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. 1.1.0) 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 438 + 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.

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

Detergent Industry Network for CLP Classification 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 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

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

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

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

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

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

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

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

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

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

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