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Diss Factsheets

Toxicological information

Skin sensitisation

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Administrative data

Endpoint:
skin sensitisation: in chemico
Type of information:
(Q)SAR
Adequacy of study:
supporting study
Reliability:
2 (reliable with restrictions)
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:
1. SOFTWARE
OASIS TIMES v2.27.19.13

2. MODEL (incl. version number)
Skin sensitization with autoxidation, v. 21.26

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
NCCCOCCOCCOCCCN

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: In vivo: skin sensitization
- Unambiguous algorithm: refer to QMRF
- Defined domain of applicability:
1. General parametric requirements - includes ranges of variation of log KOW and MW. It specifies in
the domain only those chemicals that fall in the range of variation of the MW and log Kow defined on
the bases of the correctly predicted training set chemicals. This layer of the domain is applied only on
parent chemicals.
2. Structural domain - it is represented by list of atom - centered fragments extracted from the chem
icals in the training set. The training chemicals were split into two subsets: chemicals correctly
predicted by the model and incorrectly predicted
chemicals. These two subsets of chemicals were used to extract characteristics determining the
"good" and "bad" space of the domain. Extracted characteristics were split into three categories: u
nique characteristics of correct and incorrect chemicals (presented only in one of the subsets) and
fuzzy characteristics presented in both subsets of chemicals. Structural domain is applied on parent
chemicals, only.
3. Mechanistic domain - in SS model it includes: Interpolation space: this stage of the applicability
domain of the model holds only for chemicals for which an additional COREPA model is required. It
estimates the position of the target chemicals in the population density plot built in the parametric sp
ace defined by the explanatory variables of the model by making use the training set chemicals. Cur
rently, the accepted threshold of population density is 10%.
The mechanistic domain is applied on the parent structures and on their metabolites.
- Appropriate measures of goodness-of-fit and robustness and predictivity:
External Validation: For substances in the applicability domain, a predictivity of 100% was found for
100 industrial chemicals for the distinction of non-sensitizers versus sensitizers of GHS Category 1.
The evaluation has been published in W. Teubner, A. Mehling, P.X. Schuster, K.Guth, B. A. Worth,
J. Burton, B. van Rawenzwaay, R. Landsiedel: Computer models versus reality: How well do in silico
models currently predict the sensitization potential of a substance, Regulatory Toxicology and Pha
rmacology 67 (2013) 468-485
Statistics for goodness-of-fit: For 875 chemicals, the TIMES-SS model was able to predict correctly
90% of the strong sensitizers, 55% of the weak sensitizers and 77% of the non-sensitizers, i.e., an
overall performance of 78 %. Sensitivity: 78 %, Specificity: 77 %
- Mechanistic interpretation:
The TIMES-SS (Tissue Metabolism Simulator for skin sensitization) model integrates a simulator of
skin metabolism together with a number of “local” QSAR models for assessing the reactivity of spec
ific alerts. A skin metabolism simulator was developed based on empirical and theoretical knowledge
(not enough reported observed skin metabolism data). The transformation probabilities (defining th
e priority of their execution) were parameterized to reproduce skin sensitization data. The simulat
or comprises of about 420 transformations, which can be divided into four main types: abiotic trans
formations, covalent interaction with proteins, Phase I and Phase II reactions. Autoxidation (AU) of
chemical is also accounted for. Interactions with skin proteins are grouped into three types: leading to
strong or weak skin sensitization effect and interactions requiring QSAR models to quantify the potency of sensitization
of the alerting groups. The QSAR models were developed by the COmmon PAttern Recognition
(COREPA) approach [3]. The skin sensitization model predicts skin sensitization effect in three classes:
strong, weak and non-sensitizers. Reliability of alerts in the TIMES-SS model has been also evaluated to provide transparent me
chanistic reasoning for predicting sensitization potential. Alert performance was defined as the ratio
between the number of correct (positive and negative) predictions and the total number of chemicals
within the local training set that triggered the alert. The alert performance was assessed based on the
predictions on parents, autoxidation products simulated by the external AU simulator and metabolites
as simulated by the skin metabolism simulator embedded in TIMES-SS model. Four different categor
ies of reliability were defined: High reliability – alert performance higher than 60% and more than 5 chemical in local (transformatio
n/alert) training set Low reliability – performance less than 60% and more than 5 chemicals in training set
Undetermined reliability – less than 5 chemicals in training set Undetermined (theoretical) – there are no chemicals supporting the alert in the local training set

5. APPLICABILITY DOMAIN
- Descriptor domain:
Log(Kow): range = [ -13.2 .. 15.4 ]
calculated: 3.94 (In domain)
MOL._WEIGHT: range = [ 30 .. 738 ]Da
calculated: 134Da (In domain)
--> Conclusion: The chemical fulfils the general properties requirements.
- Structural fragment domain: The following ACF are identified: Fragments in correctly predicted
training chemicals – 100.00%, Fragments in non-correctly predicted training chemicals – 0.00%,
Fragments not present in the training chemicals – 0.00%
--> Conclusion: The chemical is in the interpolation structural space
- Mechanistic domain: Interpolation space
- Similarity with analogues in the training set: not reported

6. ADEQUACY OF THE RESULT
The substance falls in the applicability domain of the model. The model was found to give reliable
predictions for industrial chemicals. It is therefore considered to be acceptable for REACH.

Data source

Reference
Reference Type:
other company data
Title:
Unnamed
Year:
2020
Report date:
2020

Materials and methods

Test guideline
Qualifier:
according to guideline
Guideline:
other: REACH guidance on QSARs R.6, May/July 2008
Principles of method if other than guideline:
TIMES-SS v.2.27.19.13 - Skin sensitization with autoxidation v.21.26 (structure-toxicity and structure-metabolism relationships)
GLP compliance:
no

Test material

1
Chemical structure
Reference substance name:
3,3'-oxybis(ethyleneoxy)bis(propylamine)
EC Number:
224-207-2
EC Name:
3,3'-oxybis(ethyleneoxy)bis(propylamine)
Cas Number:
4246-51-9
Molecular formula:
C10H24N2O3
IUPAC Name:
3,3'-[oxybis(ethane-2,1-diyloxy)]dipropan-1-amine

Results and discussion

In vitro / in chemico

Results
Key result
Remarks on result:
positive indication of skin sensitisation
Other effects / acceptance of results:
The chmical fulfills the general properties requirements
The chemical is in the interpolation structural space
Mechanistic domain: Out of domain

Applicant's summary and conclusion

Interpretation of results:
Category 1 (skin sensitising) based on GHS criteria
Conclusions:
The QSAR program calculated a weak sensitization potential of the test substance.
Executive summary:

The registrant considers this predication as valid because TIMES-SS was validated with 100 substances from the registrant's portfolio (Teubner et al., Regulatory Toxicology and Pharmacology 67 (2013) 468–485). All predictions that fullfilled all domain requirements were correct (Specificity 100%).

The QSAR program calculated a weak sensitization potential of the test substance. The chemical is not entirely in domain of the system (mechanistic domain: out of domain).