confidence in the following order: certain> probable>plausible>equivocal. Predictions against toxicity increase in confidence in the following order: doubted
GLP compliance:
no
Specific details on test material used for the study:
not applicable
Key result
Parameter:
other: EC3% (predicted)
Value:
9.6
Other effects / acceptance of results:
Reasoning summary:
Prediction strength: EQUIVOCAL
Alert matched: 712 Terpenoid
Please refer to the attached prediction report for further details about this alert.
Interpretation of results:
Category 1B (indication of skin sensitising potential) based on GHS criteria
Conclusions:
(-)-alpha-Pinene is predicted as moderate sensitiser to the skin (predicted LLNA EC3%: 9.6) using Derek Nexus v5.0.2.
The prediction is based on the triggered structured alert for terpenoids.
The prediction strength is Equivocal.
Executive summary:

Based on the derived prediction using Derek Nexus v5.0.2, (-)-alpha-pinene is predicted as moderate sensitiser to the skin with a predicted LLNA EC3 of 9.6% and a prediction strength as Equivocal. This substance triggered a skin sensitisation alert for terpenoids.

Therefore, (-)-alpha-pinene is classifed as skin sensitiser category 1B.

Endpoint:
skin sensitisation, other
Remarks:
QSAR model
Type of information:
(Q)SAR
Adequacy of study:
supporting study
Study period:
25/08/2017
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 limited documentation / justification
Justification for type of information:
1. SOFTWARE:
VEGA in silico platform v1.1.4

2. MODEL:
VEGA Skin Sensitisation model (CAESAR) 2.1.6

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL:
CC1=CC[C@H]2C[C@@H]1C2(C)C


4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL:
See attached article

5. APPLICABILITY DOMAIN:
See attached prediction report

6. ADEQUACY OF THE RESULT:
See attached prediction report
Qualifier:
no guideline required
Principles of method if other than guideline:
To address the skin sensitization issue, two complementary approaches were investigated in the CAESAR Platform:
a) A global approach aimed at developing a classifier to discriminate sensitizers vs non sensitizers.
b) A local approach that investigated a mechanistic based category formation coupled with a read-across approach within each category.

The CAESAR model for skin sensitization was developed using Adaptive Fuzzy Partition (AFP) – AFP was used to develop classification models implementing a fuzzy partition algorithm. It models relations between molecular descriptors and chemical activities by dynamically dividing the descriptor space into a set of fuzzy partitioned subspaces. The aim of this algorithm is to select the descriptor and the cut position that allow to get the maximal difference between the two fuzzy rule scores generated by the new subspaces. The score is determined by the weighted average of the chemical activity values in an active subspace A and in its neighbouring subspaces.

A complementary approach was developed to enable potential mechanisms of toxic action to be assigned to chemicals thought to be capable of skin sensitisation. This approach was based on the work of Aptula and Roberts [2] who had previously suggested that for a chemical to be a skin sensitiser it must be capable (either directly or after some abiotic or metabolic transformation) of one of five electrophilic-nucleophilic reactions. The approach undertaken was to devise SMARTS patterns capable of identifying the electrophilic mechanisms previously assigned to the 210 Gerberick LLNA dataset [3]. The 44 chemical TIMES-SS LLNA data, in which each chemical has also had a mechanism of action assigned to it by the same authors [4] was then used to validate the applicability of the SMARTS patterns.

Reference: http://www.caesar-project.eu/index.php?page=results§ion=endpoint&ne=2
GLP compliance:
no
Parameter:
other:
Remarks:
QSAR model
Run / experiment:
Prediction: Skin Sensitiser (realible result)
Other effects / acceptance of results:
Prediction is Sensitizer, the result appears reliable as the substance is within the applicability domain of the model.
Please refer to the applicability domain information provided in the attached prediction report.

Please refer to the attached prediction report for further information about the prediction result for (-) alpha pinene, list of most similar compounds found in the training set, parameters used for evaluating the reliability in prediction.

Interpretation of results:
Category 1 (skin sensitising) based on GHS criteria
Conclusions:
(-)-alpha-Pinene is predicted as skin sensitiser using the VEGA skin sensitisation model (CAESAR). (-)-alpha-Pinene falls within the applicability domain of the model.
Executive summary:

(-)-alpha-Pinene was predicted, with a good reliability, as skin sensitiser using the VEGA Skin Sensitisation model (CAESAR v2.1.6). (-)-alpha-Pinene falls within the applicability domain of the model.

Endpoint conclusion
Endpoint conclusion:
adverse effect observed (sensitising)
Additional information:

Based on the derived prediction using Derek Nexus v5.0.2, (-)-alpha-pinene is predicted as moderate sensitiser to the skin with a predicted LLNA EC3 of 9.6% and a prediction strength as Equivocal. This substance triggered a skin sensitisation alert for terpenoids. This result was confrmed with one other prediction: VEGA Skin Sensitisation model.

(-)-alpha-Pinene was predicted with a good reliability as skin sensitiser using the VEGA Skin Sensitisation model (CAESAR v2.1.6). (-)-alpha-Pinene falls within the applicability domain of the model.

Respiratory sensitisation

Endpoint conclusion
Endpoint conclusion:
no study available

Justification for classification or non-classification

(-)-alpha-Pinene is predicted as moderate sensitiser to the skin (predicted LLNA EC3% : 9.6) using Derek Nexus v5.0.2.

Therefore, (-)-alpha-pinene is classified as skin sensitiser category 1B according to CLP Regulation (EC) No 1272/2008 and UN GHS.

This classification is confimed by the results obtained with the VEGA skin sensitisation model.