Registration Dossier

Environmental fate & pathways

Bioaccumulation: aquatic / sediment

Currently viewing:

Administrative data

Link to relevant study record(s)

Description of key information

not bioaccumulative

Key value for chemical safety assessment

Additional information

The bioaccumulative potential of the substance was determined in an experimental study conducted in 2001 according to OECD TG 305 (aqueous exposure). Furthermore, information from different QSAR models (Table 1) were used as supporting information.

Additionally, the relevant metabolites identified under section 5.2 were assessed with information from OASIS Catalogic v5.11.19, BCF base-line model v.02.09 and further lines of evidence, e.g. logKow, general polarity.

 

Experimental study

The experimental study was conducted based on the guidelines OECD 305. The test substance was measured using HPLC in water and the fish without growth or lipid correction. As the steady-state-BCF was determined, no depuration was conducted.

The fish were exposed to two concentrations of test substance at 0.02 and 0.2 mg/L in a flow-through-system for an uptake period of 28 days. Over the entire test all water quality parameters were maintained within acceptable limits. No toxic effects (i.e. mortality) or changes in behavior or appearance were observed in the test treatment organisms in comparison to the control group. Test substance concentrations in fish and water were determined during uptake by measuring the test substance using HPLC. The concentrations of test substance in water during the test were within 0.184 -0.197 mg/L (high concentration level) and 0.0195 -0.0213 mg/L (low concentration level).

The measured values in fish tissues were within ±20% of each other from days 14 – 28, thus steady state concentration was reached by day 21 according to criterion in OECD 305. The BCFss was <5 (high concentration level) and < 49 (low concentration level) as estimated based on measurements from days 14, 21, and 28. The low concentration level is within the range of water solubility, (see IUCLID chapter 4.8).

 

QSAR calculations

As supporting information several QSAR models were used to calculate the BCF (Table 1). The results and further information on the reliability (e.g. applicability domain) can be found in Table 2.As the substance is a mixture of the main component itself and several impurities, the main impurity and the main component were evaluated to exclude any possible hazard based on bioaccumulation for the substance.

 Table 1: Models used for QSAR

Software

Model

Sub-model

OASIS Catalogic v5.13.1

BCF base-line model v.03.10

 

EPISuite v4.11

BCFBAF model v3.01

Regression-based estimate

 

 

Arnot-Gobas BCF & BAF methods

VEGA v1.1.3

CAESAR v2.1.14

 

 

Meylan v1.0.3

 

 

KNN/Read-Across v1.1.0

 

 

 Table 2: Results and further details of the supporting QSAR estimations

 Model 

Main

Component

Main

Impurity

 

Results [L/kg]

Remarks

Results [L/kg]

Remarks

OASIS Catalogic v5.13.1; BCF base-line model v.03.10

12.88

 

[BCFmax = 6223]

- all mitigating factors applied

- within parameter and mechanistic domain

- outside structural fragment domain

7.76

 

[BCFmax = 9.14]

- all mitigating factors applied

- within parameter and mechanistic domain

- outside structural fragment domain

EPISuite v4.11; BCFBAF model v3.01; regression-based estimate

879

- within applicability domain

3.16

- within applicability domain

EPISuite v4.11; BCFBAF model v3.01; Arnot-Gobas BCF & BAF methods

upper trophic level

157

-including biotransformation

- within the applicability domain

0.893

-including biotransformation

- within the applicability domain

- the amount of CH2 (linear) fragments exceeded the maximum number of instances in the training set

VEGA v1.1.3; CAESAR v2.1.14

3.47

- outside of the applicability domain

1.02

- outside of the applicability domain

VEGA v1.1.3; Meylan v1.0.3

690

- outside of the applicability domain

3.16

- outside of the applicability domain

VEGA v1.1.3; KNN/Read-Across v1.1.0

4.57

- outside of the applicability domain

27.54

- outside of the applicability domain

 

 Table 2: Other mitigating factors

Property

Main

component

Main

impurity

 

Value

Remarks

Value

Remarks

Average maximum diameter in nm

2.27

(1.64 – 3.55)

-calculated using OASIS Catalogic v5.13.1; BCF base-line model v.03.10

3.26

(2.27 – 5.6)

-calculated using OASIS Catalogic v5.13.1; BCF base-line model v.03.10

log Kow

8.19

-calculated using OASIS Catalogic v5.13.1; BCF base-line model v.03.10

17.05

-calculated using OASIS Catalogic v5.13.1; BCF base-line model v.03.10

 

 


 

Main Component

The BCF base-line model v.03.10 integrated in OASIS Catalogic v5.13.1 reflects the current understanding of the process by which lipophilic organic chemicals are bioaccumulated in fish through the respiratory organs only. In the present case, the substance fulfills the general properties requirements, i.e. its logKow, molecular weight and water solubility are within the ranges of the model. Furthermore, the substance is within the mechanistic domain, i.e. it is expected to be taken up by passive diffusion only. However, the substance is not in the structural domain. Only 64% of its fragments could be found in correctly predicted training set chemicals. The remaining 36% are not present in the training set chemicals. If a chemical is out of at least one of the specified layers mentioned above, it will be classified as out of the applicability domain. This classification means that the prediction falls in the extrapolation space but the prediction still could be reliable. The experimentally determined BCFss of <5 resp. <49 L/kg almost perfectly matches the predicted BCF of 12.88 L/kg. Therefore, although the predicted result falls in the extrapolation space of the model the result is regarded as highly reliable.

EPISuite v4.11 includes the BCFBAF model v3.01 which encompasses two BCF estimation methodologies. The regression-based model based on the work from Meylan et al. (1997 and 1999) derived a BCF value of 879 L/kg based on a calculated logKow of 8.19 (an experimental value for logKow is not available). The substance was within the applicability domain of the model (molecular weight and logKow ranges). This result is far above the experimentally derived value which might be due to the decreasing correlation of the logKow and the logBCF for substances with higher logKow values. Furthermore, biotransformation is not considered in this submodel. However, degradation data show the potential of the substance to be transformed. According to ECHA’s Guidance on Information Requirements and Chemical Safety Assessment, Chapter R.11: PBT/vPvB assessment draft version 3.0 (March 2017), the relationship between logKow and logBCF decreases at very high logKow (>6). The present compound has a calculated logKow of 8.19. Therefore, even if the main component is within the applicability domain of the model the result is regarded as not reliable.

The model based on the works of Arnot and Gobas (2003) takes the biotransformation rate of the compound into account and calculates BCF values for the upper, mid and lower trophic levels. The values for the present compound range from 157 (upper trophic level) to 239.8 (lower trophic level). The model assumes default lipid contents of 10.7%, 6.85% and 5.98% for the upper, middle and lower trophic levels, respectively whereas experimentally derived BCF values are normalised to 5% lipid content.

The current VEGA package v1.1.3 comprises three different models. (1) CAESAR v2.1.14, (2) Meylan v1.0.3 and (3) KNN/Read-Across v1.1.0. The CAESAR model predicted a BCF of 3.48 but the substance was out of the applicability domain. Nevertheless, the model was used as a supporting information for the assessment of the bioaccumulative potential.

The Meylan model is a reconstruction of the regression-based model integrated in EPISuite (Meylan et al. 1997, 1999). The model predicted a BCF of 690 but the substance was out of the applicability domain. The result is not regarded as reliable (see regression-based model integrated in EPISuite).

The KNN/Read-Across model predicted a BCF of 4.57 L/kg but the substance is out of the applicability domain. Nevertheless, the model was used as a supporting information for the assessment of the bioaccumulative potential.

The size of the molecule can be used to strengthen the evidence for a limited bioaccumulative potential of a substance. A parameter that directly reflects the molecular size of a substance is the average maximum diameter (DiamMax average). Very bulky molecules will less easily pass through the cell membranes. In ECHA’s Guidance on Information Requirements and Chemical Safety Assessment, Chapter R.11: PBT/vPvB assessment version 3.0 (June 2017), it is stated that there is evidence that compounds with a DiamMax average larger than 1.7 nm and a molecular weight of > 1100g/mol the BCF will be less than 2000 and with a molecular weight of 700g/mol the BCF will be less than 5000. The main component has a DiamMax average of 2.27nm but a molecular weight of < 700g/mol. However, based on the DiamMax average, the molecular size is assumed to be an important factor for limited bioavaibility of the substance.

Another line of evidence is the result of the toxicological studies, whereas based on the molecular size, the absence of adverse findings in toxicity studies and the presence of functional groups for metabolism a potential for bioaccumulation is unlikely.

As the uptake of an organic substance in aquatic organisms is driven by its hydrophobicity, the logKow is a useful criterion to conclude on the bioaccumulative potential. According to ECHA’s R.11 guidance at logKow values between 4 and 5 the logBCF increases linearly with logKow. However, at very high logKow values (>6) a decreasing relationship between the two parameters is observed. Thus, a direct conclusion on the bioaccumulative potential based on the logKow is not possible for the present substance. Furthermore, as mentioned above the decreasing relationship between the two parameters is probably the reason why some of the QSAR models predicted very high BCF values. Another uptake mechanisms than passive diffusion driven by hydrophobicity is not expected for the present substance.

Based on the available data in this weight of evidence approach with consideration of the experimental data it can be concluded that the BCF of the main component is < 100.

 

Main Impurity

The BCF base-line model v.03.10 integrated in OASIS Catalogic v5.13.1 reflects the current understanding of the process by which lipophilic organic chemicals are bioaccumulated in fish through the respiratory organs only. In the present case, the substance fulfills the general properties requirements, i.e. its logKow, molecular weight and water solubility are within the ranges of the model. Furthermore, the substance is within the mechanistic domain, i.e. it is expected to be taken up by passive diffusion only. However, the substance is not in the structural domain. Only 76% of its fragments could be found in correctly predicted training set chemicals. The remaining 24% are not present in the training set chemicals. If a chemical is out of at least one of the specified layers mentioned above, it will be classified as out of the applicability domain. This classification means that the prediction falls in the extrapolation space but the prediction still could be reliable. Therefore, although the predicted result falls in the extrapolation space of the model the result is regarded as highly reliable.

EPISuite v4.11 includes the BCFBAF model v3.01 which encompasses two BCF estimation methodologies. The regression-based model based on the work from Meylan et al. (1997 and 1999) derived a BCF value of 3.16 L/kg based on a calculated logKow of 17 (an experimental value for logKow is not available). The substance was within the applicability domain of the model (molecular weight and logKow ranges). According to ECHA’s Guidance on Information Requirements and Chemical Safety Assessment, Chapter R.11: PBT/vPvB assessment version 3.0 (June 2017), the relationship between logKow and logBCF decreases at very high logKow (>6). The present compound has a calculated logKow of 17.

The model based on the works of Arnot and Gobas (2003) takes the biotransformation rate of the compound into account and calculates BCF values for the upper, mid and lower trophic levels. The values for the present compound range from 0.893 (upper trophic level) to 0.9462 (lower trophic level). The amount of CH2 (linear) fragments exceeded the maximum number of instances in the training set, nevertheless the model was used for estimation as it clearly indicates the low potential for bioaccumulation of the main impurity.

The current VEGA package v1.1.3 comprises three different models. (1) CAESAR v2.1.14, (2) Meylan v1.0.3 and (3) KNN/Read-Across v1.1.0. The CAESAR model predicted a BCF of 1.02 but the main impurity was out of the applicability domain. Nevertheless, the model was used as a supporting information for the assessment of the bioaccumulative potential.

The Meylan model is a reconstruction of the regression-based model integrated in EPISuite (Meylan et al. 1997, 1999). The model predicted a BCF of 3.16 but the substance was out of the applicability domain (see regression-based model integrated in EPISuite).

The KNN/Read-Across model predicted a BCF of 27.54 L/kg but the substance is out of the applicability domain. Nevertheless, the model was used as a supporting information for the assessment of the bioaccumulative potential.

The size of the molecule can be used to strengthen the evidence for a limited bioaccumulative potential of a substance. A parameter that directly reflects the molecular size of a substance is the average maximum diameter (DiamMax average). Very bulky molecules will less easily pass through the cell membranes. In ECHA’s Guidance on Information Requirements and Chemical Safety Assessment, Chapter R.11: PBT/vPvB assessment version 3.0 (June 2017), it is stated that

that there is evidence that compounds with a DiamMax average larger than 1.7 nm and a molecular weight of > 1100g/mol the BCF will be less than 2000 and with a molecular weight of 700g/mol the BCF will be less than 5000. The main impurity has a DiamMax average of 3.26 nm but a molecular weight of < 1100g/mol. Therefore, the molecular size is assumed to be an important factor for limited bioavaibility of the substance.

As the uptake of an organic substance in aquatic organisms is driven by its hydrophobicity the logKow is a useful criterion to conclude on the bioaccumulative potential. According to ECHA’s R.11 guidance at logKow values between 4 and 5 the logBCF increases linearly with logKow. However, at very high logKow values (>6) a decreasing relationship between the two parameters is observed. Thus, a direct conclusion on the bioaccumulative potential based on the logKow is not possible for the present substance. Furthermore, as mentioned above the decreasing relationship between the two parameters is probably the reason why some of the QSAR models predicted very high BCF values. Another uptake mechanisms than passive diffusion driven by hydrophobicity is not expected for the present substance.

No experimental data on bioaccumulation potential is avaialable. All QSAR data show BCF values of < 50. The main impurity is out of the applicability domain of some of the models. However, based on the available data in this weight of evidence approach it can be concluded that the BCF of the main impurity is < 100

Conclusion

The substance including its main component und main impurity is clearly not bioaccumulative. In a valid and reliable experimental study a BCF value of <49 L/kg was determined. This result could be confirmed by different QSAR predictions which predicted BCF values in the same range. Assessing all lines of evidence it can be concluded that the substance is not bioaccumulative. The BCF of the substance (including main impurity) is clearly below 100, respectively.

 

Metabolites

In addition to the main component and the main impurity the relevant metabolites were assessed regarding their potential to bioaccumulate.In the absence of experimental data, the metabolites for main component and main impurity were identified with CATALOGIC 301C v11.15 integrated in OASIS Catalogic v5.13.1. Only metabolites at the PBT-relevant quantity of more than 0.1% were taken into account. Out of these metabolites only metabolites with a logKow4 have been further taken into account. According to ECHAs Guidance on Information Requirements and Chemical Safety Assessment, Chapter R.11: PBT/vPvB assessment draft version 3.0 (March 2017), for the PBT and vPvB assessment a screening threshold value has been established, which is logKow greater than 4.5. Therefore, the decision to take only metabolites with a logKow4 presents a reasonable worst case. Ultimately, 4 relevant metabolites could be identified for the main impurity which were further evaluated. All of these 4 identified metabolites with logKow4.5 and a quantity0.1 % showed a very high degree of potential biodegradation (86 – 100 %) predicted by CATALOGIC 301C v11.15. Therefore, none of the relevant metabolites is regarded to be bioaccumulative (see IUCLID chapter 5.2.1 for further information).

For the main component no relevant metabolites with a logKow >= 4 could be identified.

Based on these results a bioaccumulation potential of the determined metabolites can be excluded and no further assessment is performed.

 

 References

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).

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.

Dimitrov S, Dimitrova N, Parkerton T, Comber M, Bonnell M and Mekenyan O. “Base-line model for identifying the bioaccumulation potential of chemicals”, SAR and QSAR in Environmental Research 16(6), 2005