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EC number: 946-420-6 | CAS number: -
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
Partition coefficient
Administrative data
Link to relevant study record(s)
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- 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
- Justification for type of information:
- 1. SOFTWARE
ACD percepta software Release Release 2016, (Build 2911 July 2016)
2. MODEL (incl. version number)
log P Classic
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
example structures:
Diglycerol (PG2) OCC(O)COCC(O)CO
Triglycerol (PG3) OC(COCC(O)COCC(O)CO)CO
Nonaglycerol (PG9) OC(COCC(O)COCC(O)COCC(O)COCC(O)CO)COCC(O)COCC(O)COCC(O)COCC(O)CO
C10-PG2 mono OC(COCC(O)COC(=O)CCCCCCCCC)CO
C10-PG3-mono OC(COCC(O)COCC(O)CO)COC(=O)CCCCCCCCC
C12-PG2 mono OC(COCC(O)COC(=O)CCCCCCCCCCC)CO
C12-PG3-mono OC(COCC(O)COCC(O)CO)COC(=O)CCCCCCCCCCC
C10-C10-PG2 Diester OC(COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCC
C10-C10-PG3 Diester OC(COCC(O)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCC
C12-C10-PG2 Diester OC(COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCC
C12-C10-PG3 Diester OC(COCC(O)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC
C12-C12-PG2 Diester OC(COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCCCC
C12-C12-PG3 Diester OC(COCC(O)COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCCCC
C10-C10-C12 PG3 Triester OC(COCC(OC(=O)CCCCCCCCC)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC
C10-C10-C12 PG4 Triester OC(COCC(OC(=O)CCCCCCCCC)COCC(O)COC(=O)CCCCCCCCC)COCC(O)COC(=O)CCCCCCCCCCC
Explanation Algorithms for Log P:
The logP prediction module offers two different predictive algorithms within ACD/Percepta software—Classic and GALAS (Global, Adjusted Locally According to Similarity). A Consensus logP based on these two models is also available. Experts can investigate each model manually to decide which is more appropriate for particular chemical space, and provide colleagues with guidelines for use.
Classic
The primary algorithm calculates logP using the principle of isolating carbons. Well-characterized logP contributions have been compiled for atoms, structural fragments, and intramolecular interactions derived from >12,000 experimental logP values. A secondary algorithm is applied when unknown fragments are presented. A detailed description of the original algorithm may be found at "Petrauskas, A., Kolovanov, E., ACD/Log P Method Description. Persp. in Drug Design, 19:1–19,2000".
Source of experimental data—peer-reviewed scientific journals and the BioByte Star list.
Provides a detailed calculation protocol with references for known fragments, and indication of approximated contributions, with mapping onto the structure for easy interpretation. - Principles of method if other than guideline:
- Estimation via ACD percepta software Release Release 2016, (Build 2911 July 2016)
- GLP compliance:
- no
- Type of method:
- calculation method (fragments)
- Partition coefficient type:
- octanol-water
- Type:
- log Pow
- Partition coefficient:
- >= -4.84 - <= 12.77
- Temp.:
- 25 °C
- pH:
- >= 0 - <= 14
- Conclusions:
- Log P correlates with the degree of polymerisation of the polyglycerol backbone and grade of esterification.
With increasing of the degree of polymerisation of polyglycerol, the components are relatively more hydrophilic. With each added ester group, the lipophilic character increase. - Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- 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
- Justification for type of information:
- 1. SOFTWARE
EpiSuite V4.11
2. MODEL (incl. version number)
KOWWIN v1.68
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
Example structures
OC(COCC(O)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC
OC(COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCC
OC(COCC(O)COCC(O)CO)CO
OC(COCC(O)COCC(O)CO)COCC(O)CO
O=C(CCCCCCCCCCC)OCC(O)COC(=O)CCCCCCCCC
O=C(CCCCCCCCC)OC(COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC
OC(COCC(O)COC(=O)CCCCCCCCC)CO
OCC(O)CO
O=C(CCCCCCCCC)OCC(O)COC(=O)CCCCCCCCC
OCC(O)COCC(O)CO
O=C(CCCCCCCCCCC)OC(COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC
OC(COCC(O)COCC(O)COCC(O)CO)COCC(O)CO
OC(COCC(O)COCC(O)COCC(O)CO)COCC(O)COCC(O)CO
O=C(CCCCCCCCCCC)OC(COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCCCC
OC(COCC(O)COC(=O)CCCCCCCCCCC)CO
OC(COCC(OC(=O)CCCCCCCCC)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC
O=C(CCCCCCCCCCC)OCC(O)COC(=O)CCCCCCCCCCC
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
see attached justification
5. APPLICABILITY DOMAIN
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that log P estimates are less accurate for compounds outside the MW range of the training set compounds, and/or that have more instances of a given fragment than the maximum for all training set compounds. It is also possible that a compound may have a functional group(s) or other structural features not represented in the training set, and for which no fragment coefficient was developed.
6. ADEQUACY OF THE RESULT
Since the substance falls within the molecular weight range predictivity of the model used and there are no functional groups in the molecule that are not represented in the training set, the prediction is sufficient to provide reliable results for classification and labelling and risk assessment. - Principles of method if other than guideline:
- QSAR estimation using EPISUITE v4.11 software and the KOWWIN v1.68 model. Identifier used for input for the estimation are SMILES.
- GLP compliance:
- no
- Type of method:
- calculation method (fragments)
- Partition coefficient type:
- octanol-water
- Key result
- Type:
- log Pow
- Partition coefficient:
- 3.9
- Temp.:
- 25 °C
- pH:
- >= 0 - <= 14
- Remarks on result:
- other: weighted mean
- Type:
- log Pow
- Partition coefficient:
- >= -8.05 - <= 15.09
- Temp.:
- 25 °C
- pH:
- >= 0 - <= 14
- Conclusions:
- The weighted mean log Pow of polyglycerin caprylate/caprinate is estimated to be 3.9 using EPISUITE v4.11, KOWWIN v1.68.
- Endpoint:
- partition coefficient
- Type of information:
- experimental study
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- comparable to guideline study with acceptable restrictions
- Qualifier:
- equivalent or similar to guideline
- Guideline:
- OECD Guideline 117 (Partition Coefficient (n-octanol / water), HPLC Method)
- GLP compliance:
- no
- Type of method:
- HPLC method
- Partition coefficient type:
- octanol-water
- Analytical method:
- high-performance liquid chromatography
- Type:
- log Pow
- Partition coefficient:
- >= 0 - <= 3.6
- Temp.:
- 25 °C
- pH:
- >= 0 - <= 14
- Remarks on result:
- other: Additional compounds elute between 70 and 80 minutes in presence of 99% acetonitrile and 1% water as eluent. These compounds could not be eluted under the isocratic conditions applied in the test.
- Conclusions:
- The log Kow of polyglycerin caprylate/caprinate was determined usingn the HPLC method. The test item consists of multiple components covering a log P range from approximate 0 – 3.6. However, as is was not possible to find isocratic HPLC conditions for all constituents, the partition coefficients of characteristic single structures were estimated by QSAR.
Referenceopen allclose all
|
Smiles |
Log P |
Diglycerol (PG2) |
OCC(O)COCC(O)CO |
-2.61 ± 0.70 |
Triglycerol (PG3) |
OC(COCC(O)COCC(O)CO)CO |
-3.06 ± 0.72 |
Nonaglycerol (PG9) |
OC(COCC(O)COCC(O)COCC(O)COCC(O)CO)COCC(O)COCC(O)COCC(O)COCC(O)CO |
-4.84 ± 0.87 |
C10-PG2 mono |
OC(COCC(O)COC(=O)CCCCCCCCC)CO |
2.65 ± 0.67 |
C10-PG3-mono |
OC(COCC(O)COCC(O)CO)COC(=O)CCCCCCCCC |
2.21 ± 0.61 |
C12-PG2 mono |
OC(COCC(O)COC(=O)CCCCCCCCCCC)CO |
3.72 ± 0.67 |
C12-PG3-mono |
OC(COCC(O)COCC(O)CO)COC(=O)CCCCCCCCCCC |
3.27 ± 0.71 |
C10-C10-PG2 Diester |
OC(COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCC |
7.82 ± 0.63 |
C10-C10-PG3 Diester |
OC(COCC(O)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCC |
7.06 ± 0.79 |
C12-C10-PG2 Diester |
OC(COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCC |
8.88 ± 0.63 |
C12-C10-PG3 Diester |
OC(COCC(O)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC |
8.44 ± 0.69 |
C12-C12-PG2 Diester |
OC(COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCCCC |
9.94 ± 0.63 |
C12-C12-PG3 Diester |
OC(COCC(O)COCC(O)COC(=O)CCCCCCCCCCC)COC(=O)CCCCCCCCCCC |
9.19 ± 0.79 |
C10-C10-C12 PG3 Triester |
OC(COCC(OC(=O)CCCCCCCCC)COCC(O)COC(=O)CCCCCCCCC)COC(=O)CCCCCCCCCCC |
12.91 ± 0.88 |
C10-C10-C12 PG4 Triester |
OC(COCC(OC(=O)CCCCCCCCC)COCC(O)COC(=O)CCCCCCCCC)COCC(O)COC(=O)CCCCCCCCCCC |
12.77 ± 0.86 |
The technical sample polyglycerol-3 elutes within the dead time (t0) of both HPLC tests. The result of the isocratic HPLC analysis is, the test item constitutes of multiple components covering a log P range from approximate 0 – 3.6. These detected components could be polyglycerol monoesters, the experimental values correlate
with the estimated values.
The chromatogram shows, that additional compounds elute between 70 and 80 minutes in presence of 99% acetonitrile and 1% water as eluent. These compounds could not be eluted under the isocratic conditions described above.
It is not possible to find isocratic HPLC conditions for all constituents of the test item. Thus, the partition coefficient of characteristic single structures were estimated by QSAR.
Description of key information
The log Kow of polyglycerin caprylate/caprinate was determined usingn the HPLC method. The test item consists of multiple components covering a log P range from approximate 0 – 3.6. However, as is was not possible to find isocratic HPLC conditions for all constituents, the partition coefficients of characteristic single structures were estimated by QSAR.
The weighted mean log Pow of polyglycerin caprylate/caprinate is estimated to be 3.9 using EPISUITE v4.11, KOWWIN v1.68.
Key value for chemical safety assessment
- Log Kow (Log Pow):
- 3.9
- at the temperature of:
- 25 °C
Additional information
Information on Registered Substances comes from registration dossiers which have been assigned a registration number. The assignment of a registration number does however not guarantee that the information in the dossier is correct or that the dossier is compliant with Regulation (EC) No 1907/2006 (the REACH Regulation). This information has not been reviewed or verified by the Agency or any other authority. The content is subject to change without prior notice.
Reproduction or further distribution of this information may be subject to copyright protection. Use of the information without obtaining the permission from the owner(s) of the respective information might violate the rights of the owner.