Registration Dossier

Ecotoxicological information

Toxicity to aquatic algae and cyanobacteria

Administrative data

Endpoint:
toxicity to aquatic algae and cyanobacteria
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
2014
Reliability:
2 (reliable with restrictions)
Justification for type of information:
QSAR prediction: migrated from IUCLID 5.6

Data source

Referenceopen allclose all

Reference Type:
publication
Title:
The ECOSAR (ECOlogical Structure Activity Relationships) class program for microsoft windows v1.11; within Estimation Programs Interface for Microsoft Windows, EPI Suite version 4.11
Author:
ECOSAR v1.11
Year:
2014
Bibliographic source:
Software package: ECOSAR v1.11, U.S. Environmental Protection Agency, Office of Chemical Safety and Pollution Prevention, 1200 Pennsylvania Ave., N.W. Washington, DC 20460-0001, USA.
Report Date:
2014
Reference Type:
other:
Title:
Guidance on information requirements and chemical safety assessment - Chapter R.7b: Endpoint specific guidance (version 2)
Author:
ECHA
Year:
2012
Bibliographic source:
European Chemicals Agency (ECHA)

Materials and methods

Test guidelineopen allclose all
Guideline:
other: REACH Guidance on QSARs R.6, May/July 2008
Guideline:
EPA OPPTS 850.5400 (Algal Toxicity, Tiers I and II)
Version / remarks:
This guideline is preferred for the training set but not obligatory
Principles of method if other than guideline:
ECOSAR v1.11 - Green Algae 96h EC50 ; Esters Class, Neutral Organics Class (baseline toxicity)

Test material

Reference
Name:
Unnamed
Type:
Constituent
Type:
Constituent
Type:
Constituent

Results and discussion

Effect concentrations
Duration:
96 h
Dose descriptor:
EC50
Effect conc.:
4.573 mg/L
Nominal / measured:
meas. (not specified)
Conc. based on:
test mat.
Basis for effect:
growth rate

Any other information on results incl. tables

1. Defined Endpoint:

QMRF 3. Ecotoxic effects

QMRF 3. 2. Short-term toxicity to algae (inhibition of the exponential growth rate)

 

Reference to type of model used and description of results:

ECOSAR v1.11 – Green Algae 96h EC50 ; Esters Class, Neutral Organics Class (baseline toxicity), 19 June 2012

2. Description of results and assessment of reliability of the prediction:

Ecosar Class:

Esters: Green Algae 96-hr EC50: 4.573 mg/l

Neutral Organic SAR (baseline toxicity): Green Algae 96-hr EC50: 13.609 mg/l

Assessment of the substance within the applicability domain as documented within the corresponding QMRF named ‘QMRF Title: ECOSAR v1.11 Green Algae 96h EC50’ version 1.0; 13 August 2014 – section 5; indicates the substance:

(i) Falls within the Log Kow domain of < 5 (general domain for the model; and Esters class specific cut off); (ii) Molecular weight is < 1000 g/mol and; (iii) Effect levels are predicted below the water solubility.

The substance does not possess functional groups outside those included within the esters, neutral organics or mono-epoxides classes and training sets. The assigned chemical class (Esters) is appropriate to the substance. The ECOSAR QSAR model as detailed is not known to function by specific modes of action associated with the chemical class(es) assigned. Full references to training set data are presented within ECOSAR v1.1 Help System; if not proprietary (in such cases the chemical identification is listed as CBI, but the relevant descriptor data are provided). A summary of this information is presented by the applicant.

The substances in the training set are considered analogues to the target substance since they possess an ester group and log Kow < 5 and MW < 1000 g/mol. The substance and the structural analogues share a common functional group and physic-chemical domains versus a neutral organics class (baseline toxicity). The ECOSAR class is based on similar relationships between toxicity and the various types of pharmacologic properties.

 

3. Uncertainty of the prediction and mechanistic domain:

The coefficients of determination for each chemical class training set is published as presented below:

Neutral Organics: Coefficient of determination (r2) = 0.6782

Esters: Coefficient of determination (r2) = 0.8581

Data for the Esters Class training set are available via external validation (see attached QMRF prepared by the applicant for full citations of the relevant validations).

Consistency of ECOSAR data compared to measured toxicity showed 60-64 % of green algae predictions (all chemical classes assessed) within a tolerance factor of 10, which is comparable to that seen in Hulzebos & Posthumus (2003).

Uncertainty in the prediction relates to the limited external validation on the Esters class. Model predictivity could be improved by the assignment of additional chemical categories and expansion of sub-structure rules, in addition further substances addition to the training set and rules for stereochemical effects within the model would improve predictivity.

 

The ECOSAR QSAR model as detailed is not known to function by specific modes of action associated with the chemical class(es) assigned. ECOSAR classes are grouped based on similar relationships between toxicity and the various types of pharmacologic properties. The model does not apply a mechanistic approach to assessment of toxicity other than assignment of chemical classes (to identify potential toxicity in excess of baseline narcosis) using an expert decision tree. The selected classes appear appropriate to the substance based on expert assessment.

Applicant's summary and conclusion

Conclusions:
The results are adequate for the regulatory purpose.
Executive summary:

ECOSAR v1.11 – Green Algae 96h EC50 ; Esters Class, Neutral Organics Class (baseline toxicity), 19 June 2012

Ecosar Class:

Esters: Green Algae 96-hr EC50: 4.573 mg/l

Neutral Organic SAR (baseline toxicity): Green Algae 96-hr EC50: 13.609 mg/l

 

The prediction is adequate for the Classification and Labelling or risk assessment of the substance as indicated in REACH Regulation (EC) 1907/2006: Annex XI Section 1.3. The predictions do not indicate extreme or acute toxicities relevant for classification and labelling. The assessment indicates that the prediction is suitable for the regulatory conclusion in accordance with the tonnage driven information requirements.