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Diss Factsheets

Administrative data

Endpoint:
carcinogenicity, other
Remarks:
Qualitative prediction
Type of information:
(Q)SAR
Remarks:
CAESAR
Adequacy of study:
weight of evidence
Study period:
April 2016
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification

Data source

Reference
Reference Type:
other: QSAR models (27 models)
Title:
VEGA 1.1.1
Author:
Istituto di Ricerche Farmacologiche Mario Negri (Laboratory of Environmental Chemistry and Toxicology) and Kode srl
Year:
2015
Bibliographic source:
CAESAR project, EPA’s T.E.S.T. Software, DEMETRA project, EPISuite, Istituto di Ricerche Farmacologiche Mario Negri, ISS - ToxTree,

Materials and methods

Test guideline
Qualifier:
according to guideline
Guideline:
other: CAESAR
Version / remarks:
Qualitative prediction
Principles of method if other than guideline:
The model has been built as a Counter Propagation Artificial Neural Network (CP ANN). The neural network output consists of two values labeled as Positive and Non-Positive, both in the range [0,1] and with sum equal to 1; they represent how much the neuron in which the predicted compound falls belongs to the class of carcinogenic or non-carcinogenic compounds. The higher between these two values leads to the prediction. Full reference and details of the used formulas can be found in: Fjodorova N., Vračko M., Novič M., Roncaglioni A. and Benfenati E. New public QSAR model for carcinogenicity. Chemistry Central Journal (2010), 4 (Suppl 1):S3
The descriptors used by the CPANN are the following:
- PW5: Path/walk 5 - Randic shape index
- D/Dr6: Distance/detour ring index of order 6
- MATS2: Moran autocorrelation - lag 2/weighted by atomic polarizabilities
- EEig10: Eigenvalue 10 from edge adj. matrix weighted by edge degrees
- ESpm11: Spectral moment 11 from edge adj. matrix weighted by edge degrees
- ESpm9: Spectral moment 09 from edge adj. matrix weighted by dipole moments
- GGI2: Topological charge index of order 2
- JGI6: Mean topological charge index of order 6
- nRNNOx: Number of N-nitroso groups (aliphatic)
- nPO4: Number of phosphates/thiophosphates
- N_067: Number of Al2-NH atom centered fragments
- N_078: Number of Ar-N = X/X-N = X atom centered fragments
The descriptors were calculated, in the original model, by means of dragonX software and are now entirely calculated by an in-house software module in which they are implemented as described in: R. Todeschini and V. Consonni, Molecular Descriptors for Chemoinformatics, Wiley-VCH, 2009.
GLP compliance:
no
Remarks:
Qualitative prediction

Test material

Constituent 1
Chemical structure
Reference substance name:
Tetrakis(2-ethylhexyl) benzene-1,2,4,5-tetracarboxylate
EC Number:
221-508-0
EC Name:
Tetrakis(2-ethylhexyl) benzene-1,2,4,5-tetracarboxylate
Cas Number:
3126-80-5
Molecular formula:
C42H70O8
IUPAC Name:
1,2,4,5-tetrakis(2-ethylhexyl) benzene-1,2,4,5-tetracarboxylate
Test material form:
liquid: viscous
Specific details on test material used for the study:
CAS number 3126-80-5
EC number: 221-508-0

Results and discussion

Effect levels

Remarks on result:
other: QSAR prediction
Remarks:
Prediction is NON-carcinogenic using CAESAR model

Target system / organ toxicity

Critical effects observed:
not specified

Applicant's summary and conclusion

Conclusions:
Prediction is NON-Carcinogen, but the result may be not reliable.
A check of the information given in the following section should be done, paying particular attention to the following issues:
- only moderately similar compounds with known experimental value in the training set have been found
- similar molecules found in the training set have experimental values that disagree with the predicted value
Executive summary:

Prediction is NON-carcinogenic using CAESAR model