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Environmental fate & pathways

Bioaccumulation: aquatic / sediment

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Reference
Endpoint:
bioaccumulation: aquatic / sediment
Type of information:
(Q)SAR
Adequacy of study:
key study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification
Justification for type of information:
1. SOFTWARE
Individual model BCFBAF included in the Estimation Programs Interface (EPI) Suite.

2. MODEL (incl. version number)
BCFBAF v3.01 included in EPISuite v 4.11, 2000 - 2012

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS NUMBER was entered in the initial data entry screen. An experimental determined log Kow value was provided prior to estimation.
A searchable database of CAS RNs and corresponding SMILES structures are provided within the KOWWIN program. CAS RNs are available for approximately 112,000 organic chemicals. If a CAS RN is not available, a SMILES notation can be directly entered by the user. Alternatively, logKow values can be manually entered if available. The correction factors are linked to the presence of certain structural fragments or functional groups.

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
a. Defined endpoint: Bioconcentration factor (BCF). As a coefficient the logBCF is given without unit. The BCF can be given with L/kg wet wt.
b. Explicit algorithm (OECD Principle 2): The BCF is usually estimated from regression equations of the general form logBCF= a logKow + b, whereas a and b are empirically determined constants and Kow is the n octanol/water partition coefficient. Therefore, logBCF values for the non-ionic and ionics were plotted separately against the respective logKow values yielding a linear relationship for certain logKow ranges. Furthermore, compounds sharing certain structural features were identified resulting in residuals that were relatively consistent in sing and magnitude. On this basis several compound classes were identified that seemed amenable to derivation of correction factors.

Non-ionic compounds:
(i) For LogKow 1.0 to 7.0 the derived QSAR estimation equation is:
Log BCF= 0.6598 LogKow - 0.333 + Σ correction factors
(ii) For LogKow > 7.0 the derived QSAR estimation equation is:
Log BCF= -0.49 LogKow + 7.554 + Σ correction factors
(iii) For LogKow < 1.0 the derived QSAR estimation equation is:
All compounds with a logKow of less than 1.0 are assigned an estimated log BCF of 0.50.

Ionic compounds:
logKow < 5.0: log BCF= 0.50
logKow 5.0 to 6.0: log BCF= 0.75
logKow 6.0 to 7.0: log BCF= 1.75
logKow 7.0 to 9.0: log BCF= 1.00
logKow > 9.0: log BCF= 0.50

Ionic compounds include carboxylic acids, sulfonic acids and salts of sulfonic acids, and charged nitrogen compounds (nitrogen with a +5 valence such as quaternary ammonium compounds). All other compounds are classified as non-ionic.
Metals (tin and mercury), long chain alkyls and aromatic azo compounds require special treatment (see Meylan et al., 1999).
For ionic substances with long alkyl chains (≥ 11 carbons) a general log BCF of 1.85 was assigned by the program.

c. Applicability domain: The minimum and maximum values for molecular weight are the following:
Training Set Molecular Weight:
Minimum MW (Non-Ionic): 68.08
Maximum MW (Non-Ionic): 959.17
Average MW (Non-Ionic): 513.63

Minimum MW (Ionic): 102.13
Maximum MW (Ionic): 991.80
Average MW (Ionic): 546.97

The minimum and maximum values for logKow are the following:
Training Set logKow:
Minimum LogKow (Non-Ionic): -1.37
Maximum LogKow (Non-Ionic): 11.26

Minimum LogKow (Ionic): -6.50
Maximum LogKow (Ionic): 7.86

d. Statistics for goodness-of-fit:
number in dataset = 527
correlation coef (r^2) = 0.833
standard deviation = 0.502
average deviation = 0.382

e. Predictivity – Statistics obtained by external validation:
number in dataset = 158
correlation coef (r2) = 0.82
standard deviation = 0.59
average deviation = 0.46

f. Mechanistic interpretation: The BCF is an inherent property used to describe the accumulation of a substance dissolved in water by an aquatic organism. The BCFBAF program estimates BCF of an organic compound using the compound's log octanol-water partition coefficient (Kow).
Measured BCFs and other experimental details were collected and analysed to derive subsets of data on non-ionic, ionic, aromatic and azo compounds, tin and mercury compounds. Because of the deviation from rectilinearity, different models were developed for different log Kow ranges, and a set of 12 correction factors and rules were introduced to improve the accuracy of the BCF predictions.

g. The uncertainty of the prediction (OECD principle 4): The rules applied for estimating the BCF of Solvent violet 59 appear appropriate. An individual uncertainty for the investigated substance is not available.

h. The chemical and biological mechanisms according to the model underpinning the predicted result (OECD principle 5): Not applicable.

i. Limits of applicability: Model predictions may be highly uncertain for chemicals that have estimated log KOW values > 9. The model is not recommended at this time for chemicals that appreciably ionize, for pigments and dyes, or for perfluorinated substances.

5. APPLICABILITY DOMAIN
a. Descriptor Domains:
i. log Kow: With a log Kow value of 5.3 (exp.), the substance is within the range of the training set (Non-Ionics: -1.37 – 11.26).
ii. Molecular weight: With a molecular weight of 422.44 g/mole the substance is within the range of the training set (Non-Ionics 68.08 – 959.17).
iii. Structural fragment domain: Not applicable as the BCF is not estimated on the basis of fragments.
iv. Mechanism domain: NO INFORMATION AVAILABLE
v. Metabolic domain: NOT RELEVANT
b. Structural analogues: Not relevant as the BCF is not estimated based on structural fragments.

6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used for regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value may be used to fill data gaps needed for hazard and risk assessment.
c. Outcome: The estimation of the bioconcentration factor (BCF) yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes.
Guideline:
other: REACH guidance on QSARs R.6, May 2008
Deviations:
not applicable
Principles of method if other than guideline:
Calculated with BCF Program BCFBAF v.3.01 included in the Estimation Programs Interface (EPI)-Suite. The estimation methodology is based on the chemical structure of an organic compound and its log octanol-water partition coefficient (log Kow). Depending on chemical structure, structural correction factors are applied.
GLP compliance:
no
Radiolabelling:
no
Test organisms (species):
other: none, estimated by calculation
Key result
Type:
BCF
Value:
379.2 L/kg
Basis:
other: calculation

Any decomposition of the substance in water is not considered by the program.

Validity of model:

- Defined endpoint: bioconcentration of a substance in biota

- Unambiguous algorithm: linear regression QSAR. Because of the deviation from rectilinearity, different models were developed for different log Kow ranges. Metals (tin and mercury), long chain alkyls and aromatic azo compounds are specially treated.

- Applicability domain: the model is applicable to ionic as well as non-ionic compounds. It is applicable to substances with a logKow in the following range: -6.50 to 7.86 (ionic compounds) and -1.37 to 11.26 (non-ionic compounds). Applicable to substances with a molecular weight in the following range: 102.13 to 991.80 g/mole (ionic substances) and 68.08 and 959.17 g/mole (non-ionic compounds). ). Model predictions may be highly uncertain for chemicals that have estimated logKow values > 9. The model is not recommended at this time for chemicals that appreciably ionize, for pigments and dyes, or for perfluorinated substances.

- Statistical characteristics:

number in dataset = 527

correlation coef (r2) = 0.833

standard deviation = 0.502

- Mechanistic interpretation: The BCF is an inherent property used to describe the accumulation of a substance dissolved in water by an aquatic organism based on the lipophilicity of the compound.

Adequacy of prediction: Solvent violet 59 falls within the applicability domain described above and, therefore, the predicted value can be considered reliable taking into account that the standard deviation error of prediction of the external test set is 0.59 (logBCF). Considering that error, the predicted value is not above or close to the criterion to consider a substance as potential bioaccumulative.

Conclusions:
The bioaccumulation factor (BCF) of Solvent violet 59 was estimated to be 379 L/kg wet-wt sing the BCFBAF model included in the EPI-Suite Programm concluding that the substance has a low potential to bioaccumulate in biota.
Executive summary:

The bioaccumulation factor (BCF) of Solvent violet 59 was estimated to be 379 L/kg wet-wt sing the BCFBAF model included in the EPI-Suite Programm concluding that the substance has a low potential to bioaccumulate in biota. Within the scope of the Persistency-Bioaccumulation-Toxicity (PBT)-Assessment, the substance does not fullfil the B-criterion. Solvent violet 59 falls within the applicability domain described above and, therefore, the predicted value can be considered reliable.

Description of key information

The bioaccumulation factor (BCF) of Solvent violet 59 was estimated to be 379 L/kg wet-wt using the BCFBAF model included in the EPI-Suite Programm concluding that the substance has a low potential to bioaccumulate in biota.

Key value for chemical safety assessment

BCF (aquatic species):
379 L/kg ww

Additional information