Integration of non-testing tools: a weight of evidence approach. Dinant Kroese TNO Quality of Life Zeist, The Netherlands

Transcription

1 Integration of non-testing tools: a weight of evidence approach Dinant Kroese TNO Quality of Life Zeist, The Netherlands

2 Generation of information under REACH Gathering all existing data Data sharing Animal studies only as a last resort

3 Required Information under REACH Annexes VII - X Tonnage 1 10 tpa Annex VII tpa Annex VIII tpa Annex IX >1000 tpa Annex X Human Health In vitro skin and eye irritation Skin sensitization In vitro mutagenicity Acute toxicity (one route) In vivo skin and eye irritation Further in vitro mutagenicity Acute toxicity (2nd route) Sub acute toxicity (28d) Reproductive toxicity screen Further mutagenicity tests Sub-chronic toxicity (90d) Reproductive toxicity tests Further mutagenicity tests Further reproductive toxicity tests Carcinogenicity may Chronic toxicity may

4 REACH Estimated number of substances Annex VII 1 tpa Annex VIII 10 tpa Annex X 1000 tpa 2,600 substances Annex IX 100 tpa 2,900 substances 4,600 substances 20,000 substances

5 Animal use Scenario for animal use under REACH Registration Annex IX June 2013 Registration Annex VII & VIII June Pre-registration Dec 2008 Registration Annex X + CMR (cat 1+2) > 1 tonne/y + very toxic (R50/53) > 100 tonnes/y Dec 2010

6 Different types of information Human data Non-Testing information (Q)SAR In vitro Exposure Grouping & read across

7 Combine information in Integrated Testing Strategies (ITS) Existing testing information In vitro Human data Gathered information.. via ITS Grouping & read across (Q)SAR

8 Combine information in Integrated Testing Strategies (ITS) Existing testing information In vitro Human data cf Required information: Annexes VI-XI? using WoE Additional Testing Needed? Grouping & read across (Q)SAR Perform the test!

9 Combine information in Integrated Testing Strategies (ITS) Existing testing information In vitro Human data Waiving cf Annex XI: cf Required information: Annexes VI-XI? using WoE Additional Testing Needed? Grouping & read across (Q)SAR Technical or Exposure arguments? Perform the test!

10 Weight of Evidence Making decisions on information in ITS. taking into account: Quality descriptors Relevance of data Acceptability in the field Fit for purpose Cost effectiveness Pragmatism Deadlines

11 When is information sufficient? Available information + = REACH objectives C&L, RC OK??? Non-GLP / Non-OECD + +

12 Evaluating information a formal approach needed! that: allows for transparency and objectivity assesses value of individual test & non-test information combines values of test & non-test information, expert judgement, historical context reflects hierarchy of the testing strategy quantifies uncertainty resolves conflicting results.

13 Evaluating information a formal approach needed! that: allows for transparency and objectivity assesses value of individual test & non-test information combines values of test & non-test information, expert judgement, historical context reflects hierarchy of the testing strategy quantifies uncertainty resolves conflicting results.

14 Animal model Human exposure to substance A e.g. use of (Q)SARs Human health effect

15 Animal model e.g. use of (Q)SARs Mechanism A Mechanism B Mechanism C Same effect

16 e.g. use of (Q)SARs Animal model Statistical model (Q)SAR model, critical: Mechanism A 1. Understanding of toxicity mechanisms biological domain Mechanism B Mechanism C 2. Specifying of applicability domains chemical domain Same effect

17 e.g. use of (Q)SARs Animal model Statistical model Uncertainty is defined by variability sensitivity specificity

18 Evaluating information in ITS using Decision Analysis ITS can be modeled as Decision Networks through Influence Diagrams Influence Diagrams are graphical networks with 3 types of nodes, that model: 1. Chance events, e.g. probability of a chemical having a certain property 2. Decisions, such as exposure-based waiving, decisions to do more testing 3. Utilities: costs, animal use, value of information

19 Influence Diagram: Does a compound have a certain toxicity? Decide on running one or more non-testing models from toolbox Mechanisms, Domain, Specificity, Sensitivity Dependence Result Model A Decide on running one or more testing models from toolbox Result Model B Costs, value, animal use Result Model C Predictivity Sufficient certainty to make decision?? Result Model I Result Model II Result Model III

20 Is there a WoE approach? Not yet available.

21 interaction between: toxicologist, chemists, statisticians, hygienists, toolbuilders.. own language and concepts etc. Landscaping document: conclusions Webtool: position & functionalities Route to webtool: concept deliverable Takes time to achieve common understanding and agreement!

22 The OSIRIS webtool To help registrant/user to comply with REACH

23 OSIRIS webtool features Implements the ITS developed within RIP/OSIRIS Compatibility of data formats from external sources Is secure and keeps user privacy ITS processes are persistent ITS is easily changed Is easy to use SETAC EU Working - October Group 24, on 2008 QSARs - OSIRIS

24 Position of OSIRIS webtool

25 General concept of OSIRIS tool Input WP webtool 4.2 Tool sorts to type of info Predefined questionaire? adds weight to type of info or identifies datagap or asks expert input ITS library of options makes an assessment consults ITS and library of options compares with golden standard information, and concludes on: C & L RA concludes on additional information needed Output

26 General concept of OSIRIS tool Input Generate new test data WP webtool 4.2 Tool sorts to type of info Predefined questionaire? adds weight to type of info or identifies datagap or asks expert input ITS library of options makes an assessment consults ITS and library of options compares with golden standard information, and concludes on: C & L RA concludes on additional information needed

27 pilot webtool

28 Input OSIRIS webtool features input & output Only public databases are used Accepts testing data introduced by the end user Testing data introduced by a specific user are not used in the process of another user Allows to include expert judgment in selected phases Output A report describing the whole process It indicates what (testing) data is required to satisfy information requirements Can be tuned to minimize costs or animal use SETAC EU Working - October Group 24, on 2008 QSARs - OSIRIS

29 Concluding remarks WoE: yet no prototype.. Assesses and adding weight to information is being worked on Positioning webtool in very dynamic field needs attention Very first webtool pilot on mutagenicity; only testing sofar A long way to go there is an urgent need

30 Acknowledgements Istituto Di Ricerche Farmacologiche Mario Negri University of Rovira I Vergilli Procter & Gamble Fraunhofer Institut, University of Berlin, UFZ, DIALOGIK Joint Research Centre SIMPPLE NICBP RIVM, University of Wageningen, TNO