DetNet - AISE · - Building on CLP: hierarchy of data, bridging principles, expert judgement, classification network. - Use of in vitro methods to generate new skin and eye data

DetNet Detergent Industry Network for CLP Classification

(skin and eye effects)

An A.I.S.E. Initiative

A.I.S.E.’s project for CLP

implementation

Adequate safety assessment for skin and eye effects,

based on in vitro test data

2

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)

Stakeholder dialogue

Detergent Industry Network for CLP Classification

An A.I.S.E. initiative

Legal background

CLP Regulation, Annex I (paragraph 1.1.0.):

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

3 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



DetNet

Unique features

5

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: Organisational structure

6

DATABASE

- ca 200 formulations

- toxicity data:

historical in vivo

new in vitro Network Management

- Process

- Database

SCIENTIFIC ADVISORY

PANEL

“Guidance &

Quality Assurance”

- Medical/Toxicological

experts from e.g. Academia,

Poison Centers…

Secured Web / IT tool

EXPERT POOL

- Internal and External

experts

- Nominated/Trained

Evaluation/

Classification

COMPANY

placing product on

the market:

Responsibility for

final classification

AUTHORITIES Access info on

request



Experts

Options for company

7

COMPANY

Nominate classification expert

In-house Employee Company-retained

consultant

Contract external experts

Eligibility criteria + mandatory training

“Expert pool”



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.



A.I.S.E. Classification Guidance

for DetNet classification experts



1. Identification of available

information on the mixture

and ingredients

2. Check pH (extreme pH

or not)

3. Compare with previously tested

mixtures (hazardous): can

“permitted variations”

Bridging Principle (BP) be

applied?

4. Can “dilution” or

“batching” BP be applied?

5. Are there 2 TM of same

classification that could be

used for “Interpolation”

BP?

Check Tested Mixture in DetNet

database, select possible Tested

Mixtures (TM) and apply BP

6. Is there a TM of same

classification that could be

used for “Substantially

Similar Mixture” (SSM) BP?

7. Is/ are there TM(s) that can

be used for “Interpolation”

or “SSM” BP using expert

judgement?

8. Is/ are there TM(s) and/ or available

information allowing WoE

assessment using expert

judgement?

9. Generate new data (e.g. In vitro) or

apply Additivity Approach

Yes :

Classify

Yes :

Classify

Yes :

Classify

Yes :

Classify

Yes :

Classify

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.



Classification Record (p.1)

11

CLP Annex I

1,1,0: Suppliers

should document

fully the

classification

basis; data and

information to be

made available to

authorities on

request



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…)



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



Documents

DetNet - AISE · - Building on CLP: hierarchy of data, bridging principles, expert judgement, classification network. - Use of in vitro methods to generate new skin and eye data