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Diss Factsheets

Administrative data

Description of key information

The Danish QSAR is a freely available database developed by the Technical University of Denmark (DTU) that can be used for regulatory purposes. Three different in silico models for skin sensitisation prediction are implemented in the Danish QSAR Database: CASE Ultra, Leadscope and SciQSAR. 
Two of the three models predictions are within the corresponding applicability domain and since these predictions are concordant in predicting a positive effect, the battery alghoritm outcome is evaluated as positive. 


 


The OECD QSAR Toolbox is a freely available computational tool developed by the Laboratory of Mathematical Chemistry (LMC) of “Prof. Dr. As. Zlatarov” University (Bulgaria) that can be used for regulatory purposes. The automated workflow for skin sensitisation potential prediction implemented in the OECD QSAR Toolbox is based on experimental EC3 data from LLNA (Local Lymph Node Assay) and from skin sensitization data from GPMT (Guinea Pig Maximization Test) assays. Protein binding structural alerts for skin sensitization are detected in the target molecule AP 729. 

Key value for chemical safety assessment

Skin sensitisation

Link to relevant study records

Referenceopen allclose all

Endpoint:
skin sensitisation, other
Remarks:
Validated QSAR model
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
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:
The OECD QSAR Toolbox is a freely available computational tool developed by the Laboratory of Mathematical Chemistry (LMC) of “Prof. Dr. As. Zlatarov” University (Bulgaria) that can be used for regulatory purposes.
Qualifier:
according to guideline
Guideline:
other: REACH Guidance on QSARs R.6
Remarks on result:
positive indication of skin sensitisation
Remarks:
The automated workflow for skin sensitisation potential prediction implemented in the OECD QSAR Toolbox is based on LLNA and GPMT experimental data, and qualitatively predicts these endpoints. Further information on results is provided in section "Any other information on results incl. tables".

The automated workflow for skin sensitisation potential prediction implemented in the OECD QSAR Toolbox is based on experimental EC3 data from LLNA (Local Lymph Node Assay) and from skin sensitization data from GPMT (Guinea Pig Maximization Test) assays. The model qualitatively predicts skin sensitisation in vivo endpoint according to different profiling criteria.


In the present case, protein binding structural alerts for skin sensitization by OASIS (alkyl halides) are detected in the target molecule AP 729. Further details on the prediction and on the category members can be found in the attached QPRF and data matrix. 


The substance is predicted to have the potential to cause skin sensitising effects. 

Interpretation of results:
Category 1A (indication of significant skin sensitising potential) based on GHS criteria
Conclusions:
According to the automated workflow for skin sensitisation potential prediction implemented in the OECD QSAR Toolbox, the substance is predicted to have the potential to cause skin sensitising effects. 
Executive summary:

The automated workflow for skin sensitisation potential prediction implemented in the OECD QSAR Toolbox is based on experimental EC3 data from LLNA (Local Lymph Node Assay) and from skin sensitization data from GPMT (Guinea Pig Maximization Test) assays. 


Protein binding structural alerts for skin sensitization are detected in the target molecule AP 729. 


The substance is therefore predicted to have the potential to cause skin sensitising effects. 

Endpoint:
skin sensitisation, other
Remarks:
Validated QSAR model
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
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:
The Danish QSAR is a freely available database developed by the Technical University of Denmark (DTU) that can be used for regulatory purposes.
Information on models can be found in the attached QMRFs and QPRFs.
Qualifier:
according to guideline
Guideline:
other: REACH Guidance on QSARs R.6
Remarks on result:
positive indication of skin sensitisation
Remarks:
Three different in silico models for skin sensitisation prediction are implemented in the Danish QSAR Database. These models qualitatively predict GPMT and Allergic Contact Dermatitis in Humans. Further information on results provided in section "Any other information on results incl. tables".

Three different in silico models for skin sensitisation prediction are implemented in the Danish QSAR Database: CASE Ultra, Leadscope and SciQSAR. 


These models qualitatively predict the endpoint effect based on data from human epidemiological studies on allergic contact dermatitis (ACD) and results from the Guinea Pig Maximization Test (GPMT)


Single QSAR predictions of each indipendent QSAR model are then combined into a battery prediction using a battery alghoritm. 


The results and the battery approach result for substance AP 729 are give in the following Table. 


 


























Table 1
 Battery approachCASE Ultra LeadscopeSciQSAR
Allergic contact dermatitis
in Guinea Pig and Human
POSPOSPOSPOS
Model Domain INOUTININ

Where:
POS: positive effect; IN: inside applicability domain; OUT: outside applicability domain


 


As two models (Leadscope and SciQSAR) predictions are within the relative applicability domain and these models are concordant in predicting a positive effect, the battery alghoritm outcome is positive. 


The substance is therefore predicted to have the potential to cause skin sensitising effects. 


 

Interpretation of results:
Category 1A (indication of significant skin sensitising potential) based on GHS criteria
Conclusions:
According to two different models of the Danish QSAR Database, the substance is predicted to have the potential to cause skin sensitising effects. 
Executive summary:

Three different in silico models for skin sensitisation prediction are implemented in the Danish QSAR Database: CASE Ultra, Leadscope and SciQSAR.


Two of the three models predictions are within the corresponding applicability domain and since these predictions are concordant in predicting a positive effect, the battery alghoritm outcome is evaluated as positive. 


The substance is therefore predicted to have the potential to cause skin sensitising effects. 

Endpoint conclusion
Endpoint conclusion:
adverse effect observed (sensitising)

Justification for classification or non-classification

According to two different models of the Danish QSAR Database, the substance is predicted to have the potential to cause skin sensitising effects. 


Moreover, also according to the automated workflow for skin sensitisation potential prediction implemented in the OECD QSAR Toolbox, the substance is predicted to have the potential to cause skin sensitising effects.