p-benzoquinone dioxime

Adsorption / desorption

Link to relevant study record(s)

Reference

Reference 1

Endpoint:

adsorption / desorption: screening

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

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:

1. SOFTWARE
Estimation Programme Interface (EPI) Suite programme for Microsoft Windows v4.11
Contact EPISuite:
U.S. Environmental Protection Agency
1200 Pennsylvania Ave.
N.W. (Mail Code 7406M)
Washington, DC 20460

2. MODEL (incl. version number)
KOCWIN v2.00
September 2010 (model development); November 2012 (model publication)

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
See QPRF attached: ‘QPRF Title: Substance: 1,4-benzoquinone dioxime using the model KOCWIN v2.00 for the endpoint: Soil Adsorption Coefficient (Koc)’ version 1.0; dated 14 May 2018.

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
Full details of the method are provided in the attached QMRF named ‘QMRF Title: KOCWIN v2.00: Soil Adsorption Coefficient (Koc)’ version 1.0; 14 May 2018.

5. APPLICABILITY DOMAIN
See ‘any other information on results incl. tables’.
See QPRF attached: ‘QPRF Title: Substance: 1,4-benzoquinone dioxime using the model KOCWIN v2.00 for the endpoint: Soil Adsorption Coefficient (Koc)’ version 1.0; dated 14 May 2018.

6. ADEQUACY OF THE RESULT
1) QSAR model is scientifically valid. 2) The substance falls within the applicability domain of the QSAR model. 3) The prediction is fit for regulatory purpose.
The prediction is adequate contributing information to the environmental fate and transport and distribution assessment of the substance. The prediction is also supporting information for the Classification and Labelling or risk assessment of the substance as indicated in REACH Regulation (EC) 1907/2006: Annex XI Section 1.3. Specifically when combined with further information such as environmental toxicity and environmental fate testing.

Guideline:

other: REACH Guidance on QSARs R.6, May/July 2008

Principles of method if other than guideline:

Full details of the method are provided in the attached corresponding QMRF named ‘QMRF Title: KOCWIN v2.00: Soil Adsorption Coefficient (Koc)’ version 1.0; 14 May 2018.
- The model applies the following methodology to generate predictions:
(1) MCI model: first-order Molecular Connectivity Index with Fragment (group contribution) correction based QSAR; based on multiple linear-regression modelling
(2) Log Kow Regression mode: thermodynamic relationship model with Fragment (group contribution) correction based QSAR; based on multiple linear-regression modelling

- The model and the training and validation sets are published by US Environmental Protection Agency (USA).
The experimental Koc values in the training set and validation set were measured using one or more methods equivalent or similar to the following guidelines:
- HPLC method (OECD TG 121, 2001)
- Sediment and soil adsorption/desorption isotherm; screening method using three soil types (US EPA guideline OPPTS 835.1220, 1996)
- Batch equilibrium method (OECD TG 106, 2000)
- Leaching in Soil Columns method (Kd) (OECD TG 312, 2002)
- Simulation tests and direct field measurement (OECD Guidance Document 22, 2000)

Relevant EU (1992 as amended) may be also have been used where appropriate. It is understood that the core data of the training set would have been generated by non-HPLC method direct measurements of KOC. Additional data may have been subsequently added utilising estimates from the HPLC method in the model update from PCKOCWIN v1.0 to KOCWIN v2.0 and incorporation of Schuurmann et al. (2006) and other data.
- Justification of QSAR prediction: The result should be considered in relation to corresponding information presented and in accordance with the tonnage driven information requirements of REACH Regulation (EC) 1907/2006 in a weight of evidence.
In accordance with the tonnage driven information requirements: the calculated method for Log Koc has been adopted.
The calculated predictions are indicative of a substance of low adsorption potential:
Loc Koc in the range of 1.29.

Media:

soil

Type:

log Koc

Value:

ca. 1.29 dimensionless

pH:

7

Temp.:

25 °C

Matrix:

Soil

Type:

Koc

Value:

ca. 19.62 L/kg

pH:

7

Temp.:

25 °C

Matrix:

Soil

1. Defined Endpoint:

QMRF 2. Environmental Fate Parameters

QMRF 2.7. Adsorption/Desorption in soil

Reference to type of model used and description of results:

KOCWIN v2.00; integrated within the Estimation Programme Interface (EPI) Suite programme for Microsoft Windows v4.11; September 2010 (model development); November 2012 (model publication)

 

2. Description of results and assessment of reliability of the prediction:

The predicted values are provided within the QPRF attached: ‘QPRF Title: Substance: 1,4-benzoquinone dioxime using the model KOCWIN v2.00 for the endpoint: Soil Adsorption Coefficient (Koc)’ version 1.0; dated 14 May 2018.

 

KOCWIN v2.00 (model publication: November 2012)

All predictions are based on the KOCWIN v2.00: Log Kow Regression sub-model due to greater domain applicability than the MCI Regression sub-model. Further details are provided below.

 

Koc: ca. 19.62 L/Kg

Log Koc : ca. 1.29

 

It is noted by the applicant that the option of the KOCWIN v2.00 output of sub-models applicability: MCI regression and/or Log Kow regression is based on expert judgement. There are no transformations of units. The model programme is able to transform the units (Koc) to the coefficient of the logarithm scale (Log Koc). The result is then compared with the ranges of adsorption that are utilised in environmental fate modelling using expert systems. Additional criteria may apply if appropriate when interpreting the result for relevant endpoints. There is no universally acknowledged applicability domain for the model. However, assessment of the substance within the applicability domains recommended by the developers is documented within the corresponding QMRF named ‘QMRF Title: KOCWIN v2.00: Soil Adsorption Coefficient (Koc)’ version 1.0; 14 May 2018 – section 5; indicates the substance (constituents):

(i) All constituents fall within the Molecular Weight range domain.

(ii) There are no direct analogues (imine or hydroxy-imines) in the training (or validation) sets and there are no distinct hydroxy-imine correction factors in the MCI or log Kow regression methodologies. 1). There are nitro- and similar substances in the training and validation sets. Such substances are treated as nitrogen connected to non-fused aromatic ring (with correction factor coefficient; maximum occurrence: 2). There are quinones and anthraquinone(s) (multi-cyclics and/or aromatics) in the training set for the Log Koc regression with correction factor coefficient. Expert judgement indicates that there is limited domain applicability in the MCI model for the constituents (given no correction factor) which is indicated by examining the differences in the MCI predictions of the target versus 1,4-Dinitrosobenzene prediction (which uses the nitrogen connected to non-fused aromatic ring correction factor). From this the absence of correction factor places the target substance out of MCI sub model domain and is indicative of why the MCI model prediction apparently deviates so significantly from Kow Regression prediction. Within the Log Kow regression methodology domain as this primarily addresses the prediction by addressing the thermodynamic relationship between partitioning behaviour and the Koc. See QMRF section 4.2. Overall it would appear within the MCI sub-model due to the lack of correction factor and lack of imine and hydroxy-imine groups in the training set that the Log Kow regression model is a better model for the target substance as it has greater coverage of the target substance and its constituent fragments – implicit within the model training set. Expert judgement would indicate that the substance constituent are acceptably in the structural fragment domain of the Log Kow regression model. The input parameter is based upon the log Kow 1.49 (experimental citation within the PhysProp experimental database underpinning the model).

 

3. Uncertainty of the prediction and mechanistic domain:

The training set of the model has the following statistics and coefficients of determination:

MCI Methodology (no corrections, non-polar)

Training Set Statistics: number in dataset = 69 ; correlation coef (r2) = 0.967 ; standard deviation = 0.247 ; absolute deviation = 0.199

MCI Methodology (with corrections)

Training Set Statistics: number in dataset = 447 ; correlation coef (r2) = 0.900 ; standard deviation = 0.340 ; absolute deviation = 0.273

 

Log Kow to Log Koc Methodology (no corrections)

Training Set Statistics: number in dataset = 68 ; correlation coef (r2) = 0.877 ; standard deviation = 0.478; absolute deviation = 0.371

Log Kow to Log Koc Methodology (with corrections)

Training Set Statistics: number in dataset = 447 ; correlation coef (r2) = 0.855 ; standard deviation = 0.396 ; absolute deviation = 0.307

 

The combined training sets (of 516 substances) has the following statistics:

MCI Methodology

Total Training Set Statistics: number in dataset = 516 ; correlation coef (r2) = 0.916 ; standard deviation = 0.330 ; absolute deviation = 0.263

Log Kow to Log Koc Methodology

Total Training Set Statistics: number in dataset = 516 ; correlation coef (r2) = 0.860 ; standard deviation = 0.429 ; absolute deviation = 0.321

 

The model has been externally validated on a set of 158 (or 150) substances and the following statistics and coefficients of determination are presented:

Validation Set Statistics - MCI Methodology:

number in dataset = 158 ; correlation coef (r2) = 0.850 ; standard deviation = 0.583 ; absolute deviation = 0.459

Validation Set Statistics - Log Kow Methodology:

number in dataset = 150 ; correlation coef (r2) = 0.778 ; standard deviation = 0.679 ; absolute deviation = 0.494

 

Data for the training set are available via external validation (see attached QMRF prepared by the applicant for full citations).

The model is based on the thermodynamic relationship between surrogates chemical structure (group contribution) fragments and their chemical activity from first order molecular connectivity (surface area) indices and separately thermodynamic relationship with physicochemical properties, specifically correlation with n-octanol/water partitioning coefficients and substructure correction. In order to improve the model additional substances could be added to the model; new fragments and substructure corrections introduced. The model is non-proprietary and the training sets and validation sets can be downloaded from the internet. A summary of this information is presented by the applicant. For the substance and consideration of the structural fragment domain it is considered that the Log Kow Regression sub-model had better domain applicability than MCI Regression sub-model.

Validity criteria fulfilled:

yes

Conclusions:

The results are adequate for the for the regulatory purpose.

Executive summary:

KOCWIN v2.00 (model publication: November 2012)

All predictions are based on the KOCWIN v2.00: Log Kow Regression sub-model due to greater domain applicability than the MCI Regression sub-model.

Koc: ca. 19.62 L/Kg

Log Koc : ca. 1.29

 

Adequacy of the QSAR:

1) QSAR model is scientifically valid. 2) The substance falls within the applicability domain of the QSAR model. 3) The prediction is fit for regulatory purpose.

The prediction is adequate contributing information to the environmental fate and transport and distribution assessment of the substance. The prediction is also supporting information for the Classification and Labelling or risk assessment of the substance as indicated in REACH Regulation (EC) 1907/2006: Annex XI Section 1.3. Specifically when combined with further information such as environmental toxicity and environmental fate testing.

Reference 2

Endpoint:

adsorption / desorption: screening

Data waiving:

other justification

Justification for data waiving:

the study does not need to be conducted because the substance has a low octanol water partition coefficient and the adsorption potential of this substance is related to this parameter

the study does not need to be conducted because the physicochemical properties of the substance indicate that it can be expected to have a low potential for adsorption

other:

Justification for type of information:

JUSTIFICATION FOR DATA WAIVING
In accordance with REACH Regulation (EC) No. 1907/2006 Annex VIII, column 2 section 9.3.1 the study does not need to be conducted based on structural assessment of the substance and measured physicochemical and environmental fate properties. The substance constituents do not contain functional groups associated with ionisation potential in environmentally relevant pH ranges (reference: Anon., Log Kow HPLC study, OECD TG 117, 2018) and is not predicted to be surface active. The substance has a measured logarithmic n-octanol/water partition coefficient: << 3.0. On this basis it can therefore can be expected to have a low potential for adsorption. The applicant provides a calculated value of Log Koc as supporting information for environmental fate modelling and demonstrating low adsorption potential. According to ECHA Guidance on Information Requirements and Chemical Safety Assessment (Chapter R.7a: Endpoint Specific Guidance, R.7.1.15, July 2017 and Chapter R.7b: Endpoint Specific Guidance, June 2017) the study does not need to be conducted.

Description of key information

Log Koc, soil: ca. 1.29, at 25 °C; ca. pH 7, QSAR Prediction - KOCWIN v2.00, 2018

Key value for chemical safety assessment

Koc at 20 °C:

19.62

Additional information

In accordance with REACH Regulation (EC) No. 1907/2006 Annex VIII, column 2 section 9.3.1 the study does not need to be conducted based on structural assessment of the substance and measured physicochemical and environmental fate properties. The substance constituents do not contain functional groups associated with ionisation potential in environmentally relevant pH ranges (reference: Anon., Log Kow HPLC study, OECD TG 117, 2018) and is not predicted to be surface active. The substance has a measured logarithmic n-octanol/water partition coefficient: << 3.0. On this basis it can therefore can be expected to have a low potential for adsorption. The applicant provides a calculated value of Log Koc as supporting information for environmental fate modelling and demonstrating low adsorption potential. According to ECHA Guidance on Information Requirements and Chemical Safety Assessment (Chapter R.7a: Endpoint Specific Guidance, R.7.1.15, July 2017 and Chapter R.7b: Endpoint Specific Guidance, June 2017) the study does not need to be conducted.

SAR Predictions KOCWIN v2.00 model, 2018 –

KOCWIN v2.00 (model publication: November 2012)

All predictions are based on the KOCWIN v2.00: Log Kow Regression sub-model due to greater domain applicability than the MCI Regression sub-model.

Koc: ca. 19.62 L/Kg

Log Koc : ca. 1.29

 

Adequacy of the QSAR:

1) QSAR model is scientifically valid. 2) The substance falls within the applicability domain of the QSAR model. 3) The prediction is fit for regulatory purpose.

The prediction is adequate contributing information to the environmental fate and transport and distribution assessment of the substance. The prediction is also supporting information for the Classification and Labelling or risk assessment of the substance as indicated in REACH Regulation (EC) 1907/2006: Annex XI Section 1.3. Specifically when combined with further information such as environmental toxicity and environmental fate testing.