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Diss Factsheets

Administrative data

Endpoint:
bioaccumulation in aquatic species: fish
Type of information:
(Q)SAR
Adequacy of study:
other information
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 limited documentation / justification

Data source

Reference
Reference Type:
other: QSAR model
Title:
OPERA V1.5
Year:
2020
Bibliographic source:
OPERA-model for Bioconcentration

Materials and methods

Test guideline
Qualifier:
according to guideline
Guideline:
other: ECHA guidance on information requirements and chemical safety assessment Chapter R.6: QSARs and grouping of chemicals.
Principles of method if other than guideline:
[1]An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modeling. 2016. Kamel Mansouri, Chris M. Grulke, Ann M. Richard, Richard S. Judson and Antony J. Williams. SAR & QSAR in Environ. Res; Vol. 27 , Iss. 11,2016. doi:
10.1080/1062936X.2016.1253611.
[2]OPERA: A free and open source QSAR tool for physicochemical properties and environmental fate predictions. Kamel Mansouri, Chris Grulke, Richard Judson, Antony Williams, Journal of Cheminformatics (2017)
[3]PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints. Chun Wei Yap. (2011). J. Comput. Chem., 32: 1466–1474. doi:10.1002/jcc.21707 http://onlinelibrary.wiley.com/doi/10.1002/jcc.21707/abstract
[4]A KNIME workflow for chemical structures curation and standardization in QSAR modeling. Kamel Mansouri, Sherif Farag, Jayaram Kancherla, Regina Politi, Eugene Muratov, Denis Fourches, Nikolai Nikolov, Eva Bay Wedebay, Christopher Grulke, Ann Richard, Richard Judson, Alexander Tropsha. (in preparation)
[5]The influence of data curation on QSAR Modeling – examining issues of quality versus quantity of data (SOT). Williams, A., K. Mansouri, A. Richard, AND C. Grulke. Presented at Society of Toxicology, New Orleans, LA, March 13 - 17, 2016. https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=311418
[6]An Online Prediction Platform to Support the Environmental Sciences (American Chemical Society). Richard, A., C. Grulke, K. Mansouri, R. Judson, AND A. Williams. Presented at ACS Spring Meeting, San Diego, CA, March 13 - 17, 2016. https://cfpub.epa.gov/si/si_public_record_Report.cfm?dirEntryId=311655
[7]The importance of data curation on QSAR Modeling: PHYSPROP open data as a case study. Kamel Mansouri, Christopher Grulke Ann Richard Richard Judson Antony Williams. Presented at QSAR2016 14 June 2016, Miami, FL http://www.qsar2016.com/program
[8]Mansouri K. (2017) OPERA: A QSAR tool for physicochemical properties and environmental fate predictions. doi: 10.6084/m9.figshare.4836428 https://figshare.com/articles/OPERA_A_QSAR_tool_for_physicochemical_properties_and_environm ental_fate_predictions/4836428

Test material

Constituent 1
Chemical structure
Reference substance name:
Dimethyl succinate
EC Number:
203-419-9
EC Name:
Dimethyl succinate
Cas Number:
106-65-0
Molecular formula:
C6H10O4
IUPAC Name:
dimethyl succinate
Specific details on test material used for the study:
COC(=O)CCC(=O)OC

Results and discussion

Bioaccumulation factor
Type:
BCF
Value:
2.93 dimensionless
Remarks on result:
other: QSAR prediction

Any other information on results incl. tables

The molecule is included in the applicability domain of the model:

Global applicability domain: Inside
Local applicability domain index: 0.484
Confidence level: 0.592

Applicant's summary and conclusion

Validity criteria fulfilled:
yes
Conclusions:
The substance has a BCF of 2.93.