1. Detergent Industry Network for CLP Classification
DetNet
Detergent Industry Network for CLP Classification
(skin and eye effects)
An A.I.S.E. Initiative
DetNet builds on the CLP provisions (Annex I, par ) allowing for data and expertise sharing among industry operators.
It is a database that includes currently around 200 reference formulations and covers 5 product categories (laundry powders, laundry liquids, hand dishwashing liquids and non-extreme pH all-purpose cleaners). These reference formulations have corresponding toxicological data, either skin human test data (HPT - Human Patch Test) and/or historic eye test data (LVET - Low Volume Eye Test) + in vitro data (EpiSkin OECD TG439 and ICE OECD histopathology) .
The aim is to contribute to establish the appropriate classification and consistent interpretation for expert judgement for skin/eye effects under CLP. For this, DetNet relies on the bridging principles.

2. A.I.S.E.’s project for CLP implementation
Adequate safety assessment for skin and eye effects, based on in vitro test data
Toxicological /classification and safety data
Share expertise to use and interpret data
New method and data generation
(in vitro)
Classification process
Industry network (WoE/ expert judgement)
A.I.S.E.’s objective => to collectively explore adequate options available under CLP to realistically classify detergent mixtures with the view to secure the safe use of consumers, namely:
assess the applicability of validated in vitro methods to generate test data on detergent mixtures in order to be able to use reliable test data for classification of mixtures, and
share data and expertise under the umbrella of an ‘Industry Classification Network’, and apply bridging principles and expert judgement, so that not every mixture needs to be individually tested.
Stakeholder dialogue
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

3. Detergent Industry Network for CLP Classification
Legal background
CLP Regulation, Annex I (paragraph ):
Suppliers may cooperate through formation of a network to share data and expertise
Suppliers should document fully the basis on which classification decisions are made
Suppliers should make data and information on which classifications are based available to authorities on request
Each supplier remains fully responsible for the classification, labelling and packaging of products placed on the market
The above text are excerpts from the CLP legal text.
All these requirements have been addressed in the DetNet approach.
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

4. Detergent Industry Network for CLP Classification
DetNet Scope
Products:
Laundry detergents (liquids & powders)
Hand dish wash detergents
All-purpose cleaners (non-extreme pH products)
Alkaline bleaches
Other cleaning and maintenance product types with similar chemistry (e.g. car wash products)
Consumer and professional products
Note: other products may be added in the future (e.g. concentrated liquid laundry detergents, extreme-pH products)
Endpoints: skin and eye irritation/ corrosion
Limitations: other endpoints than skin and eye effects, and other “chemistries” must be assessed separately
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

5. DetNet Unique features
Web-based IT system
IT-system searches the database of Reference Tested Mixtures
Security (individual access code), confidentiality protected
Standardised process and records
Classification Record using a standard format
Classification logging number as proof
Classification explanatory notes
Data sharing for all users, expertise
More than 200 mixtures, including recent market representative products
Enhanced composition details on Reference Tested Mixtures
Recent in vitro data using enhanced test method for eye effects
Data quality and robustness assessed (Klimisch scoring)
Study Summaries available
Scientific Advisory Panel comprising experts from academia
Training and support
Training of classification experts
Help Desk support
FAQ
DetNet is a secured web-based IT-system, with a number of built-in functionalities (e.g. search and compare formulation compositions), standard procedures, standard forms and a User Manual.
In practice, when an expert enters the composition of an untested mixture to classify, the IT-tool will search the database and present a number of possible matching formulations (with no ranking of ‘closeness’) which the expert then evaluates manually to see whether any of the CLP bridging principles can be applied.
The IT- functionality is called ‘Tested Mixtures Search Tool’. It is not intended to propose a classification, only to present potentially relevant information in a computerised manner to experts.
DetNet is not intended to propose a classification, it is only intended to support classification with a compilation of test data: the expert has to derive the classification manually, by comparing the formulation to be classified with the reference formulations identified by DetNet and decide whether (and how) the bridging principles can be applied. The actual classification is therefore derived from the expert’s own judgment.
Recent in vitro data included in the database were generated using EpiSkin (skin effects) and ICE (Isolated Chicken Eye Test) complemented with histopathology for eye effects.
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

6. DetNet: Organisational structure
DATABASE
- ca 200 formulations
- toxicity data:
 historical in vivo
 new in vitro
Network Management
- Process
- Database
AUTHORITIES
Access info on request
Secured Web / IT tool
SCIENTIFIC ADVISORY PANEL
“Guidance &
Quality Assurance”
- Medical/Toxicological experts from e.g. Academia, Poison Centers…
EXPERT POOL
- Internal and External experts
- Nominated/Trained
Key elements in DetNet
The cornerstone of DetNet is a database consisting of ca. 200 Tested Mixtures
Expert pool
This is the group of ‘classification experts’ (those that have been nominated by member companies, that meet the eligibility criteria and have followed the online training), i.e. individuals that will have access to the DetNet database and derive classification on that basis. – ‘Classification Experts’.
Two ‘External Experts’ (appointed by A.I.S.E.) also available for companies to use e.g. if don’t have classification expertise in-house or company expert needs 2nd opinion on a classification.
Scientific Advisory Panel (SAP):
An external Scientific Advisory Panel comprised of recognised independent experts (from Academia, Poison Centres) with in-depth knowledge in the fields of toxicology, dermatology or ophthalmology has been created.
This Panel provides independent advice to A.I.S.E. on the scientific approach, toxicological assessment, effect mechanisms, clinical experience and generation of reliable data (for classification purposes).
Access to authorities
In line with the CLP provisions, upon request, A.I.S.E. will make available detailed mixture information to inspectors namely, the full composition of the TM used to derive classification and/or the full test reports.
COMPANY
placing product on the market:
Responsibility for final classification
Evaluation/ Classification
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

7. Experts Options for company
Nominate classification expert
Contract external experts
In-house Employee
Company-retained consultant
Eligibility criteria + mandatory training
“Expert pool”
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

8. Classification experts: Eligibility criteria
Classification experts should fulfill at least one of the following criteria:
Bachelor degree (in chemistry or biology) and at least 5 years industry/regulatory safety/toxicology experience;
Relevant Master’s degree and at least 3 years of experience;
Relevant PhD and at least 2 years of experience; 
Candidates holding a further relevant professional qualification (e.g. European Registered Toxicologist (ERT), Diplomate of the American Board of Toxicology (DABT)) or being members of internationally recognised groups of experts may not have to meet the above criteria;
Other candidates with qualifications not listed above will be considered by the SAP on a case by case basis.
All nominations are reviewed and assessed individually.
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

9. A.I.S.E. Classification Guidance for DetNet classification experts
Identification of available information on the mixture and ingredients
Compare with previously tested
mixtures (hazardous): can
“permitted variations”
Bridging Principle (BP) be
applied?
Check Tested Mixture in DetNet database, select possible Tested Mixtures (TM) and apply BP
2. Check pH (extreme pH
or not)
4. Can “dilution” or
“batching” BP be applied?
Are there 2 TM of same
classification that could be
used for “Interpolation”
BP?
Yes : Classify
Yes : Classify
8. Is/ are there TM(s) and/ or available
information allowing WoE
assessment using expert
judgement?
7. Is/ are there TM(s) that can
be used for “Interpolation”
or “SSM” BP using expert
judgement?
6. Is there a TM of same
classification that could be
used for “Substantially
Similar Mixture” (SSM) BP?
Builds on and complements ECHA Guidance on CL
Yes : Classify
Generate new data (e.g. In vitro) or apply Additivity Approach
Yes : Classify
Yes : Classify
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

10. Options in case no suitable Tested Mixture is found
A member company that has not found a suitable Tested Mixture in the DetNet database has the following options:
Conduct an in vitro test at company level (check suitable methods)- could be shared with A.I.S.E. for inclusion into DetNet datase;
Derive the classification using the calculation method.
If a company does not find a closely matching formulation in the DetNet database, it can decide to conduct an in vitro test, according to suitable methods. A company can always decide to derive classification by calculation.
DetNet could also be used by companies in complement to other information (eg. Company data…) for classification:
1. There is a Tested Mixture in DetNet which is suitable, but cannot be used as stand alone. The company may decide to generate new additional in vitro data to derive a classification.
2.      The company owns historical in vivo data and existing in vitro data, DetNet data are used in addition to company data in order to accomplish a WoE assessment.
3. There is data in DetNet for one endpoint (relevant ofr classification) and no data (not tested, not relevant) for the other endpoint,
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

11. Classification Record (p.1)
CLP Annex I 1,1,0: Suppliers should document fully the classification basis; data and information to be made available to authorities on request
Any decision made by the expert to derive the classification is recorded in the Classification Record delivered at the end of the process by DetNet, following a standard format.
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

12. Detergent Industry Network for CLP Classification
Access by authorities
DetNet users can share with local enforcement authorities the DetNet Classification Record and the study summaries if needed;
After reviewing this available information, authorities may contact the A.I.S.E. DetNet manager to request detailed information on the Tested Mixtures used (i.e. full compositional details, full study reports…)
CR contains compositional details of Reference Tested Mixtures + reference to BP used + scientific/ regulatory rationale for the application of these BP and for the final classification
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative

13. Detergent Industry Network for CLP Classification
CONCLUSIONS
More than 200 experts from 150 companies have been trained to correctly access and use DetNet
More than 1,000 detergent mixtures classified using data from DetNet early 2016
DetNet is the first Industry Classification Network for mixtures
Building on CLP: hierarchy of data, bridging principles, expert judgement, classification network.
Use of in vitro methods to generate new skin and eye data.
Data-sharing at A.I.S.E. level for a sector-consistent approach.
Transparency and documentation.
A.I.S.E. has more work ahead: more data into the database, more dialogue with authorities, work on science…
We welcome your feedback
Detergent Industry Network for CLP Classification
An A.I.S.E. initiative