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EC number: 904-139-6 | CAS number: -
Biodegradation in water: screening tests
Administrative data
Link to relevant study record(s)
- Endpoint:
- biodegradation in water: ready biodegradability
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- January 15, 2018
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification
- Justification for type of information:
- The model is been assessed according to the OECD principles for the validation of QSAR, to generate a transparent, understandable, reproducible and verifiable result.
- Qualifier:
- equivalent or similar to guideline
- Guideline:
- other: ECHA Guidance on information requirements and chemical safety assessment - Chapter R.06: QSARs and grouping of chemicals
- Principles of method if other than guideline:
- Battery algorithm
The models are made in three independent systems: CASE Ultra (CU), Leadscope Predictive Data Miner (LS) and SciQSAR (SQ). Based on predictions from each of the applied systems, a battery prediction is made using a so-called battery algorithm. The battery approach can give more reliable predictions and can also expand the applicability domain, which was shown in a previous pilot project including 32 different models and the three systems mentioned above (not published).
For the biodegradability endpoint, QSAR predictions are made in each of the independent QSAR model systems and combined into a battery prediction by using the criteria shown in the following table. The first column shows the total number of predictions (positive/negative) in domain. The next two columns show the number of positive and negative predictions, respectively. The final battery prediction based on the individual predictions is shown in the fourth column.
Total POS/NEG POS NEG Battery prediction (a) Remarks
in domain in domain in domain
3 3 0 POS_IN
3 0 3 NEG_IN
3 2 1 POS_IN
3 1 2 INC_OUT EXCEPT when CU and LS are both NEG_IN,
or (see remark) in this case the battery call is NEG_IN
NEG_IN
(a) POS, positive; NEG, negative; INC, inconclusive; IN, inside applicability domain; OUT, outside applicability domain.
(b) Less weight is put on an SQ POS compared to LS or CU POS in cases where LS and CU agree on a NEG in AD prediction, because SQ in many cases has lower specificity than LS and CU. - Parameter:
- other: Not ready biodegradability (QSAR/QSPR)
- Remarks on result:
- readily biodegradable based on QSAR/QSPR prediction
- Validity criteria fulfilled:
- yes
- Interpretation of results:
- readily biodegradable
- Conclusions:
- According to the result of the Battery algorithm, applied on CASE Ultra, Leadscope Predictive Data Miner and SciQSAR models, 1,2-diethyl citrate was found to be readily biodegradable in water.
- Executive summary:
According to the result of the Battery algorithm, applied on CASE Ultra, Leadscope Predictive Data Miner and SciQSAR models, 1,2-diethyl citrate was found to be readily biodegradable in water.
- Endpoint:
- biodegradation in water: ready biodegradability
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- January 15, 2018
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification
- Justification for type of information:
- The model is been assessed according to the OECD principles for the validation of QSAR, to generate a transparent, understandable, reproducible and verifiable result.
- Qualifier:
- equivalent or similar to guideline
- Guideline:
- other: ECHA Guidance on information requirements and chemical safety assessment - Chapter R.06: QSARs and grouping of chemicals
- Principles of method if other than guideline:
- Battery algorithm
The models are made in three independent systems: CASE Ultra (CU), Leadscope Predictive Data Miner (LS) and SciQSAR (SQ). Based on predictions from each of the applied systems, a battery prediction is made using a so-called battery algorithm. The battery approach can give more reliable predictions and can also expand the applicability domain, which was shown in a previous pilot project including 32 different models and the three systems mentioned above (not published).
For the biodegradability endpoint, QSAR predictions are made in each of the independent QSAR model systems and combined into a battery prediction by using the criteria shown in the following table. The first column shows the total number of predictions (positive/negative) in domain. The next two columns show the number of positive and negative predictions, respectively. The final battery prediction based on the individual predictions is shown in the fourth column.
Total POS/NEG POS NEG Battery prediction (a) Remarks
in domain in domain in domain
3 3 0 POS_IN
3 0 3 NEG_IN
3 2 1 POS_IN
3 1 2 INC_OUT EXCEPT when CU and LS are both NEG_IN,
or (see remark) in this case the battery call is NEG_IN
NEG_IN
(a) POS, positive; NEG, negative; INC, inconclusive; IN, inside applicability domain; OUT, outside applicability domain.
(b) Less weight is put on an SQ POS compared to LS or CU POS in cases where LS and CU agree on a NEG in AD prediction, because SQ in many cases has lower specificity than LS and CU. - Parameter:
- other: Not ready biodegradability (QSAR/QSPR)
- Remarks on result:
- readily biodegradable based on QSAR/QSPR prediction
- Validity criteria fulfilled:
- yes
- Interpretation of results:
- readily biodegradable
- Conclusions:
- According to the result of the Battery algorithm, applied on CASE Ultra, Leadscope Predictive Data Miner and SciQSAR models, 1-ethyl citrate was found to be readily biodegradable in water.
- Executive summary:
According to the result of the Battery algorithm, applied on CASE Ultra, Leadscope Predictive Data Miner and SciQSAR models, 1-ethyl citrate was found to be readily biodegradable in water.
- Endpoint:
- biodegradation in water: ready biodegradability
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- January 15, 2018
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification
- Justification for type of information:
- The model is been assessed according to the OECD principles for the validation of QSAR, to generate a transparent, understandable, reproducible and verifiable result.
- Qualifier:
- equivalent or similar to guideline
- Guideline:
- other: ECHA Guidance on information requirements and chemical safety assessment - Chapter R.06: QSARs and grouping of chemicals
- Principles of method if other than guideline:
- Battery algorithm
The models are made in three independent systems: CASE Ultra (CU), Leadscope Predictive Data Miner (LS) and SciQSAR (SQ). Based on predictions from each of the applied systems, a battery prediction is made using a so-called battery algorithm. The battery approach can give more reliable predictions and can also expand the applicability domain, which was shown in a previous pilot project including 32 different models and the three systems mentioned above (not published).
For the biodegradability endpoint, QSAR predictions are made in each of the independent QSAR model systems and combined into a battery prediction by using the criteria shown in the following table. The first column shows the total number of predictions (positive/negative) in domain. The next two columns show the number of positive and negative predictions, respectively. The final battery prediction based on the individual predictions is shown in the fourth column.
Total POS/NEG POS NEG Battery prediction (a) Remarks
in domain in domain in domain
3 3 0 POS_IN
3 0 3 NEG_IN
3 2 1 POS_IN
3 1 2 INC_OUT EXCEPT when CU and LS are both NEG_IN,
or (see remark) in this case the battery call is NEG_IN
NEG_IN
(a) POS, positive; NEG, negative; INC, inconclusive; IN, inside applicability domain; OUT, outside applicability domain.
(b) Less weight is put on an SQ POS compared to LS or CU POS in cases where LS and CU agree on a NEG in AD prediction, because SQ in many cases has lower specificity than LS and CU. - Parameter:
- other: Not ready biodegradability (QSAR/QSPR)
- Remarks on result:
- readily biodegradable based on QSAR/QSPR prediction
- Validity criteria fulfilled:
- yes
- Interpretation of results:
- readily biodegradable
- Conclusions:
- According to the result of the Battery algorithm, applied on CASE Ultra, Leadscope Predictive Data Miner and SciQSAR models, triethyl citrate was found to be readily biodegradable in water.
- Executive summary:
According to the result of the Battery algorithm, applied on CASE Ultra, Leadscope Predictive Data Miner and SciQSAR models, triethyl citrate was found to be readily biodegradable in water.
Referenceopen allclose all
Substance |
DK |
Exp |
Battery |
CASE Ultra |
Leadscope |
SciQSAR |
Comp. #1 Diethyl citrate |
Not Ready Biodegradability (POS=Not Ready) |
|
NEG_IN |
NEG_IN |
NEG_IN |
NEG_IN |
Substance |
DK |
Exp |
Battery |
CASE Ultra |
Leadscope |
SciQSAR |
Comp. #2 Monoethyl citrate |
Not Ready Biodegradability (POS=Not Ready) |
|
NEG_IN |
NEG_IN |
NEG_IN |
NEG_IN |
Substance |
DK |
Exp |
Battery |
CASE Ultra |
Leadscope |
SciQSAR |
Comp. #1 Triethyl citrate |
Not Ready Biodegradability (POS=Not Ready) |
|
NEG_IN |
NEG_IN |
NEG_IN |
NEG_IN |
Description of key information
Biodegradation: readily biodegradable
Key value for chemical safety assessment
- Biodegradation in water:
- readily biodegradable
- Type of water:
- freshwater
Additional information
The screening test inherent to the biodegradability of diethyl citrate tecnical was evaluated using several (Q)SAR models on the costituents of the above substance.
All the results indicate that diethyl citrate technical is expected to be readily biodegradable.
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