(E)-1,2-difluoroethylene

Endpoint summary

Description of key information

Introduction

For the evaluation of the toxicological profile of the compound, quantitative structure activity relationship (QSAR) modelling was performed using BIOVIA Discovery Studio (TOPKAT) 4.5, VEGA NIC 1.1.4, OECD QSAR Toolbox 4.4, and DEREK Nexus 6.0.1.

Appraisal of (Q)SAR Modelling

Results

Software	Model	Result (Reliability*)
TOPKAT	extended	Sensitizer (1)
VEGA	CAESAR 2.1.6	Non-sensitizer (0)
	IRFMN/JRC 1.0.0	Non-sensitizer (0)
Derek	Skin sensitisation	Non-sensitizer
OECD QSAR Toolbox	Profilers	1 alert for Protein Binding by SN2
	Metabolites	No metabolites identified
	Read-across prediction	Sensitizer (2)
Toxtree	Skin sensitisation reactivity domains	Alert for SN2-Nucleophillic Aliphatic Substitution
Danish QSAR Database	Consensus	Negative - out of domain**

*Reliability score: where 3= Good, 2=Moderate, 1=Low, and 0 = not reliable
**Consensus based on 3 models: CASE Ultra (NEG_OUT), Leadscope (NEG_OUT), and SciQSAR (NEG_IN).

 

TOPKAT:

TOPKAT predicted the compound to be a sensitizer, though reliability is noted to be low owing to various issues, such as the poor structural similarity between TKN1 and the nearest neighbours in the training set. Also, three out of the four nearest structures have existing study data are non-sensitizers, in disagreement with the predicted value for TKN1. Furthermore, the accuracy of the predicted value is called into question as two of the similar structures, 1,2-Dichloroethane and Chlorobenzene, were incorrectly predicted to be positive by a narrow margin. It is noteworthy also in relation to this, that the distance between the Bayesian score for TKN1 and the best split value of the overall dataset is also small, suggesting further uncertainty. The prediction has been considered as part of the weight of evidence, but it is noted that the reliability of this prediction is considered to be low.

 

VEGA:

For both the CAESAR and the IFRMN/JRC models, the compound did not fall into the applicability domain of the model, with fragments involving flurinated alkenes being poorly represented in their respective training sets. Beyond the failure to meet with the applicability domain, while both models predicted the compound to be non-sensitising, they both displayed either only moderate similarity between the TKN1 and the nearest neighbours, only moderate concordance, only moderate accuracy, or all of these, suggesting significant uncertainty in the predictions. As such these predictions were not considered reliable. 

 

DEREK:

The knowledgebase in DEREK did not identify the compound as a sensitizer, suggesting no structural alerts for skin sensitisation were fired. However, the model also specifies that all components of the compound were features that were not found in the negative prediction dataset. The conclusion is that the compound is not sensitising on a lack of alerts. As no alerts are referenced and no EC3 values predicted, it was not possible to determine a reliability for this result.

 

TOXTREE:

It was identified in Toxtree in the Skin sensitisation reactivity domains an alert for SN2 nucleophilic aliphatic substitution was fired, suggesting a potential for sensitisation.

 

TOOLBOX:

As with Toxtree, the Toolbox profilers identified an alert for SN2 via the Protein binding from OECD profiler for “Polarised alkenes with a halogen leaving group”.
The alert refers to potential SN2 reactions with amines from proteins and halogenated alkenes, where the halogen is the leaving group, allowing the alkene to bind with the protein. Where the halogen can be Fluorine, chlorine, bromine of iodine.

However it is noteworthy that no other profilers found an alert, and no autoxidation or skin metabolism products were predicted, thus further assessment of alerts for metabolite compounds was not possible.

 

DANISH QSAR database:

The Danish QSAR database predicted the compound to be negative, however overall consensus was determined to be out of domain.

 

Conclusion

There is disagreement amongst the models, and most predictions were of low reliability. Due to these issues, while there is a weight of evidence suggesting that TKN1 may be sensitizing, further confirmatory testing beyond the scope of this assessment would usually be recommended to determine whether TKN1 should be considered sensitizing, and further to this, a measure of potency if required. However, due to the inherent properties of the compound, further testing is not currently perceived to be possible. While it is noteworthy that two of the nearest compounds to the target in the Toolbox read across prediction were strong sensitizers, as with the other models all nearest compounds were significantly different to the target compound. Also, while the toolbox read across prediction is based on the alert for halogenated alkenes, it is noted that none of the nearest compounds to the target structure were fluorinated compounds. This is further the case with the similar halogenated compounds in other models, with data being available only from chlorinated and brominated structures.
This is also apparent for the negative prediction from DEREK, in that the unclassified feature was the fluorinated alkene, and hence the entire target compound, as discussed above.

Thus no firm conclusion can be made for TKN1 and no classification is concluded and the assessment is indeterminate.

 

As the substance is a gas, skin sensitisation (dermal exposure) is not considered to be a relevant concern for the substance. In addition, the substance will be used mainly in closed systems where significant (dermal) exposure is not considered likely.

Key value for chemical safety assessment

Skin sensitisation

Link to relevant study records

Reference

Reference 1

Endpoint:

skin sensitisation, other

Type of information:

(Q)SAR

Remarks:

TOXTREE

Adequacy of study:

weight of evidence

Reliability:

3 (not reliable)

Rationale for reliability incl. deficiencies:

results derived from a (Q)SAR model, with limited documentation / justification, but validity of model and reliability of prediction considered adequate based on a generally acknowledged source

Justification for type of information:

1. SOFTWARE
Toxtree (stimation of Toxic Hazard - Decision Tree Approach)

2. MODEL (incl. version number)

v3.1.0-1851

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
F\C=C\F

4. APPLICABILITY DOMAIN
Toxtree is based on classification trees and does not provide such information and thus no reliability is assigned. All original model results are presented in the software printout section.

Principles of method if other than guideline:

- Principle of test: QSAR for skin sensitisation
- Short description of test conditions: n/a
- Parameters analysed / observed: QSAR for skin sensitisation (TOXTREE)

GLP compliance:

no

Run / experiment:

other: QSAR: TOXTREE

Remarks on result:

positive indication of skin sensitisation

Interpretation of results:

study cannot be used for classification

Conclusions:

It was identified in Toxtree in the Skin sensitisation reactivity domains an alert for SN2 nucleophilic aliphatic substitution was fired, suggesting a potential for sensitisation.

Reference 2

Endpoint:

skin sensitisation, other

Type of information:

(Q)SAR

Remarks:

OECD QSAR toolbox

Adequacy of study:

weight of evidence

Reliability:

2 (reliable with restrictions)

Justification for type of information:

1. SOFTWARE
QSAR Toolbox 4.4.1

2. MODEL (incl. version number)
QSAR Toolbox 4.4.1
Database version: 4.4.1
TPRF v4.4.1

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
F\C=C\F

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
Please see attached justification

5. APPLICABILITY DOMAIN
Please see attached justification

6. ADEQUACY OF THE RESULT
The Toolbox profilers identified an alert for SN2 via the Protein binding from OECD profiler for “Polarised alkenes with a halogen leaving group”.
The alert refers to potential SN2 reactions with amines from proteins and halogenated alkenes, where the halogen is the leaving group, allowing the alkene to bind with the protein. Where the halogen can be Fluorine, chlorine, bromine of iodine.

However it is noteworthy that no other profilers found an alert, and no autoxidation or skin metabolism products were predicted, thus further assessment of alerts for metabolite compounds was not possible. Therefore an attempt was made to derive a prediction for skin sensitisation via read-across in the Toolbox using this alert alone, which led to a positive prediction, relating to 4 compounds sharing the same alert. One being negative, and the other three being positive. All involving chlorine, but where two compounds are identified as being category 1A, one is identified as being category 1B. It was not possible to determine a category for the target compound via a predicted EC3.

Qualifier:

no guideline followed

Principles of method if other than guideline:

- Principle of test: QSAR for skin sensitisation
- Short description of test conditions: n/a
- Parameters analysed / observed: QSAR for skin sensitisation (OECD QSAR toolbox)

GLP compliance:

no

Run / experiment:

other: (QSAR) OECD TOOLBOX

Remarks on result:

positive indication of skin sensitisation

Interpretation of results:

study cannot be used for classification

Conclusions:

As with Toxtree, the Toolbox profilers identified an alert for SN2 via the Protein binding from OECD profiler for “Polarised alkenes with a halogen leaving group”.
The alert refers to potential SN2 reactions with amines from proteins and halogenated alkenes, where the halogen is the leaving group, allowing the alkene to bind with the protein. Where the halogen can be Fluorine, chlorine, bromine of iodine.

However it is noteworthy that no other profilers found an alert, and no autoxidation or skin metabolism products were predicted, thus further assessment of alerts for metabolite compounds was not possible. Therefore an attempt was made to derive a prediction for skin sensitisation via read-across in the Toolbox using this alert alone, which led to a positive prediction, relating to 4 compounds sharing the same alert. One being negative, and the other three beign positive. All involving chlorine, but where two compounds are identified as being category 1A, one is identified as being category 1B. It was not possible to determine a category for the target compound via a predicted EC3.

Reference 3

Endpoint:

skin sensitisation, other

Type of information:

(Q)SAR

Remarks:

DEREK

Adequacy of study:

weight of evidence

Reliability:

3 (not reliable)

Justification for type of information:

1. SOFTWARE
DEREK Nexus: 6.0.1, Nexus 2.2.1

2. MODEL (incl. version number)
Nexus 2.2.1
skin sensitisation in mammals

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
F\C=C\F

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
Please see attached justification

5. APPLICABILITY DOMAIN
Please see attached justification

6. ADEQUACY OF THE RESULT
The knowledgebase in DEREK did not identify the compound as a sensitizer, suggesting no structural alerts for skin sensitisation were fired. However, the model also specifies that all components of the compound were features that were not found in the negative prediction dataset. The conclusion is that the compound is not sensitising based on a lack of alerts. As no alerts are referenced, and subsequently no EC3 values predicted, it was not possible to determine a reliability for this result.

Principles of method if other than guideline:

- Principle of test: QSAR for skin sensitisation
- Short description of test conditions: n/a
- Parameters analysed / observed: QSAR for skin sensitisation (DEREK)

GLP compliance:

no

Run / experiment:

other: QSAR: DEREK

Remarks on result:

no indication of skin sensitisation

Interpretation of results:

study cannot be used for classification

Conclusions:

The knowledgebase in DEREK did not identify the compound as a sensitizer, suggesting no structural alerts for skin sensitisation were fired. However, the model also specifies that all components of the compound were features that were not found in the negative prediction dataset. The conclusion is that the compound is not sensitising based on a lack of alerts. As no alerts are referenced, and subsequently no EC3 values predicted, it was not possible to determine a reliability for this result.

Reference 4

Endpoint:

skin sensitisation, other

Type of information:

(Q)SAR

Remarks:

VEGA (IRFMN/JRC)

Adequacy of study:

weight of evidence

Reliability:

3 (not reliable)

Rationale for reliability incl. deficiencies:

results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification

Justification for type of information:

Substance
CAS number 1630-78-0
EC number 216-629-0
Chemical name
IUPAC (E)-1,2-Difluoroethene
Other Ethene, 1,2-difluoro-
Other (E)-1,2-difluoroethylene

Structure codes
SMILES F\C=C\F
InChI 1S/C2H2F2/c3-1-2-4/h1-2H/b2-1+
Other
Stereochemical features Not applicable

General Information
Date of QPRF 15 February 2021

Author and contact details Covance Laboratories Limited

Prediction
Endpoint (OECD Principle 1)
Endpoint Skin Sensitisation (None vs Sensitiser)
Dependent variable Classification as sensitiser or non-sensitiser
Algorithm (OECD Principle 2)
Model or submodel name IRFMN/JRC model for skin sensitisation (None vs Sensitiser) within VEGA 1.1.4
Model version 2.1.6
Reference to QMRF Not available
Predicted values (model result) Non-Sensitiser
Predicted values (comments) According to VEGA's evaluation scheme the prediction has low reliability.
Input for prediction Smiles
Descriptor values Not provided
Applicability domain (OECD Principle 3)
Domains
i. Global AD Index = 0.365 the predicted compound is outside the Applicability Domain of the model.
ii. Similarity index = 0.625 only moderately similar compounds with known experimental value in the training set have been found.
iii Accuracy index = 1 accuracy of prediction for similar molecules found in the training set is good.
iv Concordance index = 0.607 some similar molecules found in the training set have experimental values that disagree with the predicted value.
v Descriptors range check = True, descriptors for this compound have values inside the descriptor range of the compounds of the training set.
vi. ACF index = 0.51 a prominent number of atom centered fragments of the compound have not been found in the compounds of the training set or are rare fragments (1 unknown fragments and 1 infrequent fragments found).
Structural analogues
i. CAS: 75-35-4
ii. CAS: 96-33-3
iii. CAS: 107-22-2
iv. CAS: 68-12-2

Consideration on structural analogues
With 60% the average similarity of the four analogues to the query structure is considered moderate. Two out of the four nearest structures are sensitisers thus indicating moderate concordance with the query structure prediction. Accuracy between predicted and actual result is moderate as CAS 68-12-2 is predicted as a false positive.
The uncertainty of the prediction (OECD principle 4)
Uncertainty may be indicated by query structure which is outside applicability domain of the model, only moderate structural similarity, moderate concordance and moderate accuracy. Furthermore, the unknown and infrequent fragments referred to in the ACF index above are FC and FC=C, which is a majority of the components in the compound, suggesting further uncertainty. VEGAs own reliability score is low for the prediction also.
The chemical and biological mechanisms according to the model underpinning the predicted result (OECD principle 5)
Not applicable since statistical model

Adequacy (Optional)
Regulatory purpose
Skin sensitisation endpoint for determining property of chemical to be sensitizer or not sensitizer.

Approach for regulatory interpretation of the model result
Result is directly applicable since no conversion of the result is required.

Outcome
Non-Sensitiser. There is considerable uncertainty in the prediction due to the reasons listed under the section 3.4 of this QPRF.

Conclusion
The prediction is not considered reliable, as the prediction is not within the applicability domain of the model.

Principles of method if other than guideline:

Principle of test: QSAR for skin sensitisation
Short description of test conditions: n/a
Parameters analysed/observed: QSAR for skin sensitisation (VEGA, IRFMN/JRC)

GLP compliance:

no

Run / experiment:

other: IRFMN/JRC (VEGA)

Remarks on result:

not determinable because of methodological limitations

Interpretation of results:

study cannot be used for classification

Conclusions:

The prediction is not considered reliable, as the prediction is not within the applicability domain of the model.

Reference 5

Endpoint:

skin sensitisation, other

Type of information:

(Q)SAR

Remarks:

(VEGA, CAESAR)

Adequacy of study:

weight of evidence

Reliability:

3 (not reliable)

Rationale for reliability incl. deficiencies:

results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification

Justification for type of information:

Substance
CAS number 1630-78-0
EC number 216-629-0
Chemical name
IUPAC (E)-1,2-Difluoroethene
Other Ethene, 1,2-difluoro-
Other (E)-1,2-difluoroethylene
Structural formula

Structure codes
SMILES F\C=C\F
InChI 1S/C2H2F2/c3-1-2-4/h1-2H/b2-1+
Other
Stereochemical features Not applicable

General Information
Date of QPRF 15 February 2021

Author and contact details Covance Laboratories Limited

Prediction
Endpoint (OECD Principle 1)
Endpoint Skin Sensitisation (None vs Sensitiser)
Dependent variable Classification as sensitiser or non-sensitiser
Algorithm (OECD Principle 2)
Model or submodel name Extension of the original CAESAR model for skin sensitisation (None vs Sensitiser) within VEGA 1.1.4
Model version 2.1.6
Reference to QMRF Not available
Predicted values (model result) Non-Sensitiser
Predicted values (comments) According to VEGA's evaluation scheme the prediction has low reliability.
Input for prediction Smiles
Descriptor values Not provided
Applicability domain (OECD Principle 3)
Domains
i. Global AD Index = 0.356, the predicted compound is outside the Applicability Domain of the model.
ii. Similarity index = 0.624, only moderately similar compounds with known experimental value in the training set have been found.
iii Accuracy index = 1, accuracy of prediction for similar molecules found in the training set is good.
iv Concordance index = 0.609, some similar molecules found in the training set have experimental values that disagree with the predicted value.
v Descriptors range check = True, descriptors for this compound have values inside the descriptor range of the compounds of the training set.
vi. ACF index = 0.51 a prominent number of atom centered fragments of the compound have not been found in the
compounds of the training set or are rare fragments (1 unknown fragments and 1 infrequent fragments found).
Structural analogues i. CAS: 75-35-4
ii. CAS: 107-22-2
iii. CAS: 140-88-5
iv. CAS: 57-57-8

Consideration on structural analogues With 59% the average similarity of the four analogues to the query structure is considered moderate. Three out of the four structures are sensitisers thus indicating low concordance with the query structure prediction. Accuracy between predicted and actual result is high as all four structures are predicted correctly.

The uncertainty of the prediction (OECD principle 4)

Uncertainty may be indicated by query structure which is outside applicability domain of the model, moderate structural similarity and low concordance. Furthermore, the unknown and infrequent fragments referred to in the ACF index above are FC and FC=C, which is a majority of the components in the compound, suggesting further uncertainty. VEGAs own reliability score is low for the prediction also.
The chemical and biological mechanisms according to the model underpinning the predicted result (OECD principle 5)
Not applicable since statistical model

Adequacy (Optional)

Regulatory purpose
Skin sensitisation endpoint for determining property of chemical to be sensitizer or not sensitizer.

Approach for regulatory interpretation of the model result
Result is directly applicable since no conversion of the result is required.

Outcome
Not-Sensitiser. There is considerable uncertainty in the prediction due to the reasons listed under the section 3.4 of this QPRF.

Conclusion
The prediction is not considered reliable, as the prediction is not within the applicability domain of the model.

Principles of method if other than guideline:

Principle of test: QSAR for skin sensitisation
Short description of test conditions: n/a
Parameters analysed/observed: QSAR for skin sensitisation (VEGA, CAESAR)

GLP compliance:

no

Run / experiment:

other: CAESAR (VEGA)

Remarks on result:

not determinable because of methodological limitations

Interpretation of results:

study cannot be used for classification

Conclusions:

The prediction is not considered reliable, as the prediction is not within the applicability domain of the model.

Reference 6

Endpoint:

skin sensitisation, other

Type of information:

(Q)SAR

Remarks:

(TOPKAT)

Adequacy of study:

weight of evidence

Reliability:

3 (not reliable)

Rationale for reliability incl. deficiencies:

results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification

Justification for type of information:

Substance
CAS number 1630-78-0
EC number 216-629-0
Chemical name
IUPAC (E)-1,2-Difluoroethene
Other Ethene, 1,2-difluoro-
Other (E)-1,2-difluoroethylene

Structure codes
SMILES F\C=C\F
InChI 1S/C2H2F2/c3-1-2-4/h1-2H/b2-1+
Other
Stereochemical features Not applicable

General Information
Date of QPRF 04 February 2021

Author and contact details Covance Laboratories Limited,

Prediction
Endpoint (OECD Principle 1)
Endpoint Skin Sensitisation (None vs Sensitiser)
Dependent variable Classification as sensitiser or non-sensitiser
Algorithm (OECD Principle 2)
Model or submodel name Toxicity Prediction (Extensible)Toxicity Prediction (Extensible) Skin sensitisation (None vs Sensitiser)
Model version 4.5
Reference to QMRF The corresponding QMRF "BIOVIA toxicity prediction model – skin sensitiser vs nonsensitiser" is available from JRC QSAR Model Database (http://qsardb.jrc.it/qmrf)

QMRF identifier (ECB Inventory): :Q50-54-55-509.
The original data set was extended with 74 additional compounds from Covance database.
Predicted values (model result) Sensitiser
Predicted values (comments) Bayesian score of 0.12 is only just above the best split value of 1.134 which may suggest some uncertainty in the prediction.
Input for prediction Smiles

Descriptor values

Descriptor Value
LogP 0.138
Molecular weight (g/mol) 64
Number of hydrogen bond donors 0
Number of hydrogen bond acceptors 0
Number of rotatable bonds in the molecule 0
The fraction of polar surface area over 0
the total molecular surface area
FCFP_12: Unit functional class Not applicable
extended-connectivity atom type fingerprint
with a maximum length of 12 bonds

Applicability domain (OECD Principle 3)

Domains
i. All properties and OPS components are within expected ranges.
ii. All fingerprint features of the query molecule are found in the training set
iii. Considerations on the mechanism domain are not applicable since the
contributing FCFP_12 features of the model are selected purely on their
Bayesian score (statistical model)

Structural analogues
i. 1,2-Dichloroethane
ii. Triethylamine
iii. Chlorobenzene
iv. Bromostyrene

Consideration on structural analogues With 0.61 the average of the closest distance of the four analogues to the query structure the similarity is considered high, indicating low similarity. Three out of the four nearest structures are non-sensitizers, thus indicating low concordance with the query structure prediction. Accuracy between predicted and actual result is moderate as only two out of the four nearest compounds are predicted correctly, with 1,2-Dichloroethane and Chlorobenzene being marginally above the best split value.
The uncertainty of the prediction (OECD principle 4)
Uncertainty may be indicated primarily due to low structural similarity, low concordance with the query structure prediction and the nearest four structures, low accuracy of the predictions in the four nearest structures, and low distance between the Bayesian score and the best split value.
The chemical and biological mechanisms according to the model underpinning the predicted result (OECD principle 5)
Not applicable since statistical model

Adequacy (Optional)
Regulatory purpose Skin sensitisation endpoint for determining property of chemical to be sensitizer or not sensitizer.

Approach for regulatory interpretation of the model result
Result is directly applicable since no conversion of the result is required.

Outcome
Sensitiser. There is significant uncertainty in the prediction due to the reasons listed under the section 3.4 of this QPRF.

Conclusion
The compound is predicted to be sensitising, however there are significant issues with all measures of reliability, with the only redeeming feature being the molecule was within the applicability domain of the model. As such the reliability of this prediction is considered to be low.

Principles of method if other than guideline:

- Principle of test: QSAR for skin sensitisation
- Short description of test conditions: n/a
- Parameters analysed / observed: QSAR for skin sensitisation (TOPKAT)

GLP compliance:

no

Run / experiment:

other: TOPKAT

Remarks on result:

positive indication of skin sensitisation

Interpretation of results:

study cannot be used for classification

Conclusions:

TOPKAT predicted the compound to be a sensitizer, though reliability is noted to be low owing to various issues, such as the poor structural similarity between TKN1 and the nearest neighbours in the training set. Also, three out of the four nearest structures have existing study data are non-sensitizers, in disagreement with the predicted value for TKN1. Furthermore, the accuracy of the predicted value is called into question as two of the similar structures, 1,2-Dichloroethane and Chlorobenzene, were incorrectly predicted to be positive by a narrow margin. It is noteworthy also in relation to this, that the distance between the Bayesian score for TKN1 and the best split value of the overall dataset is also small, suggesting further uncertainty. The prediction has been considered as part of the weight of evidence, but it is noted that the reliability of this prediction is considered to be low.

Endpoint conclusion

Endpoint conclusion:

no adverse effect observed (not sensitising)

Respiratory sensitisation

Endpoint conclusion

Endpoint conclusion:

no study available

Justification for classification or non-classification

Owing to the physical characteristics of the compound, it was determined that the approach of using in vitro methods would not be viable in the case of any of the test methods available (OECD 442C, D or E). Further to this, testing in vivo would also not be viable. As such it was required to come to a conclusion with the in silico predictions. However, the various predictions made by the models were collectively of poor reliability in general. The weight of evidence of this assessment suggested that TKN1 is likely to possess skin sensitizing properties owing to the presence the halogenated alkene which has been identified as potentially leading to sensitization by some of the models. However it is not possible to determine the potential potency as a predicted EC3 value was not predicted by either DEREK, or the OECD QSAR Toolbox. Therefore a determination between a classification of Skin Sens. 1A or 1B cannot be made.
There is disagreement amongst the models, and most predictions were of low reliability. Due to these issues, while there is a weight of evidence suggesting that TKN1 may be sensitizing, further confirmatory testing beyond the scope of this assessment would usually be recommended to determine whether TKN1 should be considered sensitizing, and further to this, a measure of potency if required. However, due to the inherent properties of the compound as discussed above, further testing is not currently perceived to be possible. While it is noteworthy that two of the nearest compounds to the target in the Toolbox read across prediction were strong sensitizers, as with the other models all nearest compounds were significantly different to the target compound. Also, while the toolbox read across prediction is based on the alert for halogenated alkenes, it is noted that none of the nearest compounds to the target structure were fluorinated compounds. This is further the case with the similar halogenated compounds in other models, with data being available only from chlorinated and brominated structures. This is also apparent for the negative prediction from DEREK, in that the unclassified feature was the fluorinated alkene, and hence the entire target compound, as discussed above.
Thus no firm conclusion can be made for TKN1, while there are alerts relating the halogenated alkenes which may suggest classification as a precaution, owing to the uncertainty discussed above no classification is concluded and the assessment is indeterminate.