1. The conversion of Saul to St Paul (Michelangelo, 1542) Marcel Leist Doerenkamp-Zbinden Chair For Alternative in vitro Methods, University Konstanz, Konstanz Germany EPAA Annual Conference 2007 Regulatory acceptance and implementation of 3Rs approaches Criteria and Drivers for Acceptance

2. Regulatory acceptance Academia Feedback processes? Developers 3R test pipeline

3. Major drivers for 3R 3R animals confidence Validation Experience Communication Optimised strategies (De)validation

4. Confidence as key factor for regulatory acceptance of alternatives Validation of old AND new methods Safety levels, robustness, assay characteristics,....

5. …also heterogeneity in the design of the available in vivo studies underlies much of the scatter, and this puts a limit on validating in vitro data as predictors of in vivo data. Further analysis of the in vitro-in vivo correlation would therefore require high quality in vivo data, ….. Quantitative extrapolation of in vitro whole embryo culture embryotoxicity data to developmental toxicity in vivo using the Benchmark Dose approach. A.H. Piersma et al, (2007) Toxicol. Sci. Problems with in vivo assays....:

6. …also heterogeneity in the design of the available in vivo studies underlies much of the scatter, and this puts a limit on validating in vitro data as predictors of in vivo data. Further analysis of the in vitro- in vivo correlation would therefore require high quality in vivo data, ….. Quantitative extrapolation of in vitro whole embryo culture embryotoxicity data to developmental toxicity in vivo using the Benchmark Dose approach. A.H. Piersma et al, (2007) Toxicol. Sci. Example:

7. Avoidance of prejudice:....in vitro systems do not predict systemic toxicity......, in vivo systems are better Example: TeGenero TGN1412 The Journal of Immunology (2007), 179, 3325

9. Prejudice: in vitro systems do not predict systemic toxicity

10. The 3R Reduce Replace Refine

11. Driver for regulatory acceptance of reduction Enough is enough - LD50 - Ecotoxicology test strategies - Two-generation studies

12. …study retrospectively evaluates 176 multi-generation studies to assess potential differences between the first and the second generation, both in terms of the types of effects observed and in terms of the effective doses. All substances classified as reproductive toxicants by the Directive 92/32/EEC or considered as toxic to fertility by the California EPA for which we found a multi-generation study were included ….. …The second generation ….. affected neither the overall NOAEL nor the critical effect. Therefore, it had no impact on the ensuing risk assessment, nor on classification and labeling. …. A retrospective analysis of the two-generation study: What is the added value of the second generation ? G. Janers et al, (2007) Reproductive Toxicol. 24, 97

13. …study retrospectively evaluates 176 multi-generation studies to assess potential differences between the first and the second generation, both in terms of the types of effects observed and in terms of the effective doses. All substances classified as reproductive toxicants by the Directive 92/32/EEC or considered as toxic to fertility by the California EPA for which we found a multi-generation study were included ….. …The second generation ….. affected neither the overall NOAEL nor the critical effect. Therefore, it had no impact on the ensuing risk assessment, nor on classification and labeling. …. A retrospective analysis of the two-generation study: What is the added value of the second generation ? G. Janers et al, (2007) Reproductive Toxicol. 24, 97

14. …study retrospectively evaluates 176 multi-generation studies to assess potential differences between the first and the second generation, both in terms of the types of effects observed and in terms of the effective doses. All substances classified as reproductive toxicants by the Directive 92/32/EEC or considered as toxic to fertility by the California EPA for which we found a multi-generation study were included ….. …The second generation ….. affected neither the overall NOAEL nor the critical effect. Therefore, it had no impact on the ensuing risk assessment, nor on classification and labeling. …. A retrospective analysis of the two-generation study: What is the added value of the second generation ? G. Janers et al, (2007) Reproductive Toxicol. 24, 97

15. Method developers Regulators

16. Method developers Regulators Catalyzers/ Facilitators

17. Method developers Regulators Catalyzers/ Facilitators (ECVAM)

18. The validation dilemma: Are we going to hit? Real human safety profile

19. The human safety profile Tuning a test Real human safety profile

20. Any model of human safety Real human safety profile Real world scenarios: - Inexact science - poor human data

21. Accuracy and errors Animal data Human data Real human safety profile Correlations?

22. Accuracy and errors Real human safety profile Correlations? False positive False negative Accurate

23. Animal models of human safety Animal data Real human safety profile

24. Real world scenarios! Correlation of models of human safety Animal data Real human safety profile Alternative data

25. Real world scenarios! Correlation of models of human safety Animal data Real human safety profile Alternative data

26. Comparison to in vitro data Model correlation Real human safety profile Examples from ECVAM/NICEATM study corr. = 0.53 correlation = 0.56 correlation = 0.62 Personal communication T. Hartung; n = 45

27. One step further.................. Coverage of complex toxicity by integrated test batteries (e.g developmental toxicity)

28. Integrated test batteries Real human safety profile Reproductive toxicity spermatogenesis 2-Generation study

29. Integrated test batteries Real human safety profile

30. Validation procedure and regulatory acceptance Early collaboration/contact of producer (test developer) and customer (regulator) Agreement on relevant reference points - Gold standard - Reference data base - Reference compound base - State of the art of method and competitors - Situation in other sectors and countries

31. - Buildup of experience how to interpret data; how to deal with data, historic feedback Biological system Exposure situation Model endpoint Prediction model Test Validated Test Applied Test Regulator input: tuning Regulator input: fine-tuning/post-validation - Continuous feedback in test pipeline Validation procedure and regulatory acceptance

32. University Konstanz Doerenkamp-Zbinden Foundation