3,5-xylidine

Endpoint summary

Description of key information

Skin sens: QSAR prediction; negative

Key value for chemical safety assessment

Skin sensitisation

Link to relevant study records

Reference

Endpoint:

skin sensitisation: in vivo (LLNA)

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

28 NOV 2022

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
OECD QSAR Toolbox v4.5

2. MODEL (incl. version number)
Data gap filling Read-across method in QSAR toolbox

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
Cc1cc(C)cc(N)c1

4. Read across justification for the endpoint
Data on 2,4-xylidine and 2,6-xylidine (source substances) are used to fill data gaps for 3,5-xylidine (target substance). The target substance is a structural isomer of source substances. The physical and chemical properties of the source and target substances are in the same range. With a molecular weight of 121 g/mol they are small enough to be absorbed. The logP values are 2.02, 1.96 and 1.83 and the water solubility is 5.6, 7.2 and 4.8 g/L for the source1, source2 and target substances, respectively. This indicates that these substances are favorable for dermal absorption. Thus, a good bioavailability via the skin is indicated for both, the sources, and the target substance.

Guideline:

other: ECHA Guidance R.6

Version / remarks:

May 2008

Principles of method if other than guideline:

- Software tool(s) used including version: OECD QSAR Toolbox v4.5
- Model(s) used: data gap filling Read-across method in QSAR toolbox
- Model description:
Read-across and trend analysis use the available experimental data in the data matrix to fill a data gap. “(Q)SAR models” gives access to a library of external (Q)SAR models which have been integrated into the Toolbox. The choice of the most relevant data gap mechanism depends on the following considerations:
Read-across can be applied to qualitative or quantitative endpoints. It is the appropriate data-gap filling method for “qualitative” endpoints like skin sensitization or mutagenicity for which a limited number of results are possible (e.g. positive, negative, equivocal). Furthermore read-across is recommended for “quantitative endpoints” (e.g., 96h-LC50 for fish) if only a low number of analogues with experimental results are identified. Read across is also appropriate to be used for endpoints with numerical estimation such as BOD, BCF, Repeated dose toxicity, etc.
Trend analysis is the appropriate data-gap filling method for “quantitative endpoints” (e.g., 96h-LC50 for fish) if a high number of analogues with experimental results are identified.
“(Q)SAR models” can be used to fill a data gap if no adequate analogues are found for a target chemical.
- Justification of QSAR prediction: see field 'Justification for type of information'

Specific details on test material used for the study:

Cc1cc(C)cc(N)c1

Remarks on result:

no indication of skin sensitisation based on QSAR/QSPR prediction

Interpretation of results:

study cannot be used for classification

Conclusions:

According to read across method in QSAR toolbox, test substance is predicted to be negative for the endpoint skin sensitisation.

Executive summary:

The skin sensitisation endpoint was covered by data derivate from QSAR toolbox read-across method. Two measured LLNA data were used to fill the data gap of test item. Both experimental data results were negative for skin sensitising. The studies followed OECD Guideline under GLP compliance, so the results are reliable. As the registered substance is a structural isomer of these two substances, the registered substance is also predicted to be a negative for the endpoint skin sensitisation.

Endpoint conclusion

Endpoint conclusion:

no adverse effect observed (not sensitising)

Additional information:

The skin sensitisation endpoint was covered by data derivate from QSAR toolbox read-across method. Two measured LLNA data were used to fill the data gap of test item. Both experimental data results were negative for skin sensitising. The studies followed OECD Guideline under GLP compliance, so the results are reliable. As the registered substance is a structural isomer of these two substances, the registered substance is also predicted to be a negative for the endpoint skin sensitisation.

Respiratory sensitisation

Endpoint conclusion

Endpoint conclusion:

no study available

Justification for classification or non-classification

Skin sensitisation study was conducted using OECD QSAR toolbox Read-across method. Two measured LLNA data (negative) were used to fill the endpoint. As the registered substance is a structural isomer of these two substances, the registered substance is also predicted to be negative for the endpoint skin sensitisation. However, QSAR prediction itself is limited in application range. Conclusively, the substance does not need to be classified for skin sensitisation according to Regulation (EC) No 1272/2008.