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REACH

O,O,O-triphenyl phosphorothioate

EC number: 209-909-9 | CAS number: 597-82-0

Life Cycle description
Uses advised against

Environmental fate & pathways

Bioaccumulation: aquatic / sediment

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Administrative data

Link to relevant study record(s)

Reference 1

Endpoint:: bioaccumulation: aquatic / sediment
Type of information:: (Q)SAR
Adequacy of study:: weight of evidence
Reliability:: 2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:: other: Scientifically accepted calculation method; substance is within the parametric and mechanistic domains, not the structural domain of the model.
Justification for type of information:: QMRF: section ‘Overall remarks, attachments’ (‘Overall remarks’)
QPRF: section ‘Applicant’s summary and conclusion’ (‘Executive summary’)
Qualifier:: no guideline followed
Principles of method if other than guideline:: Calculation using Catalogic v.5.11.17, BCF base-line model v.02.09
GLP compliance:: no
Test organisms (species):: other: fish
Details on estimation of bioconcentration:: BASIS INFORMATION
- Measured/calculated logPow: experimental 5.0

BASIS FOR CALCULATION OF BCF
- Estimation software: BCF base-line model v02.09 of OASIS CATALOGIC v5.11.17
: Key result
Type:: BCF
Value:: 2 239 L/kg
Remarks on result:: other: Log BCF corrected = 3.35 ± 0.11; all mitigating factors applied.
Type:: BCF
Value:: 5 200 L/kg
Remarks on result:: other: Log BCF max. = 3.716; no mitigating factors applied.
Validity criteria fulfilled:: yes
Remarks:: Substance is within the parametric and mechanistic domains, not the structural domain of the model.
Conclusions:: The test substance is bioaccumulative (BCF > 2000 < 5000 kg/L)
Executive summary:: For QPRF see "Attached background material".

Reference 2

Endpoint:

bioaccumulation: aquatic / sediment

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

other: Scientifically accepted calculation method; but substance not within applicability domain of the model

Justification for type of information:

QMRF: section ‘Overall remarks, attachments’ (‘Overall remarks’)
QPRF: section ‘Applicant’s summary and conclusion’ (‘Executive summary’)

Qualifier:

no guideline followed

Principles of method if other than guideline:

The BCF is estimated based on several molecular descriptors. The applicability domain of predictions is assessed using an Applicability Domain Index (ADI) calculated by grouping several other indices, e.g. by a similarity index that consider molecule's fingerprint and structural aspects (count of
atoms, rings and relevant fragments).

GLP compliance:

Test organisms (species):

other: fish

Details on estimation of bioconcentration:

BASIS INFORMATION
- Measured/calculated logPow: calculated

BASIS FOR CALCULATION OF BCF
- Estimation software: VEGA Meylan v1.0.2
- Result based on calculated log Pow of: 7.12 (LogP as calculated by VEGA)

Type:

BCF

Value:

11 561 L/kg

Remarks on result:

other: log BCF = 4.06; According to the model’s global AD index, the predicted substance is out of the Applicability Domain of the model. An expert ananalysis can be found in chapter "Applicant’s summary and conclusion – Executive summary".

Validity criteria fulfilled:

Executive summary:

The BCF model (Meylan) v1.0.2 implemented in the VEGA platform v1.0.8: Estimation Domain (QPRF)

The applicability domain of predictions is assessed using an Applicability Domain Index (ADI) that has values from 0 (worst case) to 1 (best case). The ADI is calculated by grouping several other indices, each one taking into account a particular issue of the applicability domain. Most of the indices are based on the calculation of the most similar compounds found in the training and test set of the model, calculated by a similarity index that consider molecule's fingerprint and structural aspects (count of atoms, rings and relevant fragments). Note that when the experimental value for the given compound is found, the applicability domain indices are calculated only considering this value, without taking into account the first n similar compounds.

For each index, including the final ADI, three intervals for its values are defined, such that the first interval corresponds to a positive evaluation, the second one corresponds to a suspicious evaluation and the last one corresponds to a negative evaluation.

Following, all applicability domain components are reported along with their explanation and the intervals used. Furthermore, the specific index of the substance is given.

-Similar molecules with known experimental value.

This index takes into account how similar are the first two most similar compounds found. Values near 1 mean that the predicted compound is well represented in the dataset used to build the model, otherwise the prediction could be an extrapolation.

Defined intervals are:

1 ≥ index > 0.9	strongly similar compounds with known experimental value in the training set have been found
0.9 ≥ index > 0.75	only moderately similar compounds with known experimental value in the training set have been found
index ≤ 0.75	no similar compounds with known experimental value in the training set have been found

The substance has a similarity index of 0.935.

-Accuracy (average error) of prediction for similar molecules.

This index takes into account the error in prediction for the two most similar compounds found. Values near 0 mean that the predicted compounds falls in an area of the model's space where the model gives reliable predictions, otherwise the greater is the value, the worse the model behaves.

Defined intervals are:

index < 0.5	accuracy of prediction for similar molecules found in the training set is good
0.5 ≤ index ≤ 1.0	accuracy of prediction for similar molecules found in the training set is not optimal
index > 1.0	accuracy of prediction for similar molecules found in the training set is not adequate

The substance has an accuracy index of 0.31.

- Concordance with similar molecules (average difference between target compound prediction and experimental values of similar molecules).

This index takes into account the difference between the predicted value and the experimental values of the two most similar compounds. Values near 0 mean that the prediction made agrees with the experimental values found in the model's space, thus the prediction is reliable.

Defined intervals are:

index < 0.5	similar molecules found in the training set have experimental values that agree with the target compound predicted value
0.5 ≤ index ≤ 1.0	similar molecules found in the training set have experimental values that slightly disagree with the target compound predicted value
index > 1.0	similar molecules found in the training set have experimental values that completely disagree with the target compound predicted value

The substance has a concordance index of 1.668.

- Maximum error of prediction among similar molecules.

This index takes into account the maximum error in prediction among the two most similar compounds. Values near 0 means that the predicted compounds fall in an area of the model's space where the model gives reliable predictions without any outlier value.

Defined intervals are:

index < 0.5	the maximum error in prediction of similar molecules found in the training set has a low value, considering the experimental variability
0.5 ≤ index < 1.0	the maximum error in prediction of similar molecules found in the training set has a moderate value, considering the experimental variability
index ≥ 1.0	the maximum error in prediction of similar molecules found in the training set has a high value, considering the experimental variability

The substance has a max error index of 0.41.

- LogP reliability.

This index takes into account the reliability of the logP value used in the model. Note that the Meylan BCF model is strongly based on the logP prediction of the compound, thus this index is highly relevant for the assessment of the final prediction. The reliability of the logP value comes from the assessment of the VEGA LogP model (that provides the used logP value), which is also provided in the “Prediction summary” section of the report.

Defined intervals are:

index = 1	the maximum error in prediction of similar molecules found in the training set has a low value, considering the experimental variability
index = 0.7	the maximum error in prediction of similar molecules found in the training set has a moderate value, considering the experimental variability
index = 0	the maximum error in prediction of similar molecules found in the training set has a high value, considering the experimental variability

The substance has a LogP reliability index of 0.

- Model descriptors range check.

This index checks if the descriptors calculated for the predicted compound are inside the range of descriptors of the training and test set. The index has value 1 if all descriptors are inside the range, 0 if at least one descriptor is out of the range.

Defined intervals are:

index = 1	descriptors for this compound have values inside the descriptor range of the compounds of the training set
index = 0	descriptors for this compound have values outside the descriptor range of the compounds of the training set

The substance’ descriptors range check is 1.

- Global AD Index.

The final global index takes into account all the previous indices, in order to give a general global assessment on the applicability domain for the predicted compound.

Defined intervals are:

1 ≥ index > 0.85	predicted substance is into the Applicability Domain of the model
0.85 ≥ index > 0.75	predicted substance could be out of the Applicability Domain of the model
index ≤ 0.75	predicted substance is out of the the Applicability Domain of the model

The substance has a global AD index of 0.75.

Detailed expert analysis

With a global AD Index of 0.75, the substance is just outside the applicability domain of the model. This is due to the fact that: 1. similar molecules found in the training set have experimental values that strongly disagree with the target compound predicted value; 2. reliability of logP value used by the model is not adequate.

For "Structure A" an experimentally determined log Kow value of 4.8 -5.0 is available. This value can however not be used as input in the model (as is the case with e.g. BCFBAF). Therefore, the estimated log Kow value of 7.12 used in the VEGA Meylan BCF prediction should indeed be considered as not adequate. The Meylan BCF model is strongly based on the log Kow prediction of the compound and reaches maximum values at a log Kow of 7. The estimated BCF value based on a log Kow of 7.12 will thus be significantly overestimated. Therefore, the confidence in the predicted BCF values is considered to be low.

References:

VEGA Guide to BCF Meylan Model version 1.0.2 implemented in the VEGA tool v1.0.8.

Reference 3

Endpoint:

bioaccumulation: aquatic / sediment

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

other: see 'Remark'

Remarks:

Methods were validated by US EPA using statistical external validation. Scientifically accepted calculation method; substance within applicability domain of the model. However, based on the mean absolute error (MAE), the confidence in the predicted BCF values is low.

Justification for type of information:

QMRF: section ‘Overall remarks, attachments’ (‘Overall remarks’)
QPRF: section ‘Applicant’s summary and conclusion’ (‘Executive summary’)

Qualifier:

no guideline followed

Principles of method if other than guideline:

T.E.S.T. is a toxicity estimation software tool. The program requires only the molecular structure of the test item, all other molecular descriptors which are required to estimate the toxicity are calculated within the tool itself. The molecular descriptors describe physical characteristics of the molecule (e.g. E-state values and E-state counts, constitutional descriptors, topological descriptors, walk and path counts, connectivity, information content, 2d autocorrelation, Burden eigenvalue, molecular property (such as the octanol-water partition coefficient), Kappa, hydrogen bond acceptor/donor counts, molecular distance edge, and molecular fragment counts). Each of the available methods uses a different set of these descriptors to estimate the toxicity.
The bioaccumulation factor (BCF) was estimated using several available methods: hierarchical clustering method; FDA method, single model method; group contribution method; nearest neighbor method; consensus method. The methods were validated using statistical external validation using separate training and test data sets.
The experimental data set was obtained from several different databases (Dimitrov et al., 2005; Arnot and Gobas, 2006; EURAS; Zhao, 2008). From the available data set salts, mixtures and ambiguous compounds were removed. The final data set contained 676 chemicals.

References:
- Dimitrov, S., N. Dimitrova, T. Parkerton, M. Combers, M. Bonnell, and O. Mekenyan. 2005. Base-line model for identifying the bioaccumulation potential of chemicals. SAR and QSAR in Environmental Research 16:531-554.
- Arnot, J.A., and F.A.P.C. Gobas. 2006. A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in aquatic organisms. Environ. Rev. 14:257-297.
- EURAS. Establishing a bioconcentration factor (BCF) Gold Standard Database. EURAS [cited 5/20/09]. Available from http://www.euras.be/eng/project.asp?ProjectId=92.
- Zhao, C.; Boriani, E.; Chana, A.; Roncaglioni, A.; Benfenati, E. 2008. A new hybrid system of QSAR models for predicting bioconcentration factors (BCF). Chemosphere 73:1701-1707.

GLP compliance:

Test organisms (species):

other: fish

Details on test conditions:

BASIS FOR CALCULATION OF BCF
- Estimation software: US EPA T.E.S.T. v4.1

Applied estimation methods:
- Hierarchical clustering
- FDA
- Single model
- Group contribution
- Nearest neighbor
- Consensus

Key result

Type:

BCF

Value:

215.58 dimensionless

Remarks on result:

other: method: consensus (average of reasonable results from all models); log BCF = 2.33; The substance is within the applicability domain of the Consensus method. Based on the mean absolute error, the confidence in the predicted BCF values is low.

MODEL DETAILS:

Method	Predicted value		Model statistics			MAE (in log10)
	Predicted value		Model statistics			External test set		Training set
	Log BCF	BCF	r2	q2	No. of chemicals	Entire set	SC ≥ 0.5	Entire set	SC ≥ 0.5
Consensus method	2.33	215.58	-	-	-	0.51	1.00	0.42	0.42
Hierarchical clustering	3.10	1,271.17 (508.15-3179.93)	0.662 - 0.941	0.569 - 0.911	22 - 540 (cluster models: 7)	0.54	1.12	0.23	0.18
Single model	2.56	362.00 (27.17-4823.64)	0.764	0.733	540	0.54	1.00	0.53	0.52
Group contribution	2.10	124.85 (5.02-3107.64)	0.719	0.527	499	0.62	1.12	0.60	0.63
FDA	1.70	49.74 (13.19-187.54)	0.880	0.771	30	0.57	0.82	0.53	0.44
Nearest neighbour	2.21	162.92	-	-	3	0.60	1.13	0.55	0.63

LEGEND:

MAE = mean absolute error

SC = similarity coefficient

r² = correlation coefficient

q² = leave one out correlation coefficient

Validity criteria fulfilled:

yes

Executive summary:

QPRF: Estimation of bioaccumulation in fish using T.E.S.T. v4.1

Substance

See “Test material identity”

General information

2.1

Date of QPRF

See “Data Source (Reference)”

2.2

QPRF author and contact details

See “Data Source (Reference)”

Prediction

3.1

Endpoint
(OECD Principle 1)

Endpoint

Bioaccumulation (aquatic)

Dependent variable

Bioconcentration factor (BCF)

3.2

Algorithm
(OECD Principle 2)

Model or submodel name

US EPA T.E.S.T. v4.1:

1) Hierarchical clustering

2) FDA method

3) Single model

4) Group contribution

5) Nearest neighbour

6) Consensus

Model version

v. 4.1

Reference to QMRF

Estimation of bioaccumulation in fish using T.E.S.T. v4.1

Predicted value (model result)

See “Results and discussion”

Input for prediction

Chemical structure via CAS number, SMILES, MDL molfile, structure (drawing)

Descriptor values

Molecular descriptors (calculated by T.E.S.T.)

3.3

Applicability domain
(OECD principle 3)

General remarks

Predictions are considered only from valid models. Models which do not meet the constraints are listed in the output with a corresponding remark. If the substance is not within the applicability domain, no BCF is calculated.

Hierarchical clustering

In domain

FDA method

In domain

Single model

In domain

Group contribution

In domain

Nearest neighbour

In domain

Consensus

In domain

3.4

The uncertainty of the prediction
(OECD principle 4)

The uncertainty of the predictions can be assessed by comparing the mean absolute error (MAE) of the entire dataset with the MAE of the dataset restricted to substances with a similarity coefficient (SC) of ≥ 0.5. If the MAE for the entire set is lower than the MAE for the similar substances (SC ≥ 0.5), the confidence in the predicted BCF value is high.

The table below lists the information on q² (leave one out correlation coefficient), r² (correlation coefficient), MAE and SC of the models.

Based on the MAE of the external and the training dataset, the confidence in the estimated BCF is assessed as follows.

Model	Confidence in estimated BCF
Model	External test set:	Training set:
Consensus method	low	high
Hierarchical clustering	low	high
Single model	low	high
Group contribution	low	low
FDA	low	high
Nearest neighbor	low	low

3.5

The chemical mechanisms according to the model underpinning the predicted result
(OECD principle 5)

Molecular descriptors are used to develop the models. The overall pool of descriptors in the software contain 797 2-dimensional descriptors of the following classes: E-state values and E-state counts, constitutional descriptors, topological descriptors, walk and path counts, connectivity, information content, 2d autocorrelation, Burden eigenvalue, molecular property (such as the octanol-water partition coefficient), Kappa, hydrogen bond acceptor/donor counts, molecular distance edge, and molecular fragment counts. The descriptors used to describe the compound can be viewed in the model output details.

Detailed information on q²(leave one out correlation coefficient), r²(correlation coefficient), MAE and SC:

see 'Any other information on results incl. tables'

Reference 4

Endpoint:

bioaccumulation: aquatic / sediment

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

other: Scientifically accepted calculation method; substance within applicability domain of the model

Justification for type of information:

QMRF: section ‘Overall remarks, attachments’ (‘Overall remarks’)
QPRF: section ‘Applicant’s summary and conclusion’ (‘Executive summary’)

Qualifier:

no guideline followed

Principles of method if other than guideline:

Calculation using BCFBAF (v3.01)

GLP compliance:

Details on estimation of bioconcentration:

BASIS INFORMATION
- Measured/calculated logPow: measured

BASIS FOR CALCULATION OF BCF
- Estimation software: EPISuite-BCFBAF (version 3.01)
- Result based on measured log Pow of: 5.00 (BASF SE, 2013)

Key result

Type:

BCF

Value:

925 L/kg

Remarks on result:

other: log BCF: 2.97, the substance is within the applicability domain of the BCFBAF submodel: Bioconcentration factor (BCF; Meylan et al., 1997/1999)

Key result

Type:

BCF

Value:

643 L/kg

Calculation basis:

steady state

Remarks on result:

other: log BCF 2.8; Upper trophic, incl. biotransformation estimates; The substance is within the applicability domain of the BCFBAF submodel: Arnot&Gobas BAF and steady state BCF Arnot&Gobas, 2003)

Type:

BCF

Value:

7 882

Calculation basis:

steady state

Remarks on result:

other: log BCF 3.9, Upper trophic, incl. biotransformation rate of zero; The substance is within the applicability domain of the BCFBAF submodel: Arnot&Gobas BAF and steady state BCF Arnot&Gobas, 2003)

Key result

Type:

BAF

Value:

652

Remarks on result:

other: log BAF 2.8; Upper trophic, incl. biotransformation estimates; The substance is within the applicability domain of the BCFBAF submodel: Arnot&Gobas BAF and steady state BCF Arnot&Gobas, 2003)

Type:

BAF

Value:

107 900

Remarks on result:

other: log BAF 5.08; Upper trophic, incl. biotransformation rate of zero; The substance is within the applicability domain of the BCFBAF submodel: Arnot&Gobas BAF and steady state BCF Arnot&Gobas, 2003)

Details on kinetic parameters:

Biotransformation half-life (days): 1.669
Biotransformation rate (kM, normalised to 10g fish at 15°C: 0.4153
The substance is within the applicability domain of the BCFBAF submodel: Biotransformation rate in fish (kM; Arnot et al., 2008a/b)

Summary Results:

Log BCF (regression-based estimate): 2.97 (BCF = 925 L/kg wet-wt)

Biotransformation Half-Life (days) : 1.67 (normalized to 10 g fish)

Log BAF (Arnot-Gobas upper trophic): 2.81 (BAF = 652 L/kg wet-wt)

Log Kow (estimated) : 6.47

Log Kow (experimental): not available from database

Log Kow used by BCF estimates: 5.00 (user entered)

Equation Used to Make BCF estimate:

Log BCF = 0.6598 log Kow - 0.333 + Correction

Correction(s): Value

No Applicable Correction Factors

Estimated Log BCF = 2.966 (BCF = 924.7 L/kg wet-wt)

Whole body primary biotransformation rate estimate for fish:

Type	Num	Log Biotransformation Fragment Description	Coeff.	Value
Frag	3	Unsubstituted phenyl group (C6H5-)	-0.6032	-1.8096
Frag	1	Phosphate ester (P=S type)	0.1978	0.1978
Frag	15	aromatic-H	0.2664	3.9957
Frag	3	benzene	-0.4277	-1.2832
Lkow	*	Log Kow = 5.00 (user-entered)	0.3073	1.5367
Molwt	*	Molecular weight parameter		-0.8779
Const	*	Equation constant		-1.5371
Result	Log bio half-life (days)			0.2224
Result	Bio half-life (days)			1.669

Note: Bio Half-Life Normalized to 10 g fish at 15 °C

Biotransformation Rate Constant:

kM (Rate Constant): 0.4153 /day (10 gram fish)

kM (Rate Constant): 0.2336 /day (100 gram fish)

kM (Rate Constant): 0.1313 /day (1 kg fish)

kM (Rate Constant): 0.07386 /day (10 kg fish)

Arnot-Gobas BCF & BAF Methods (including biotransformation rate estimates):

Estimated Log BCF (upper trophic) = 2.808 (BCF = 642.6 L/kg wet-wt)

Estimated Log BAF (upper trophic) = 2.814 (BAF = 651.9 L/kg wet-wt)

Estimated Log BCF (mid trophic) = 2.918 (BCF = 827.5 L/kg wet-wt)

Estimated Log BAF (mid trophic) = 2.963 (BAF = 918.6 L/kg wet-wt)

Estimated Log BCF (lower trophic) = 2.947 (BCF = 884.4 L/kg wet-wt)

Estimated Log BAF (lower trophic) = 3.083 (BAF = 1211 L/kg wet-wt)

Arnot-Gobas BCF & BAF Methods (assuming a biotransformation rate of zero):

Estimated Log BCF (upper trophic) = 3.897 (BCF = 7882 L/kg wet-wt)

Estimated Log BAF (upper trophic) = 5.033 (BAF = 1.079e+005 L/kg wet-wt)

Validity criteria fulfilled:

yes

Conclusions:

Considering biotransformation processes, the test substance is bioaccumulative (BCF > 2000 < 5000 kg/L)

Executive summary:

QPRF: BCFBAF v3.01

1.	Substance	See “Test material identity”
2.	General information
2.1	Date of QPRF	See “Data Source (Reference)”
2.2	QPRF author and contact details	See “Data Source (Reference)”
3.	Prediction
3.1	Endpoint (OECD Principle 1)	Endpoint	Bioaccumulation (aquatic)
3.1	Endpoint (OECD Principle 1)	Dependent variable	- Bioconcentration factor (BCF) - Bioaccumulation factor (BAF; 15 °C) - Biotransformation rate (kM) and half-life
3.2	Algorithm (OECD Principle 2)	Model or submodel name	BCFBAF Submodels: 1) Bioconcentration factor (BCF; Meylan et al., 1997/1999) 2) Biotransformation rate in fish (kM; Arnot et al., 2008a/b) 3) Arnot & Gobas BAF and steady-state BCF Arnot & Gobas, 2003)
		Model version	v. 3.01
		Reference to QMRF	Estimation of Bioconcentration, bioaccumulation and biotransformation in fish using BCFBAF v3.01 (EPI Suite v4.11)
		Predicted value (model result)	See “Results and discussion”
		Input for prediction	Chemical structure via CAS number or SMILES; log Kow (optional)
		Descriptor values	- SMILES: structure of the compound as SMILES notation - log Kow - Molecular weight
3.3	Applicability domain (OECD principle 3)	Domains:
		1) Bioconcentration factor (BCF; Meylan et al., 1997/1999)
		a) Ionic/non-Ionic	The substance is non-ionic.
		b) Molecular weight (range of test data set): - Ionic: 68.08 to 991.80 - Non-ionic: 68.08 to 959.17 (On-Line BCFBAF Help File, Ch. 7.1.3 Estimation Domain and Appendix G)	The substance is within range (342.35 g/mol).
		c) log Kow (range of test data set): - Ionic: -6.50 to 11.26 - Non-ionic: -1.37 to 11.26 (On-Line BCFBAF Help File, Ch. 7.1.3 Estimation Domain and Appendix G)	The substance is within range (5.0).
		d) Maximum number of instances of correction factor in any of the training set compounds (On-Line BCFBAF Help File, Appendix E)	Not applicable as correction factors were not used.
		2) Biotransformation rate in fish (kM; Arnot et al., 2008a/b)
		a) The substance does not appreciably ionize at physiological pH. (On-Line BCFBAF Help File, Ch. 7.2.3)	Fulfilled
		b) Molecular weight (range of test data set): 68.08 to 959.17 (On-Line BCFBAF Help File, Ch. 7.2.3)	The substance is within range (342.35 g/mol).
		c) The molecular weight is ≤ 600 g/mol. (On-Line BCFBAF Help File, Ch. 7.2.3)	Fulfilled
		d) Log Kow: 0.31 to 8.70 (On-Line BCFBAF Help File, Ch. 7.2.3)	The substance is within range (5.0).
		e) The substance is no metal or organometal, pigment or dye, or a perfluorinated substance. (On-Line BCFBAF Help File, Ch. 7.2.3)	Fulfilled
		f) Maximum number of instances of biotransformation fragments in any of the training set compounds (On-Line BCFBAF Help File, Appendix F)	Not exceeded.
		3) Arnot & Gobas BAF and steady-state BCF Arnot & Gobas, 2003)
		a) Log Kow ≤ 9 (On-Line BCFBAF Help File, Ch. 7.3.1)	Fulfilled
		b) The substance does not appreciably ionize. (On-Line BCFBAF Help File, Ch. 7.3.1)	Fulfilled
		c) The substance is no pigment, dye, or perfluorinated substance. (On-Line BCFBAF Help File, Ch. 7.3.1)	Fulfilled
3.4	The uncertainty of the prediction (OECD principle 4)	1. Bioconcentration factor (BCF; Meylan et al., 1997/1999) Statistical accuracy of the training data set (non-ionic plus ionic data): - Correlation coefficient (r²) = 0.833 - Standard deviation = 0.502 log units - Absolute mean error = 0.382 log units 2. Biotransformation Rate in Fish (kM) Statistical accuracy (training set): - Correlation coefficient (r²) = 0.821 - Correlation coefficient (Q²) = 0.753 - Standard deviation = 0.494 log units - Absolute mean error = 0.383 log units 3. Arnot-Gobas BAF/BCF model No information on the statistical accuracy given in the documentation.
3.5	The chemical mechanisms according to the model underpinning the predicted result (OECD principle 5)	1. The BCF model is mainly based on the relationship between bioconcentration and hydrophobicity. The model also takes into account the chemical structure and the ionic/non-ionic character of the substance. 2. Bioaccumulation is the net result of relative rates of chemical inputs to an organism from multimedia exposures (e.g., air, food, and water) and chemical outputs (or elimination) from the organism. 3. The model includes mechanistic processes for bioconcentration and bioaccumulation such as chemical uptake from the water at the gill surface (BCFs and BAFs) and the diet (BAFs only), and chemical elimination at the gill surface, fecal egestion, growth dilution and metabolic biotransformation (Arnot and Gobas 2003). Other processes included in the calculations are bioavailability in the water column (only the freely dissolved fraction can bioconcentrate) and absorption efficiencies at the gill and in the gastrointestinal tract.

References

- Arnot JA, Gobas FAPC. 2003. A generic QSAR for assessing the bioaccumulation potential of organic chemicals in aquatic food webs. QSAR and Combinatorial Science 22: 337-345.

- Arnot JA, Mackay D, Parkerton TF, Bonnell M. 2008a. A database of fish biotransformation rates for organic chemicals. Environmental Toxicology and Chemistry 27(11), 2263-2270.

- Arnot JA, Mackay D, Bonnell M. 2008b. Estimating metabolic biotransformation rates in fish from laboratory data. Environmental Toxicology and Chemistry 27: 341-351.

- Meylan, W.M., Howard, P.H, Aronson, D., Printup, H. and S. Gouchie. 1997. "Improved Method for Estimating Bioconcentration Factor (BCF) from Octanol-Water Partition Coefficient", SRC TR-97-006 (2nd Update), July 22, 1997; prepared for: Robert S. Boethling, EPA-OPPT, Washington, DC; Contract No. 68-D5-0012; prepared by: ; Syracuse Research Corp., Environmental Science Center, 6225 Running Ridge Road, North Syracuse, NY 13212.

- Meylan, WM, Howard, PH, Boethling, RS et al. 1999. Improved Method for Estimating Bioconcentration / Bioaccumulation Factor from Octanol/Water Partition Coefficient. Environ. Toxicol. Chem. 18(4): 664-672 (1999).

- US EPA (2012). On-Line BCFBAF Help File. .

Identified Correction Factors (Appendix E)

No Applicable Correction Factors

Biotransformation Fragments and Coefficient values (Appendix F)

Fragment Description	Coefficient value	No. compounds containing fragment in total training set	Maximum number of each fragment in any individual compound	No. of instances of each fragment for the current substance
Unsubstituted phenyl group (C6H5-)	-0.60319946	47	3	3
Phosphate ester (P=S type)	0.19779672	18	1	1
Aromatic-H	0.26637806	305	15	15
Benzene	-0.427728	197	3	3

Assessment of Applicability Domain Based on Molecular Weight and log Kow

1. Bioconcentration Factor (BCF; Meylan et al., 1997/1999)

Training set: Molecular weights	Ionic	Non-ionic
Minimum	68.08	68.08
Maximum	991.80	959.17
Average	244.00	244.00
Assessment of molecular weight	Molecular weight within range of training set
Training set: Log Kow	Ionic	Non-ionic
Minimum	-6.50	-1.37
Maximum	11.26	11.26
Assessment of log Kow	Log Kow within range of training set.

2. Biotransformation Rate in Fish (kM; Arnot et al., 2008a/b)

Training set: Molecular weights
Minimum	68.08
Maximum	959.17
Average	259.75
Assessment of molecular weight	Molecular weight within range of training set
Training set: Log Kow
Minimum	0.31
Maximum	8.70
Assessment of log Kow	Log Kow within range of training set.

3. Arnot-Gobas BAF/BCF (Arnot & Gobas, 2003)

Assessment of log Kow: Log Kow within acceptable range (log Kow ≤ 9).

Reference 5

Endpoint:

bioaccumulation: aquatic / sediment

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

other: Scientifically accepted calculation method; substance within applicability domain of the model

Justification for type of information:

QMRF: section ‘Overall remarks, attachments’ (‘Overall remarks’)
QPRF: section ‘Applicant’s summary and conclusion’ (‘Executive summary’)

Qualifier:

no guideline followed

Principles of method if other than guideline:

The model performs a read-across and provides a quantitative prediction of bioconcentration factor (BCF) in fish, given in log(L/kg). The read-across is based on the similarity index developed inside the VEGA platform; the index takes into account several structural aspects of the compounds, such as their fingerprint, the number of atoms, of cycles, of heteroatoms, of halogen atoms, and of particular fragments (such as nitro groups). On the basis of this structural similarity index, the three compounds from the dataset resulting most similar to the chemical to be predicted are taken into account: the estimated BCF value is calculated as the weighted average value of the experimental values of the three selected compounds, using their similarity values as weight.

GLP compliance:

Test organisms (species):

other: fish

Details on estimation of bioconcentration:

BASIS FOR CALCULATION OF BCF
- Estimation software: VEGA Read-Across (version 1.0.2)
- Result based on calculated log Pow of: not applicable

Type:

BCF

Value:

136 L/kg

Remarks on result:

other: log BCF = 2.14; According to the model’s AD index, the read-across seems to be reliable.

Validity criteria fulfilled:

yes

Executive summary:

The BCF model (Read-Across) v1.0.2 implemented in the VEGA platform v1.0.8: Estimation Domain (QPRF)

Following, all applicability domain components are reported along with their explanation. Furthermore, the specific index of the substance is given.

- Highest similarity found for similar compounds.

This index takes into account the maximum value of similarity among the three most similar compounds found. Values higher than 0.7 mean that at least one compound with a good structural similarity with the chemical to be predicted has been found. Values lower than 0.7 mean that no remarkably similar compounds have been found, and the read-across could be not reliable.

Defined intervals are:

index ≥ 0.85	the highest similarity value found for similar compounds is adequate for a reliable read-across
index < 0.85	the highest similarity value found for similar compounds is not adequate for a reliable read-across

The substance has a maximum value of similarity of 0.956.

-Lowest similarity found for similar compounds.

This index takes into account the minimum value of similarity among the three most similar compounds found. Values higher than 0.6 mean that also the least similar among the three compounds has an acceptable structural similarity with the chemical to be predicted. Values lower than 0.6 mean that the read-across could be not reliable.

Defined intervals are:

index ≥ 0.7	the lowest similarity value found for similar compounds is adequate for a reliable read-across
index < 0.7	the lowest similarity value found for similar compounds is not adequate for a reliable read-across

The substance has a minimum value of similarity of 0.841.

- Global AD Index.

The final global index takes into account the previous indices, in order to give a general global assessment on the applicability domain for the predicted compound. If at least one of the previous indices has a negative evaluation, the final global index will result in an assessment of unreliability; if all indices have positive evaluation, then the global index will result in an assessment of reliability. In both cases, the global index value is calculated as the average value of the similarity index for the three compounds taken into account for the read-across.

The substance has a global AD index of 0.916.

References:

- VEGA Guide to BCF Read-Across version 1.0.2 implemented in the VEGA tool v1.0.8

Reference 6

Endpoint:

bioaccumulation: aquatic / sediment

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

other: Scientifically accepted calculation method; but substance not within applicability domain of the model

Justification for type of information:

QMRF: section ‘Overall remarks, attachments’ (‘Overall remarks’)
QPRF: section ‘Applicant’s summary and conclusion’ (‘Executive summary’)

Principles of method if other than guideline:

GLP compliance:

Test organisms (species):

other: fish

Details on estimation of bioconcentration:

BASIS INFORMATION
- Measured/calculated logPow: calculated

BASIS FOR CALCULATION OF BCF
- Estimation software: VEGA CAESAR v2.1.13
- Result based on calculated log Pow of: 4.38 (MLogP as calculated by VEGA-model)

Type:

BCF

Value:

98 L/kg

Remarks on result:

other: log BCF = 1.99; According to the model’s global AD index, the predicted substance is out of the Applicability Domain of the model. An expert ananalysis can be found in chapter "Applicant’s summary and conclusion – Executive summary".

Validity criteria fulfilled:

Executive summary:

The BCF model (CAESAR) v2.1.13 implemented in the VEGA platform v1.0.8: Estimation Domain (QPRF)

Following, all applicability domain components are reported along with their explanation and the intervals used. Furthermore, the specific index of the substance is given.

Similar molecules with known experimental value.

Defined intervals are:

1 ≥ index > 0.9	strongly similar compounds with known experimental value in the training set have been found
0.9 ≥ index > 0.75	only moderately similar compounds with known experimental value in the training set have been found
index ≤ 0.75	no similar compounds with known experimental value in the training set have been found

The substance has a similarity index of 0.835.

Accuracy (average error) of prediction for similar molecules.

Defined intervals are:

index < 0.5	accuracy of prediction for similar molecules found in the training set is good
0.5 ≤ index ≤ 1.0	accuracy of prediction for similar molecules found in the training set is not optimal
index > 1.0	accuracy of prediction for similar molecules found in the training set is not adequate

The substance has an accuracy index of 0.38.

Concordance with similar molecules (average difference between target compound prediction and experimental values of similar molecules).

Defined intervals are:

index < 0.5	similar molecules found in the training set have experimental values that agree with the target compound predicted value
0.5 ≤ index ≤ 1.0	similar molecules found in the training set have experimental values that slightly disagree with the target compound predicted value
index > 1.0	similar molecules found in the training set have experimental values that completely disagree with the target compound predicted value

The substance has a concordance index of 0.495.

Maximum error of prediction among similar molecules.

This index takes into account the maximum error in prediction among the two most similar compounds. Values near 0 means that the predicted compounds falls in an area of the model's space where the model gives reliable predictions without any outlier value.

Defined intervals are:

index < 0.5	the maximum error in prediction of similar molecules found in the training set has a low value, considering the experimental variability
0.5 ≤ index < 1.0	the maximum error in prediction of similar molecules found in the training set has a moderate value, considering the experimental variability
index ≤ 1.0	the maximum error in prediction of similar molecules found in the training set has a high value, considering the experimental variability

The substance has a max error index of 0.55.

Atom Centered Fragments similarity check.

This index takes into account the presence of one or more fragments that aren't found in the training set, or that are rare fragments. First order atom centered fragments from all molecules in the training set are calculated, then compared with the first order atom centered fragments from the predicted compound; then the index is calculated as following: a first index "RARE" takes into account rare fragments (those who occur less than three times in the training set), having value of 1 if no such fragments are found, 0.85 if up to 2 fragments are found, 0.7 if more than 2 fragments are found; a second index "NOTFOUND" takes into account not found fragments, having value of 1 if no such fragments are found, 0.6 if a fragments is found, 0.4 if more than 1 fragment is found. Then, the final index is given as the product "RARE * NOTFOUND".

Defined intervals are:

index = 1	all atom centered fragment of the compound have been found in the compounds of the training set
1 > index ≥ 0.7	some atom centered fragment of the compound have not been found in the compounds of the training set or are rare fragments
index < 0.7	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

The substance has an ACF matching index of 0.85.

Descriptors noise sensitivity analysis.

This index checks whether the predicted compound falls in a reliable and stable descriptors space or not. A sequence of random scrambling (noise) is applied to the descriptors calculated for the considered compound, and it is checked if the perturbation of descriptors lead to a significant change in the prediction; if the studied descriptors space is stable, these changes should be of little entity. After a large number of such random scrambling, a final index is calculated.

Defined intervals are:

1 ≥ index > 0.8	predictions has a good response to noise scrambling, thus shows a good reliability
0.8 ≥ index > 0.5	predictions has a not so good response to noise scrambling, thus shows an uncertain reliability
index ≤ 0.5	predictions has a bad response to noise scrambling, thus shows a low reliability

The substance’ descriptors range check is 0959.

Model descriptors range check.

Defined intervals are:

index = 1	descriptors for this compound have values inside the descriptor range of the compounds of the training set
index = 0	descriptors for this compound have values outside the descriptor range of the compounds of the training set

The substance’ descriptors range check is 1.

Global AD Index.

The final global index takes into account all the previous indices, in order to give a general global assessment on the applicability domain for the predicted compound.

Defined intervals are:

1 ≥ index > 0.85	predicted substance is into the Applicability Domain of the model
0.85 ≥ index > 0.75	predicted substance could be out of the Applicability Domain of the model
index ≤ 0.75	predicted substance is out of the Applicability Domain of the model

The substance has a global AD index of 0.71.

Detailed expert analysis

With a global AD Index of 0.71, the substance is outside the applicability domain of the model. This is due to the fact that: 1. only moderately similar compounds with known experimental value in the training set have been found; 2 the maximum error in prediction of similar molecules found in the training set has a moderate value (considering the experimental variability); 3. some atom centered fragments of the compound have not been found in the compounds of the training set or are rare fragments.

Closer examination of the similar compounds shows that despite fairly high similarity indexes (> 0.75) similarity should indeed be considered as moderate. The similar compounds have some additional structural fragments (e.g. additional and/or longer alkyl chains) that may have a significant effect on BCF. Further, the rare atom centered fragment is a P=S fragment in "Structure A". Although it is not used directly in the VEGA MlogP estimation, it may be expected to exert some increased lipophilicity compared to P=O fragments in similar compounds . Further it is noted that VEGA consistently underestimates BCF of similar compounds in most cases >0.5 log units which is higher than the typical uncertainty for experimental BCF values. When investigating the scatter plot of experimental values for the training set (model output; not shown here) it can be seen that the chemical is not within the general relationship logP/BCF.

Altogether, the QSAR result for the target compound seems does not seem reliable.

The model detected several structural alerts which are listed and discussed in detail below.

Structural Alerts

Model: The BCF model (CAESAR) v2.1.13 implemented in the VEGA platform v1.0.8
Substance:	"Structure A"
CAS-#:	confidential
SMILES:	confidential

The following structural alerts were detected.
Structural alerts for outliers
-	None detected
Structural alerts related to a special class of chemicals that have a particular BCF behavior.
SR 03	O-P=O residue; this SA has been found only in non-bioaccumulative compounds (45 chemicals), even when the logP value was higher than 3.
Structural alerts for polar groups.
First group:	None detected
Second group:	None detected
Third group:	None detected

VEGA gives a structural alert for the "PO2 residue (SR 03)" present in "Structure A" and which has been found only in non-bioaccumulative compounds even when the log Kow value was >3. The nature of this lower than expected bioaccumulation is uncertain but may be related to e.g. hydrolysis of phosphate ester bonds.

References:

VEGA Guide to BCF Model version 2.1.13 implemented in the VEGA tool v1.0.8

Reference 7

Endpoint:: bioaccumulation in aquatic species: fish
Type of information:: experimental study
Adequacy of study:: weight of evidence
Study period:: From Feb. 27, 1999 to Sep. 24, 1999
Reliability:: 2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:: guideline study with acceptable restrictions
Remarks:: Test concentrations are above the solubility in water. Thus, the BCF values might overestimate the bioaccumulation of test substance in fish.
Qualifier:: according to guideline
Guideline:: other: Bioconcentration study of a chemical substance in fishes and shellfishes Test method relating to a new chemical substance
Deviations:: no
GLP compliance:: yes
Radiolabelling:: no
Details on sampling:: - Sampling intervals/frequency for test organisms:
Sampled on day 7, 14, 21, 28, 42 and 56 of exposure.
Sampled on day 7 of depuration.

- Sampling intervals/frequency for test medium samples:
Sampled on day 0, 7, 14, 21, 28, 35, 42, 49, and 56.

- Details on sampling and analysis of test organisms and test media samples (e.g. sample preparation, analytical methods):
Test organisms sample preparation:
The test fishes were cut into pieces, put into a homogenizer and acetonitrile was added to the homogenizer. After being homogenized for 8 minutes at 8000 r.p.m., the contents were transferred to a tube for centrifugation. After centrifugation for 15 minutes (8000 r.p.m., 15°C), the supernatant was taken into an Erlenmeyer flask. The residue was retuned to the homogenizer, acetonitrile was added to the cup, homogenization was performed in the same way as the first time, and then the contents were transferred to the tube for centrifugation. Inside of the homogenizer cup was washed three times with acetonitrile, the solution used for washing was also transferred to centrifugation tube and centrifugation was performed in the same way as before. The supernatant was taken into the Erlenmeyer flask, anhydrous sodium sulfate was added to dry. After settled for 30 minutes or more, the solution was filtered. The filtrate was transferred to a separation funnel, n-hexane was added and the separation funnel was shaken with a shaker for 5 minutes. After settled, the acetonitrile layer was collected to a flask. Additional acetonitrile was added to the separation funnel, and extraction was performed in the same way as described above. After settled, the acetonitrile layer was collected to a flask. This was repeated a third time. The collected acetonitrile layer was concentrated under the reduced pressure by means of a rotary evaporator (in a constant - temperature water bath of 30°C). The extract from fish body was injected to Sek-Pak silica pre-conditioned with acetonitrile. The flask was washed with additional solvent for 3 times and this washing solution was also injected. The eluted solution was collected to a flask. The test material is passed through Sek-Pak silica and back ground of the fish body is absorbed. The eluted solution was dried under the reduced pressure (in a constant-temperature water bath of 30°C), the residue was dissolved in n-hexane, and the solution was injected to Sek-Pak silica pre-conditioned with n-hexane. The inside of the flask was washed with n-hexane for three times and the solution was injected to the column. Then n-hexane/acetone = 95:5 (v/v) was injected and the elution was collected to a volumetric flask. After dryness under the reduced pressure (in a constant-temperature water bath of 30°C), the residue was adjusted to 2 ml with n-hexane. This quantified solution was measured by gas chromatography analysis.

Test media sample preparation:
Approximately 1000 ml of water for Level 1 or approximately 5000 ml of water for Level 2 was sampled from the center of the test vessel respectively. 500 ml or 3000 ml of the supernatant for each level was measured with a volumetric cylinder. 500 ml of the measured test water for Level 1 was transferred to a 1L separation funnel. Each 1500 ml of the measured test water for Level 2 was transferred to two 2L separation funnels and these funnels were treated as a set. Inside of each cylinder was washed with a little distilled water and the washing solution was added to each separation funnel respectively. (150 ml to the separation funnel for Level 1,100 ml to each separation funnel for Level 2 respectively) of dichloromethane / acetone = 2 :1 (v/v) (hereinafter this solution is abbreviated to mixture solvent) was added and those funnels were shaken by a shaker for 5 minutes. After settled, the lower layer was collected to an Erlenmeyer flask (The extracted solution for Level 2 were combined). Additional mixture solvent of the same volume as described above was added to each separation funnel and it was shaken and settled. After settled, the lower layer was combined to the Erlenmeyer flask. Anhydrous sodium sulfate was added to dry. After settled for 30 minutes or more the solution was filtered. The inside of the Erlenmeyer flask and the residue were washed with a mixture solvent for 5 times and filtered in the same way. The filtrate was collected to a flask and dried under reduced pressure (in a constant-temperature water bath of 30°C) by a rotary evaporator. The inside of the flask was washed with a little n-hexane and the solutions were adjusted to 2 ml for both Level 1 area and Level 2 respectively. These quantified solutions were measured by gas chromatography.
Vehicle:: yes
Details on preparation of test solutions, spiked fish food or sediment:: PREPARATION AND APPLICATION OF TEST SOLUTION (especially for difficult test substances)
- Method: The test material is transferred to a mortar and dissolved with dichloromethane. HCO-20 of two times of the test material amount is added and is mixed sufficiently until dichloromethane is volatilized. Distilled and deionized water is added little by little to disperse and the volume is adjusted to desired concentration.
- Controls: solvent control at 1.0 mg/l (w/v)
- Chemical name of vehicle (organic solvent, emulsifier or dispersant): polyoxyethylene hydrogenated castor oil HCO-20
- Concentration of vehicle in test medium (stock solution and final test solution(s) at different concentrations and in control(s)): maximum of 1.0 mg/l (w/v)
Test organisms (species):: Cyprinus carpio
Details on test organisms:: TEST ORGANISM
- Common name: carp
- Source: Saku farm (5-41, 3-chome, Setagaya, Setagaya-ku)
- Length at study initiation (lenght definition, mean, range and SD): 9.9±0.6 cm
- Weight at study initiation (mean and range, SD): 26.4 ± 5.6 g
- Weight at termination (mean and range, SD): estimated as 30 g
- Lipid content 4.3 +-0.2%
- Description of housing/holding area: volume : 100 L; flow rate : 300 ml/min (432L/day)

ACCLIMATION
- Acclimation period: Feb. 27, 1999 to Jun. 30, 1999
- Acclimation conditions (same as test or not): same as test
Route of exposure:: aqueous
Test type:: flow-through
Water / sediment media type:: natural water: freshwater
Total exposure / uptake duration:: 56 d
Total depuration duration:: 7 d
Hardness:: 68 mg/l
Test temperature:: Test (solution) temperature: 25.1°C +-0.6
pH:: Test (solution) pH: 6.7 (min.) to 7 (max.)
Dissolved oxygen:: Test (solution) dissolved oxygen: 6.7 mg/l (min.) to 7.4 mg/l (max.)
TOC:: not reported
Salinity:: not reported
Details on test conditions:: TEST SYSTEM
- Test vessel: glass
- Type (delete if not applicable): open
- Material, size, headspace, fill volume: 100 L
- Type of flow-through (e.g. peristaltic or proportional diluter): Dynamic flow system
- Renewal rate of test solution (frequency/flow rate): 300 ml/min (432L/day)
- No. of organisms per vessel: 25 fishes for Level 1, 25 fishes for Level 2 and 6 fishes for Control
- No. of vessels per concentration (replicates): 1 vessel per concentration
- No. of vessels per control / vehicle control (replicates): 1 vessel per solvent control

TEST MEDIUM / WATER PARAMETERS
- Source/preparation of dilution water: dechlorinated Tokyo Metropolitan tap water
- Metals:
Total mercury (mg/l) ≤ 0.0005
Iron (mg/l) 0.012
Manganese (mg/l) ≤ 0.005
Zinc (mg/l) 0.0073
Lead (mg/l) 0.0072
Chromium (VI) (mg/l) ≤ 0.005
Cadmium (mg/l) ≤ 0.001
Arsenic (mg/l) ≤ 0.001
copper (mg/l) <0.005
- Pesticides:
not reported
- Chlorine: < 0.01 mg/l

OTHER TEST CONDITIONS
- Adjustment of pH: no
- Photoperiod: not reported
- Light intensity: not reported

RANGE-FINDING / PRELIMINARY STUDY
- Test concentrations: 2.8, 4.6, 7.4, 12.0, 19.1, 30.6, 49.0, 78.4 mg/l
- Results used to determine the conditions for the definitive study: 48hr-LC50 of 35 mg/l
Nominal and measured concentrations:: Level 1 = 0.5 mg/l (w/v) test substance, analysis confirmed the exposure was at the expected concentration for each component.
Level 2 = 0.05 mg/l (w/v) test substance, analysis confirmed the exposure was at the expected concentration for each component.
The concentration of the individual constituents is correspondingly lower depending on their fraction in the test substance (see any other information on results incl. tables for further details)
Reference substance (positive control):: not specified
Details on estimation of bioconcentration:: BASIS INFORMATION
- Monitoring data: concentration in fish and water monitored

BASIS FOR CALCULATION OF BCF

BCF = (concentration in fish body) / (concentration in test water)
Lipid content:: 4.3 %
Time point:: start of exposure
Remarks on result:: other: ±0.2%
: Key result
Type:: BCF
Value:: >= 842 - <= 2 194
Basis:: whole body w.w.
Time of plateau:: 2 wk
Calculation basis:: steady state
Remarks on result:: other: Peak 1 of test material
Remarks:: Conc.in environment / dose:0.05 mg/l (w/v) Test material
: Key result
Type:: BCF
Value:: >= 642 - <= 2 508
Basis:: whole body w.w.
Time of plateau:: 2 wk
Calculation basis:: steady state
Remarks on result:: other: Peak 1 of test material, in access of water solubility and of low reliability
Remarks:: Conc.in environment / dose: 0.5 mg/L (w/v) Test material
Type:: BCF
Value:: ca. 63 - ca. 118
Basis:: whole body w.w.
Time of plateau:: 2 wk
Calculation basis:: steady state
Remarks on result:: other: Peak 2 of test material
Remarks:: Conc.in environment / dose:0.5 mg/l (w/v) Test material
Type:: BCF
Value:: ca. 64 - ca. 148
Basis:: whole body w.w.
Time of plateau:: 2 wk
Calculation basis:: steady state
Remarks on result:: other: Peak 2 of test material
Remarks:: Conc.in environment / dose: 0.05 mg/l (w/v) Test material
Type:: BCF
Value:: ca. 51 - ca. 113
Basis:: whole body w.w.
Time of plateau:: 2 wk
Calculation basis:: steady state
Remarks on result:: other: Peak 3 of test material
Remarks:: Conc.in environment / dose:0.5 mg/l (w/v) Test material
Type:: BCF
Value:: ca. 75 - ca. 182
Basis:: whole body w.w.
Time of plateau:: 2 wk
Calculation basis:: steady state
Remarks on result:: other: Peak 3 of test material
Remarks:: Conc.in environment / dose:0.05 mg/l (w/v) Test material
: Key result
Elimination:: yes
Parameter:: DT50
Depuration time (DT):: 1 wk
Details on kinetic parameters:: not reported
Metabolites:: not reported
Details on results:: - Mortality of test organisms: none reported

- Behavioural abnormalities: The test material caused swimming abnormality of the test fish in Level 1 (0.5 mg/l) from Day 1 of the exposure period.

- Organ specific bioaccumulation: for Peak 1
Bioconcentration factors for each part of fish body were measured for two fishes in each level respectively on 49 day
Internal Organs:
Level 1: 950 to 994 times; (mean 972)
Level 2: 1808 to 4027 times (mean 2918)

Edible Parts:
Level 1: 376 to 499 times; (mean 438)
Level 2: 736 to 780 times (mean 758)

Head and skin:
Level 1: 620 to 966 times; (mean 793)
Level 2: 2148 to 2874 times (mean 2511)

- Mortality and/or behavioural abnormalities of control: none reported

- Depuration:
Immediately after sampling water and fish sample on Day 56 of the exposure period, water of the test vessel was retumed to fresh water without
the test material. Two fishes for Level 1 area and Level 2 area respectively were sampled for analysis of Day 7 of the depuration period. It was confirned that the concentration of the main component (peak 1) was reduced by half at Week 1.
Swimming abnormality of the test fish observed in Level 1 observed from the start of the exposure was not recovered at all, although bioconcentration factor of peak 1 (main component) reduced to half on Day 7 of the depuration study
Validity criteria fulfilled:: not applicable
Conclusions:: The substances is bioaccumulative (BCF > 2000 and <5000 L/kg).

Description of key information

Based on a weight of evidence approach it can be concluded that the bioaccumulation potential is high. The BCF is assumed to be above 2000 and below a BCF of 5000. Thus, the substance is considered to be bioaccumulative (b) but not very bioaccumulative (not vb).

Key value for chemical safety assessment

BCF (aquatic species):: 2 551 dimensionless

Additional information

According to Annex XI of Regulation (EC) No 1907/2006, experimental data with O,O,O-triphenyl phosphorothioate in a lower purity and QSAR calculations were used in a Weight-of-evidence approach to assess the bioaccumulation potential of the test substance.

In Article 13 of Regulation (EC) No 1907/2006, it is laid down that information on intrinsic properties of substances may be generated by means other than tests, provided that the conditions set out in Annex XI (of the same Regulation) are met. Furthermore according to Article 25 of the same Regulation testing on vertebrate animals shall be undertaken only as a last resort. According to Annex XI of Regulation (EC) No 1907/2006, (Q)SAR results can be used if (1) the scientific validity of the (Q)SAR model has been established, (2) the substance falls within the applicability domain of the (Q)SAR model, (3) the results are adequate for the purpose of classification and labeling and/or risk assessment and (4) adequate and reliable documentation of the applied method is provided.

Most data used to cover the endpoint (in the WoE) adequately fulfilled the criteria listed in Annex XI of Regulation (EC) No 1907/2006 and therefore the endpoint is sufficiently covered and suitable for risk assessment. Therefore, and for reasons of animal welfare, further experimental studies on bioaccumulation are not considered to be needed.

Th Weight-of-evidence approach comprised several QSAR estimations, experimental data and data on the molecular size and log Kow. The data used are summarized in te table attached.

EXPERIMENTAL DATA

One study is available investigating the bioconcentration of the substance in fish according to OECD guideline 305 with O,O,O-triphenyl phosphorothioate in a lower purity. The study was performed at the Institute of Ecotoxicology of the Gakushuin University (1999). The BCF of the individual constituents of the test material was determined. In this study, common carp (C. carpio, 25 per group) were exposed to test substance concentrations of 0.5 and 0.05 mg/L during an 8 weeks uptake phase under flow-through conditions using a vehicle. The concentrations of the major constituents were 0.188 mg/L in Level 1 and 0.0188 mg/L in Level 2, respectively. Steady-state concentrations were achieved in the tissues of fish within 14 days after start of exposure. The uptake phase was followed by a 7-day depuration phase (after day 56). Test substance (constituent) recoveries throughout the test were well above 90%. 2 fish per test concentration were sampled to determine steady-state whole body BCF values for the major constituents. In addition, 2 fish per test concentration were sampled after 7 weeks exposure to determine steady-state BCF values for fish internal organs, edible parts and head-skin tissues. The BCF values during steady-state (after 2 weeks exposure) were determined to be 1274-2508 and 1213-2194 for test concentrations of 0.5 and 0.05 mg/L, respectively. Maximum values of 2508 (at day 42, level 1) and 2194 (at day 28, level 2) were recorded for the respective test concentrations. All these values are not normalised to a lipid content of 5% (fish lipid content in the study is reported to be 4.3%). No significant bioconcentration was noted for any of the other constituents (maximum BCF of 226 for all structures). Determination of BCF values for specific fish part as well as depuration testing was performed only for O,O,O, triphenyl thiophosphate. The average steady-state BCF values determined for internal organs, edible parts and head-skin tissues were 972, 438 and 793 at the 0.5 mg/L exposure level and 2918, 758 and 2511 at the 0.05 mg/L exposure level (with a maximum 4027 in internal organs). After the 7-day depuration phase significant reduction of BCF values was reported. At the exposure level of 0.5 and 0.05 mg/L the BCF values were 146-697 and 4-15 mg/L, respectively. The half reduction time is reported as 'within 7 days'.

In level 1 (0.5 mg/L treatment) swimming condition and food consumption condition and health condition were reported as unnatural (swimming), no good (food consumption), somewhat no good (health) from day one of exposure until the end of exposure and depuration the results of level one are of limited reliability. Furthermore, the solubility of the main component of the test material (peak 1, triphenyl thiophosphate) is reported to be lower than 0.2 mg/Las applied in Level 1. No adverse findings were reported for level 2 (test material concentration 0.05 mg/L) and the corresponding test concentration of the triphenyl thiophosphate was determined to be within the solubility range (concentration of peak 1 triphenyl thiophosphate ca. 0.019 mg/L). It is assumed that the adverse effects in level 1 reflect an effect due to testing above the solubility limit rather than a toxicological effect as they do not occur in short term testing of the soluble fraction. Therefore, the BCF results in Level 2 for triphenyl thiophosphate are reliable and the highest BCF value of 2194 is used as worst case.

In this study limited data on the lipid content are available. However, the fish in level 2 exposure were healthy and had good food consumption. No significant growth was observed (see attachment in robust study summary, growth data were plotted as sampling day versus natural log (ln) of weight). For further assessment the BCF value of 2194 is normalized to a lipid content of 5% resulting in a BCF of 2551. Based on the growth data it can be expected that the lipid content did not decrease to less than 2.19% which would fulfill the vB criterion (BCF > 5000) for triphenyl thiophosphate. Therefore, the results of this study indicate that the BCF of O,O,O, triphenyl thiophosphate fulfills the criterion bioaccumulative (B) but not very bioaccumulative (vB) according to REACH, Regulation (EC) No 1907/2006, Annex XIII.

QSAR

In addition to these experimentally determined BCF values a number of QSAR calculations were performed. In general, for log Kow based model calculations reliable experimental log Kow values should be preferred as model input over estimated log Kow values (e.g. KOWWIN). In case of this substance, reliable experimental data on log Kow are available. The Meylan and the Arnot-Gobas predictions are considered to be reliable as these structures fall within the applicability domains of the respective sub-models. Based on the Meylan sub-model the BCF value is 925 L/kg. The BCF value calculated by the Arnot-Gobas sub-model is 7882 L/kg for the upper trophic level but a significant reduction of BCF is observed when biotransformation rates are taken into account (643 - 884 L/kg). Furthermore, a lipid content of 10.7% was assumed as default lipid content for upper trophic level in that model. Normalizing to 5% lipid content would result in a BCF of 3683 L7kg. Considering biotransformation, a maximum BCF value of 884 L/kg is determined. The model predictions are considered indicative for BCF values of <5000.

Within EPA T.E.S.T the consensus value is determined by calculating the average BCF from 5 other sub-models and is therefore considered to give the most reliable outcome. The most similar compounds displayed in the model output lack the P=S fragment of the thiophosphate which is likely to significantly change the substances’ properties and therewith can influence their bioaccumulation potential. Although the substance falls within the applicability domain of the model, the limited compound similarity is also expressed in the mean absolute errors (MAE) being partially > 0.5 compared to the training set (as well as the external test set). Therefore, the confidence in the predicted BCF values is low.

The VEGA CAESAR sub-model calculates BCF values based on MLogP. The MLogP calculation however appears not to account for the P=S fragment in the thiophosphate moiety and is therefore likely to generate a relatively low estimated log Kow value. This however is not a prerequisite for determination of log Kow but rather a choice of molecular descriptors (i.e. fragments) used in the log Kow prediction model. The BCF value calculated with the VEGA CAESAR sub-model is 98 L/kg. The predicted MLogP value of 4.38 lies close to the experimentally determined value of 4.8-5.0. In addition to calculation of a BCF value as such, VEGA determines whether a substance falls within the applicability domain by allocating similarity indexes based on comparison of the model outcome with calculated and experimental data of structurally similar compounds from the underlying database. Based on this comparison the structure falls out of the applicability domain of the model. This is due primarily to the fact that the most similar compounds displayed in the model output contain a P=O fragment rather than the P=S fragments and therefore probably have much lower calculated and experimental BCF values than predicted for the target compounds. Although this in some cases countered by the presence of other hydrophobic moieties such as e.g. additional and/or longer alkyl chains, this still drives similarity indexes to below cut-offs for meeting the applicability domain of the model. This is visualized also in the scatter plot of experimental values for the training set form which it is clear that the target chemicals fall not within the general relationship log kow/BCF determined for the model. Based on these considerations the confidence in the predicted BCF values is considered to be low.

The VEGA Read-Across sub-model performs a read-across to only those 3 compounds from the dataset most similar to the target compound and determines similarity indexes based on several structural aspects of the compounds, such as their fingerprint, the number of atoms, of cycles, of heteroatoms, of halogen atoms, and of particular fragments. The estimated BCF values is calculated as the weighted average value of the experimental values of the three selected compounds, using their similarity values as weight. The BCF value calculated with this sub-model is 136 L/kg. Based on this approach the substance falls within the applicability domain of the model. However, the first two similar compounds are triphenyl phosphate (CAS 115-86-6) and triphenyl phosphite (CAS 101-02-0). These substances are known to hydrolyse faster and are readily biodegradable. Therefore, the BCF prediction is considered likely to be an underestimate.

The VEGA Meylan sub-model is based on the Meylan model as also incorporated in the EPI Suite BCFBAF module. The log Kow values used as model input are calculated based on a slightly modified version of KOWWIN (which may explain the slightly higher log Kow values calculated in VEGA). The BCF value calculated with this sub-model is 11561 L/kg. This BCF is however calculated based on a log Kow input of 7.12 instead of the experimentally determined log Kow of 5. As the log Kow cannot be inserted manually in VEGA Meylan, and considering the Meylan log Kow/BCF relationship, this BCF should be considered to be highly overestimated. Comparable to the CAESAR sub-model, the Meylan sub-model determines whether a substance falls within the applicability domain by comparing the model outcome with calculated and experimental data of structurally similar compounds (similarity indexes). Based on this comparison the substance is just outside the applicability domain of the model (global AD Index of 0.75)

This is due to the fact that: 1. similar molecules found in the training set have experimental values that strongly disagree with the target compound predicted value; 2. reliability of logP value used by the model is not adequate.

For this substance an experimentally determined log Kow value of 4.8 -5.0 is available. This value can however not be used as input in the model (as is the case with e.g. BCFBAF). Therefore, the estimated log Kow value of 7.12 used in the VEGA Meylan BCF prediction should indeed be considered as not adequate. The Meylan BCF model is strongly based on the log Kow prediction of the compound and reaches maximum values at a log Kow of 7. The estimated BCF value based on a log Kow of 7.12 will thus be significantly overestimated. Therefore, the confidence in the predicted BCF values is considered to be low.

The OASIS Catalogic model BCF base-line model predicts a bioconcentration factor based on log Kow and accounts for a number of mitigating factors, such as molecular size, metabolism of parent chemical, water solubility and ionization. The experimental determined log Kow of 5 was used as model input. The highest so calculated BCF value is 5200 L/kg taking into consideration no mitigating factors. Considering the mitigating factors the BCF is 2239 L/kg. The most important mitigating factor is molecular size. However, metabolism is not regarded as significant for this structure despite the results of the Arnot-Gobas model and other indications for reduced bioaccumulation potential (see below).The structure fulfills the general properties requirements and are in the mechanistic domain of the model but are out of the interpolation structural space mainly due to structural fragments not being present in the training chemicals. Therefore, the mitigating factor metabolism might be underestimated.

INDICATIONS OF REDUCED BIOACCUMMULATION POTENTIAL

Structural alerts

The substance contains no structural fragment which is known to be related to bioaccumulation or reduced bioaccumulation, other than their contribution to estimated log Kow.

Log Kow

At very high Log Kow (> ca.7), a decreasing relationship with BCF is observed for organic substances. Based on current knowledge, a calculated log Kow >10 is taken as an indicator of reduced bioconcentration for PBT assessments. This cut-off does not apply to O,O,O triphenyl thiophosphate.

Molecular size

The decreasing log Kow/BCF relationship is considered to be due also, at least in part, by reduced uptake due to increasing molecular size. The molecular size of a substance is reflected by, among others, the average maximum diameter (Dmax-aver). Very bulky molecules will less easily pass through cell membranes which results in a reduced BCF of the substance. The substance does not fulfill the criteria for indication of reduced bioaccumulation based on molecular weight and average maximum diameter according to ECHA guidance on information requirements part R.11. However, for O,O,O triphenyl thiophosphate the OASIS Catalog model which considers size and flexibility of the structure identifies molecular size as an important mitigating factor resulting in a BCF of 2239.

Metabolism

The Arnot-Gobas model predicts significant biotransformation potential. In case of the Arnot-Gobas model, transformation is expected for the thiophosphate specific P=S group but also for aromatic-H and methyl groups. However, for some organophosphorothionate pesticides cytochrome P450 mediated oxidation of the P=S group to the P=O derivative is part of the bioactivation process (defulfurization of parathion, ECETOC TR67, 1995). Furthermore, for triphenylphosphate (CAS 115-86-6), which differs only from O,O,O triphenyl thiophosphate by a central P=O fragment instead of a P=S fragment, is reported to be degraded by P-O hydrolysis in rat liver homogenate to form diphenyl phosphate as the major metabolite (EU-RAR, 2002). Although these mammalian data cannot be extrapolated directly to fish, some form of metabolism in fish is considered likely considering the rapid depuration observed in the fish BCF study.

Toxicological studies

No indication for bioaccumulation could be found in the available studies

CONCLUSION

Three models give BCF values above the experimentally derived BCF of 2551: Arnot-Gobas upper trophic level; incl. biotransformation rate of zero, VEGA Meylan v1.0.2, Catalogic v5.11.15 (no mitigating factors appied). All of these modelled values have some deficiencies. In the Arnot Gobas model biotransformation was not considered and the default lipid content was assumed to be 10.7%. The BCF values in the Arnot -Gobas model range from 643 to 884 when taking biotransformation into account. In the VEGA Meylan model the experimentally derived log Pow could not be used and in the Catalogic model not mitigating factors like molecular size and flexibility were not considered. The BCF modelled with Catalogic and considering mitigating factors is 2239 L/kg. On the other hand the BCF values derived with US EPA T.E.S.T v.1, VEGA Read across v1.0.2 and VEGA CAESAR v2.1.13 are likely to underestimate the bioaccumulation potential as the P=S fragment is not taken into account. Considering the evidence for metabolism and the data from the toxicological studies limited bioaccumulation potential is expected. In summary, in a weight-of-evidence approach balancing different QSAR estimations and experimental data significant accumulation of the compound in organisms is expected. However, due to the experimental data and the QSARs it is not expected that the BCF is above the “vB” cut-off criterion of 5000. For further assessment the BCF of 2551 is used as worst case.

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Acids	0.000
Metabolism	0.000
Phenols	0.000
Size	0.998
Water solubility	6.95E-04

Week	Peak 1 (theor. conc. 0.188 mg/L)	Peak 2 (theor. conc. 0.08 mg/L)	Peak 3(theor. conc. 0.128mg/L)	Peak 4(theor. conc. 0.0280 mg/L)	Peak 5(theor. conc. 0.0343 mg/L)	Peak 7(theor. conc. 0.0102 mg/L)
1	0.183	0.0783	0.125	0.0269	0.0283	0.0101
2	0.181	0.0800	0.128	0.0275	0.0297	0.0102
3	0.179	0.0807	0.129	0.0279	0.0308	0.0103
4	0.179	0.0814	0.129	0.0281	0.0314	0.0103
5	0.180	0.0816	0.129	0.0282	0.0316	0.0102
6	0.179	0.0810	0.127	0.0282	0.0318	0.0101
7	0.179	0.0811	0.128	0.0283	0.0317	0.0101
8	0.178	0.0803	0.127	0.0281	0.0318	0.0102

Week	Peak 1(theor. conc. 0.0188 mg/L)	Peak 2(theor. conc. 0.008 mg/L)	Peak 3(theor. conc. 0.0128mg/L)	Peak 4(theor. conc. 0.00280 mg/L)	Peak 5(theor. conc. 0.00343 mg/L)	Peak 7(theor. conc. 0.00102 mg/L)
1	0.0177	0.00813	0.0130	0.00268	0.00340	0.000930
2	0.0184	0.00835	0.0133	0.00272	0.00336	0.000987
3	0.0189	0.00855	0.0136	0.00280	0.00350	0.00104
4	0.0186	0.00851	0.0134	0.00282	0.00352	0.00104
5	0.0185	0.00839	0.0134	0.00281	0.00350	0.00105
6	0.0183	0.00834	0.0133	0.00281	0.00349	0.00104
7	0.0182	0.00836	0.0133	0.00280	0.00347	0.00104
8	0.0181	0.00838	0.0132	0.00282	0.00345	0.00103

Day/sample	Level1 Fish weight (g)	Level1 Concentration in fish body (microg/g)	Level2 Fish weight (g)	Level2 Concentration in fish body (microg/g)
7A / 7B	23.2 / 35.5	54.9 / 60.0	27.5 / 32.0	8.51 / 6.99
14A / 14B	35.2 / 21.6	157 / 116	26.9 / 28.7	15.5 / 18.8
21A / 21B	20.1 / 19.8	235 / 386	20.2 / 29.6	25.0 / 32.8
28A / 28B	34.7 / 25.6	228 / 310	28.9 / 29.7	26.1 / 40.8
42A / 42B	38.2 / 24.7	442 / 449	20.8 / 25.6	34.2 / 22.2
56A / 56B	25.8 / 20.7	297 / 238	37.7 / 32.6	36.6 / 25.3

Component of the test material	BCF Level 1	theoretical concentration based on initial concentration of the test material in Level 1(mg/L)	BCF Level 2	theoretical concentration based on initial concentration of the test material in Level 2 (mg/L)
Peak 1	641 -2508	0.188	842 -2194	0.0188
Peak 2	63 -118	0.08	64 -148	0.008
Peak 3	51 -113	0.128	75 -182	0.0128
Peak 4	4 times or less	0.0280*	44 times or less	0.00280*
Peak 5	2 times or less	0.0343*	24 times or less	0.00343*
Peak 7	23 times or less	0.0102*	226 times or less	0.00102*

		Weight (g)	Level 1 (0.5mg/L test material)	Weight (g)	Level 2 (0.05mg/L test material)
Internal organs	A	2.4	950 times	3.1	4027 times
	B	3.4	994 times	1.2	1808 times
Edible parts	A	3.6	499 times	7.1	736 times
	B	3.4	376 times	5.8	780 times
Head skin	A	10.8	966 times	11.6	2874 times
	B	10.9	620 times	6.7	2148 times

Passage time (day)	n=2	Level 1 (0.5 mg/L test material)	Level 2 (0.05 mg/L test material)
7	A / B	146 / 697	15 / 4

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O,O,O-triphenyl phosphorothioate

Bioaccumulation: aquatic / sediment

Administrative data

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Description of key information

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