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Partition coefficient

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Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
Study period:
08-02-2018
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:
See the attached justification
Qualifier:
according to guideline
Guideline:
other: REACH Guidance QSARs R.6
Version / remarks:
2008
Principles of method if other than guideline:
The model is based on the atom/fragment contribution theory
GLP compliance:
no
Specific details on test material used for the study:
Smile: C1=C([N+](=C(N=C1Cl)N)[O-])N
Key result
Type:
log Pow
Partition coefficient:
ca. 0.46
Remarks on result:
other: QSAR prediction
Details on results:
KOWWIN predicted that, taking into account the structure of the target substance, its log Kow is equal to 0.46.
Conclusions:
KOWWIN predicted that, taking into account the structure of the target substance, its log Kow is equal to 0.46.
Executive summary:

The Kow of the test item was predicted using EPÏ Suite software v.4.11 (2012). KOWWIN predicted that the test item (smile based prediction) has a log Kow of 0.46. The prediction is considered reliable, as the test item is inside the applicability domain of the model.

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
08-02-2018
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:
See the attached justification
Principles of method if other than guideline:
The model is a consensus model based on two components, ALogP and MLogP.• ALogP is the Ghose-Crippen-Viswanadhan LogP and consists of a regression equation based on the hydrophobicity contribution of 120 atom types (Ghose AK, Crippen, 1986, 1987; Viswanadhan et al., 1989).• MLogP is the Moriguchi LogP and consists of a regression equation based on 13 structural parameters (Moriguchi et al., 1992).
GLP compliance:
no
Specific details on test material used for the study:
Smile: C1=C([N+](=C(N=C1Cl)N)[O-])N
Key result
Type:
log Pow
Partition coefficient:
ca. 0.18
Remarks on result:
other: QSAR prediction
Details on results:
VEGA predicted that, taking into account the structure of the target substance, its log Kow is equal to 0.18.
Conclusions:
VEGA predicted that, taking into account the structure of the target substance, its log Kow is equal to 0.18.
Executive summary:

The Kow of the test item was predicted using VEGA v.1.0.4. VEGA predicted that the test item (smile based prediction) has a log Kow of 0.18. The prediction is considered reliable, as the test item is inside the applicability domain of the model.

Description of key information

A WOE approach is applied for estimating the log Kow of the test item. 2 QSAR predictions are performed (SMILE based prediction), using EPI Suite (KOWWIN) and VEGA (LogP). For both QSAR, the test item is considered into the applicability domain of the model. The log Kow of the test item is predicted to be equal to 0.46 and 0.18, by KOWWIN and LogP, respectively. As a consequence, based on both QSAR predictions, the log Kow of the test item is considered equal to 0.32 (mean value of both prediction).

Key value for chemical safety assessment

Log Kow (Log Pow):
0.32
at the temperature of:
25 °C

Additional information