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Bioaccumulation: aquatic / sediment

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Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
(Q)SAR
Adequacy of study:
supporting study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Scientifically accepted calculation method
Justification for type of information:
QSAR prediction
Principles of method if other than guideline:
Estimation of BCF, BAF and biotransformation rate using BCFBAF v3.01
GLP compliance:
no
Test organisms (species):
other: fish
Details on estimation of bioconcentration:
BASIS INFORMATION CCCCCCCCCCCCCNC(=O)C=CC(=O)(O)
- Measured/calculated logPow: 5.75

BASIS FOR CALCULATION OF BCF
- Estimation software: BCFBAF Program (v3.01)
- Result based on calculated log Pow of: 5.75

BASIS INFORMATION CCCCCCCCCCCCCNC(=O)C=CC(=O)(O)
- Measured/calculated logPow: 5.38

BASIS FOR CALCULATION OF BCF
- Estimation software: BCFBAF Program (v3.01)
- Result based on calculated log Pow of: 5.38
Type:
BCF
Value:
10
Basis:
not specified
Remarks on result:
other: SMILES CCCCCCCCCCCCCNC(=O)C=CC(=O)(O) The substance is within the applicability domain of the BCFBAF submodel: Bioconcentration factor (BCF; Meylan et al., 1997/1999).
Type:
BAF
Value:
405
Basis:
not specified
Calculation basis:
steady state
Remarks on result:
other: SMILES CCCCCCCCCCCCCNC(=O)C=CC(=O)(O) 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:
10
Remarks on result:
other: SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)C=CC(=O)(O) The substance is within the applicability domain of the BCFBAF submodel: Bioconcentration factor (BCF; Meylan et al., 1997/1999).
Type:
BAF
Value:
309
Remarks on result:
other: SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)C=CC(=O)(O) 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).
Details on kinetic parameters:
SMILES CCCCCCCCCCCCCNC(=O)C=CC(=O)(O)
Biotransformation half-life (days): 1.04
Biotransformation rate (kM, normalised to 10 g fish at 15 °C): 0.662 /day
The substance is within the applicability domain of the BCFBAF submodel: Biotransformation rate in fish (kM; Arnot et al., 2008a/b).

SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)C=CC(=O)(O)
Biotransformation half-life (days): 0.795
Biotransformation rate (kM, normalised to 10 g fish at 15 °C): 0.8719 /day
The substance is within the applicability domain of the BCFBAF submodel: Biotransformation rate in fish (kM; Arnot et al., 2008a/b).

BCFBAF Program (v3.01) Results:

==============================

SMILES : CCCCCCCCCCCCCNC(=O)C=CC(=O)(O)

CHEM  :

MOL FOR: C17 H31 N1 O3

MOL WT : 297.44

--------------------------------- BCFBAF v3.01 --------------------------------

Summary Results:

Log BCF (regression-based estimate): 1.00 (BCF = 10 L/kg wet-wt)

Biotransformation Half-Life (days) : 1.05 (normalized to 10 g fish)

Log BAF (Arnot-Gobas upper trophic): 2.61 (BAF = 405 L/kg wet-wt)

 

Log Kow (experimental): not available from database

Log Kow used by BCF estimates: 5.75

 

Equation Used to Make BCF estimate:

Log BCF = 1.00 (Ionic; Log Kow dependent)

 

 

Estimated Log BCF = 1.000 (BCF = 10 L/kg wet-wt)

 

===========================================================

Whole Body Primary Biotransformation Rate Estimate for Fish:

===========================================================

------+-----+--------------------------------------------+---------+---------

TYPE | NUM | LOG BIOTRANSFORMATION FRAGMENT DESCRIPTION | COEFF | VALUE

------+-----+--------------------------------------------+---------+---------

Frag | 1 | Linear C4 terminal chain [CCC-CH3]      | 0.0341 | 0.0341

Frag | 1 | Aliphatic acid  [-C(=O)-OH]             | 0.3803 | 0.3803

Frag | 1 | Amide  [-C(=O)-N or -C(=S)-N]          | -0.5952 | -0.5952

Frag | 1 | Methyl [-CH3]                           | 0.2451 | 0.2451

Frag | 12 | -CH2- [linear]                          | 0.0242 | 0.2902

Frag | 2 | -C=CH [alkenyl hydrogen]                | 0.0988 | 0.1977

Frag | 2 | -C=CH [alkenyl hydrogen]                | 0.0000 | 0.0000

L Kow| * | Log Kow =  5.75 (KowWin estimate)       | 0.3073 | 1.7675

MolWt| * | Molecular Weight Parameter               |        | -0.7627

Const| * | Equation Constant                        |        | -1.5058

============+============================================+=========+=========

RESULT  |       LOG Bio Half-Life (days)           |        | 0.0199

RESULT  |           Bio Half-Life (days)           |        |  1.047

NOTE    | Bio Half-Life Normalized to 10 g fish at 15 deg C  |

============+============================================+=========+=========

 

Biotransformation Rate Constant:

kM (Rate Constant): 0.662 /day (10 gram fish)

kM (Rate Constant): 0.3723 /day (100 gram fish)

kM (Rate Constant): 0.2094 /day (1 kg fish)

kM (Rate Constant): 0.1177 /day (10 kg fish)

 

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

Estimated Log BCF (upper trophic) = 2.594 (BCF = 392.3 L/kg wet-wt)

Estimated Log BAF (upper trophic) = 2.608 (BAF = 405 L/kg wet-wt)

Estimated Log BCF (mid trophic)  = 2.729 (BCF = 535.5 L/kg wet-wt)

Estimated Log BAF (mid trophic)  = 2.871 (BAF = 743.5 L/kg wet-wt)

Estimated Log BCF (lower trophic) = 2.770 (BCF = 588.3 L/kg wet-wt)

Estimated Log BAF (lower trophic) = 3.192 (BAF = 1555 L/kg wet-wt)

 

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

Estimated Log BCF (upper trophic) = 4.278 (BCF = 1.896e+004 L/kg wet-wt)

Estimated Log BAF (upper trophic) = 6.133 (BAF = 1.358e+006 L/kg wet-wt)

 

BCFBAF Program (v3.01) Results:

==============================

SMILES : CCC(C)C(C)C(C)C(C)C(C)CNC(=O)C=CC(=O)(O)

CHEM  :

MOL FOR: C17 H31 N1 O3

MOL WT : 297.44

--------------------------------- BCFBAF v3.01 --------------------------------

Summary Results:

Log BCF (regression-based estimate): 1.00 (BCF = 10 L/kg wet-wt)

Biotransformation Half-Life (days) : 0.795 (normalized to 10 g fish)

Log BAF (Arnot-Gobas upper trophic): 2.50 (BAF = 319 L/kg wet-wt)

 

Log Kow (experimental): not available from database

Log Kow used by BCF estimates: 5.38

 

Equation Used to Make BCF estimate:

Log BCF = 1.00 (Ionic; Log Kow dependent)

 

 

Estimated Log BCF = 1.000 (BCF = 10 L/kg wet-wt)

 

===========================================================

Whole Body Primary Biotransformation Rate Estimate for Fish:

===========================================================

------+-----+--------------------------------------------+---------+---------

TYPE | NUM | LOG BIOTRANSFORMATION FRAGMENT DESCRIPTION | COEFF | VALUE

------+-----+--------------------------------------------+---------+---------

Frag | 1 | Aliphatic acid  [-C(=O)-OH]             | 0.3803 | 0.3803

Frag | 1 | Amide  [-C(=O)-N or -C(=S)-N]          | -0.5952 | -0.5952

Frag | 6 | Methyl [-CH3]                           | 0.2451 | 1.4706

Frag | 2 | -CH2- [linear]                          | 0.0242 | 0.0484

Frag | 5 | -CH-  [linear]                          | -0.1912 | -0.9562

Frag | 2 | -C=CH [alkenyl hydrogen]                | 0.0988 | 0.1977

Frag | 2 | -C=CH [alkenyl hydrogen]                | 0.0000 | 0.0000

L Kow| * | Log Kow =  5.38 (KowWin estimate)       | 0.3073 | 1.6545

MolWt| * | Molecular Weight Parameter               |        | -0.7627

Const| * | Equation Constant                        |        | -1.5058

============+============================================+=========+=========

RESULT  |       LOG Bio Half-Life (days)           |        | -0.0996

RESULT  |           Bio Half-Life (days)           |        |  0.795

NOTE    | Bio Half-Life Normalized to 10 g fish at 15 deg C  |

============+============================================+=========+=========

 

Biotransformation Rate Constant:

kM (Rate Constant): 0.8719 /day (10 gram fish)

kM (Rate Constant): 0.4903 /day (100 gram fish)

kM (Rate Constant): 0.2757 /day (1 kg fish)

kM (Rate Constant): 0.155 /day (10 kg fish)

 

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

Estimated Log BCF (upper trophic) = 2.501 (BCF = 316.8 L/kg wet-wt)

Estimated Log BAF (upper trophic) = 2.504 (BAF = 319.4 L/kg wet-wt)

Estimated Log BCF (mid trophic)  = 2.633 (BCF = 429.4 L/kg wet-wt)

Estimated Log BAF (mid trophic)  = 2.685 (BAF = 484.4 L/kg wet-wt)

Estimated Log BCF (lower trophic) = 2.672 (BCF = 470.2 L/kg wet-wt)

Estimated Log BAF (lower trophic) = 2.882 (BAF = 762.4 L/kg wet-wt)

 

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

Estimated Log BCF (upper trophic) = 4.137 (BCF = 1.372e+004 L/kg wet-wt)

Estimated Log BAF (upper trophic) = 5.636 (BAF = 4.327e+005 L/kg wet-wt)

 

 

Executive summary:

QPRF: BCFBAF v3.01

 

1.

Substance

CCCCCCCCCCCCCNC(=O)C=CC(=O)(O)

CCC(C)C(C)C(C)C(C)C(C)CNC(=O)C=CC(=O)(O)

2.

General information

 

2.1

Date of QPRF

June 2, 2017

2.2

QPRF author and contact details

BASF SE

3.

Prediction

3.1

Endpoint
(OECD Principle 1)

Endpoint

Bioaccumulation (aquatic)

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 (297.44  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 (5.38; 5.75).

 

d) Maximum number of instances of correction factor in any of the training set compounds (On-Line BCFBAF Help File, Appendix E)

Not exceeded.

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 (297.44  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 (5.38, 5.75).

e) The substance isnometal or organometal, pigment or dye, or a perfluorinated substance.

(On-Line BCFBAF Help File, Ch. 7.2.3)

Notfulfilled

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.

 

 

Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
(Q)SAR
Adequacy of study:
supporting study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Scientifically acceptable calculation method; the substance is within the applicability domain of the model.
Justification for type of information:
QSAR prediction
Principles of method if other than guideline:
Calculation using Catalogic v.5.11.13, BCF base-line model v.02.07
GLP compliance:
no
Specific details on test material used for the study:
The registration item is an UVCB.
Therefore, two molecules (highly branched versus not branched at all), representing the lower and the upper limit of the range of possible structures, respectively, were used to predict the potential for bioaccumulation of the registration item.
SMILES codes used as input to the calculation tool were:

CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O

CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O
Details on estimation of bioconcentration:
BASIS FOR CALCULATION OF BCF
- Estimation software: OASIS Catalogic v5.11.13 [BCF base line model - v.02.07]
Type:
BCF
Value:
191
Remarks on result:
other: SMILES CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O, log BCF corrected = 2.28
Type:
BCF
Value:
295
Remarks on result:
other: SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O, log BCF corrected = 2.47

SMILES CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O

DOMAIN APPLICABILITY

With regard to the parametric and mechanistic domain, the test substance is within the applicability domain of the model. Most of the fragments fall into the correct structural domain, 42% are unknown. There are no incorrect fragments. Therefore, the estimation is considered reliable.

EFFECTS OF MITIGATING FACTORS

relative mitigating effect of Acids       0.432

relative mitigating effect of Metabolism       0.122

relative mitigating effect of Phenols       0.000

relative mitigating effect of Size3       0.450

relative mitigating effect of Watersolubility       5.73E-005

Relative synergistic/antagonistic effect       -4.244E-003

Molecule size

DiamMax-Min       13.528

DiamMax-Max       24.997

DiamMax-Average       17.783

SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O

DOMAIN APPLICABILITY

With regard to the parametric and mechanistic domain, the test substance is within the applicability domain of the model. Most of the fragments fall into the correct structural domain, 42% are unknown. There are no incorrect fragments. Therefore, the estimation is considered reliable.

EFFECTS OF MITIGATING FACTORS

relative mitigating effect of Acids       0.550

relative mitigating effect of Metabolism       0.1558

relative mitigating effect of Phenols       0.000

relative mitigating effect of Size3       0.2956

relative mitigating effect of Watersolubility       1.42E-004

Relative synergistic/antagonistic effect       -1.908E-003

Molecule size

DiamMax-Min       11.465

DiamMax-Max       18.964

DiamMax-Average       14.688

The magnitude of the effect on the BCF by the single mitigating factors should be regarded as tentative information as the factors influence each other. The effect of individual mitigating factors (e.g. metabolism) is calculated as:

Mitigating effect of metabolism = log BCFcorrected(all factors except for metabolism) – log BCFcorrected(all factors)

RESULTS AND DISCUSSION

The BCF base-line model estimates the BCF to be 191 and 295 (log BCF = 2.28 and 2.47) for the two structrues. Mitigating factors like metabolism, molecular size and the water solubility were considered by the model.

The effects of acids, size and, to a lesser extent, metabolism were the main contributors to the reduction of potential for bioaccumulation as compared to an estimation based on logKOW only.

CONCLUSION

Both representative structures, and therefore also the components of the UVCB, are considered to not significantly bioaccumulate in organisms.

Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
calculation (if not (Q)SAR)
Remarks:
estimated by calculation
Adequacy of study:
supporting study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Methods were validated by US EPA using statistical external validation; based on the mean absolute errors of the models the confidence in the predicted results is high/low.
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:
no
Specific details on test material used for the study:
The registration item is an UVCB.
Therefore, two molecules (highly branched versus not branched at all), representing the lower and the upper limit of the range of possible structures, respectively, were used to predict the potential for bioaccumulation of the registration item.
SMILES codes used as input to the calculation tool were:

CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O

CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O
Test organisms (species):
other: fish
Details on estimation of bioconcentration:
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
Type:
BCF
Value:
1.58
Remarks on result:
other: SMILES CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O, method: consensus (average of reasonable results from all models)
Type:
BCF
Value:
2.85
Remarks on result:
other: SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O, method: consensus (average of reasonable results from all models)

Model details:

SMILES CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O

Method Predicted value Model statistics MAE (in log10)
External test set Training set
log BCF BCF No. of chemicals Entire set SC >= 0.5 Entire set SC >= 0.5
Consensus method 0,20 1,58 - - - 0,51 N/A 0,42 N/A
Hierarchical clustering -0,43 0,00 (0,00-0,00) 0,000 - 0,000 0,000 - 0,000 0 - 0 (cluster models: 0) 0,54 N/A 0,23 N/A
Single model 0,73 5,35 (0,38-75,99) 0,764 0,733 540 0,54 0,86 0,53 0,63
Group contribution -0,36 1,09 (0,10-12,34) 0,719 0,527 499 0,62 0,74 0,60 0,71
FDA 0,04 10,52 (0,00-0,00) 0,000 0,000 3 0,57 1,03 0,53 0,60
Nearest neighbor 1,02 0 - - 3 0,60 N/A 0,55 N/A

SMILES CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O

Method Predicted value Model statistics MAE (in log10)
External test set Training set
log BCF BCF No. of chemicals Entire set SC >= 0.5 Entire set SC >= 0.5
Consensus method 0,45 2,85 - - - 0,51 0,68 0,42 0,61
Hierarchical clustering -0,26 0,00 (0,00-0,00) 0,000 - 0,000 0,000 - 0,000 0 - 0 (cluster models: 0) 0,54 N/A 0,23 N/A
Single model 1,14 13,76 (0,90-209,78) 0,764 0,733 540 0,54 1,03 0,53 0,69
Group contribution N/A N/A 0,719 0,527 499 0,62 N/A 0,60 N/A
FDA 0,08 1,19 (0,19-7,45) 0,875 0,792 30 0,57 0,37 0,53 0,62
Nearest neighbor 0,77 5,87 - - 3 0,60 0,36 0,55 1,00

Legend:

MAE = mean absolute error

SC = similarity coefficient

r² = correlation coefficient

q² = leave one out correlation coefficient

Executive summary:

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

 

1.

Substance

CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O

CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O

2.

General information

 

2.1

Date of QPRF

June 02, 2017

2.2

QPRF author and contact details

BASF SE

3.

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

External test set:

Training set:

Consensus method

low

N/A

Hierarchical clustering

N/A

N/A

Single model

low

low

Group contribution

N/A

N/A

FDA

high

low

Nearest neighbor

high

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

Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
calculation (if not (Q)SAR)
Remarks:
estimated by calculation
Adequacy of study:
supporting study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Well documented QSAR model for prediction of BCF; the substance is (not) in the applicability domain of the model.
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:
no
Details on estimation of bioconcentration:
BASIS FOR CALCULATION OF BCF
- Estimation software: VEGA CAESAR v2.1.14 implemented in the VEGA tool v.1.1.1 (calculation core: v1.2.1)
- Result based on calculated log Pow of: 4.01 (calculated by VEGA: MLogP) CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O
- Result based on calculated log Pow of: 3.1 (calculated by VEGA: MLogP) CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O
Type:
BCF
Value:
57 L/kg
Remarks on result:
other: CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O, According to the model’s global AD index, the predicted compound is outside the Applicability Domain of the model. An expert analysis can be found in chapter "Overall remarks, attachments" (see attached QPRF documents).
Type:
BCF
Value:
23 L/kg
Remarks on result:
other: CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O, According to the model’s global AD index, the predicted compound is outside the Applicability Domain. An expert analysis can be found in chapter "Overall remarks, attachments" (see attached QPRF documents).
Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
calculation (if not (Q)SAR)
Remarks:
estimated by calculation
Adequacy of study:
supporting study
Study period:
2017
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Well documented QSAR model for prediction of BCF; the substance is (not) in the applicability domain of the model.
Principles of method if other than guideline:
The BCF is estimated based on log Kow. 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:
no
Details on estimation of bioconcentration:
BASIS FOR CALCULATION OF BCF
- Estimation software: VEGA Meylan v1.0.3 implemented in the VEGA tool v.1.1.1 (calculation core v1.2.1)
- Result based on calculated log Pow of: 5.75 (calculated by VEGA: Meylan/KOWWIN), CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O
- Result based on calculated log Pow of: 5.38 (calculated by VEGA: Meylan/KOWWIN), O=C(O)C=CC(=O)NCC(C)C(C)C(C)C(C)C(C)CC
Type:
BCF
Value:
6 L/kg
Remarks on result:
other: O=C(O)C=CC(=O)NCCCCCCCCCCCCC, According to the model’s global AD index, the predicted substance outside the Applicability Domain. An expert analysis can be found in chapter "Overall remarks, attachments - Attached background material".
Type:
BCF
Value:
6 L/kg
Remarks on result:
other: O=C(O)C=CC(=O)NCC(C)C(C)C(C)C(C)C(C)CC, According to the model’s global AD index, the predicted substance outside the Applicability Domain. An expert analysis can be found in chapter "Overall remarks, attachments - Attached background material".
Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
calculation (if not (Q)SAR)
Remarks:
estimated by calculation
Adequacy of study:
supporting study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: Well documented QSAR model for prediction of BCF; according to the model's application domain index, the substance [is in/could be out of/is out of] the applicability domain of the model.
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:
no
Details on estimation of bioconcentration:
BASIS FOR CALCULATION OF BCF
- Estimation software: BCF model (Read-Across/KNN) v1.1.0 implemented in VEGA v1.1.1
Type:
BCF
Value:
1.19 L/kg
Remarks on result:
other: CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O, according to the model's AD index, the substance is out of the applicability domain of the model. An expert analysis can be found in chapter "Overall remarks, attachments - Attached background material".
Type:
BCF
Value:
1.68 L/kg
Remarks on result:
other: CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O, according to the model's AD index, the substance is out of the applicability domain of the model. An expert analysis can be found in chapter "Overall remarks, attachments - Attached background material".

Description of key information

Significant accumulation in organisms is not to be expected.

Key value for chemical safety assessment

BCF (aquatic species):
295 L/kg ww

Additional information

There is no experimental data available on the bioaccumulative potential of the registration item, which is a UVCB substance.

Therefore, two molecules (highly branched versus not branched at all), representing the lower and the upper limit of the range of possible structures, respectively, were used to predict the potential for bioaccumulation of the registration item:

CCCCCCCCCCCCCNC(=O)/C=C\C(O)=O

CCC(C)C(C)C(C)C(C)C(C)CNC(=O)/C=C\C(O)=O

A variety of models have been used to address the information requirement for the registration item. Details about the individual estimations can be retrieved from the endpoint study records in this section. The results received from this BCF predictions ranged from 1.58 to 295 (including both representative structures). In a worst case approach, the upper limit of this range may be used to assess the potential for bioaccumulation of the UVCB. As this upper limit is clearly below the thresholds used for classification (500) and the screening assessment for the B criterion in the context of the PBT assessment (2000), it can be concluded that significant accumulation in organisms is not to be expected.