ISRTP Workshop. Cumulative Risk for Endocrine Disrupters: The Case FOR a dose addition approach. Andreas Kortenkamp

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1 ISRTP Workshop Cumulative Risk for Endocrine Disrupters: The Case FOR a dose addition approach Andreas Kortenkamp The School of Pharmacy, University of London February 2008

2 Endocrine disruption: some issues Human disorders on the increase No single chemical linked to disorders Mixed exposures a reality Often massive differences between lab doses and real world exposures

3 Exposure scenario in humans Multiple chemicals in human tissues, all at low levels no concern, because levels are so low EDCs too weak to impact on potent endogenous hormones

4 EDC mixtures today EAT: additive combination effects Determinants of additivity understood Evidence missing: inhibitors of aromatase steroid-conjugating enzymes

5 Calculating additivity expectations Two conceptualisations of mixture effects Independent action (response addition) Concentration addition (dose addition)

6 Independent action Agents act independently of each other Presumed applicability: combinations of agents with diverse mechanisms Additivity expectation: effect multiplication

7 Concentration addition Dilution principle Presumed applicability: agents that interact with the same target ( similar mechanisms ) Additivity expectation: addition of equi-effective doses

8 Independent action

9 Independent action Assumptions on pebbles: One dose unit of pebbles breaks 90% of eggs One hit breaks one egg Start: 1000 eggs After 1 dose unit pebbles: 100 eggs (0.1 x 1000) After 2 dose units pebbles: 10 eggs (0.1 x 100) Effect multiplication: 0.1 x 0.1 = /1000 eggs

10 Independent action Assumptions on nails: One dose unit of nails breaks 50% of eggs One hit breaks one egg Combined effect of pebbles and nails? Start: 1000 eggs After 1 dose unit pebbles: 100 eggs After 1 dose unit nails: 50 eggs 0.1 x 0.5 = 0.05 = 50/1000 eggs

11 Concentration addition

12 Concentration addition Corrected absorbance (a.u.) Concentration (µm)

13 Three androgen receptor antagonists Hass et al EHP 115 Suppl 1, 122 Dose addition

14 Algal toxicity of 16 dissimilarly acting toxicants Faust et al. (2003) Aquat Toxicol 63, 43 Aclonifen 8-Azaguanine Azaserine CCCP Chloramphenicol DTMAC Fenfuram Kresoxim-methyl Metalaxyl Metazachlor Metsulfuron-methyl Nalidixic acid Norflurazon Paraquat Terbutylazim Triadimenol Conc addition Conc addition Independent action Independent action

15 Applicability of assessment concepts DA/CA only for components interacting specifically with the same receptor? IA for all others?

16 Seven anticancer drugs with diverse modes of action Fluorouracil 120 Methotrexate 100 IA Melphalan Doxorubicin Daunorubicin Vincristine Cis-platin corrected % cell killing CA 0 Phul et al. in prep e-6 1e-5 1e-4 1e-3 1e-2 1e-1 1e+0 1e+1 1e+2 1e+3 1e+4 1e+5 1e+6 Drug Concentration (µm)

17 Antiandrogens with diverse modes of action Vincolozolin Cholesterol HDL SR-B1 Prochloraz Finasteride DEHP StAR Cholesterol Cyp 11A Pregnenolone Testosterone 17β-HSD Androstenedione Cyp 17 17α progesterone Cyp 17 Progesterone 3β-HSD Pregnenolone

18 Assessment concepts Mathematical features, not toxicological properties, drive prediction differences

19 Mathematical features Assumption: 100 Two chemicals with identical dose-response curves 1: 1 mixture ratio corrected % cell killing Dose addition Independent action Independent action Dose addition 0 1e-5 1e-4 1e-3 1e-2 1e-1 1e+0 1e+1 1e+2 1e+3 1e+4 1e+5 1e+6 Drug Concentration (µm)

20 What is the correct assessment concept? Presumed modes of action do not provide reliable guidance Choice of concept by experimental validation? Similarity of effect, not similar MOA, should drive cumulative risk assessment

21 Experiences with mixtures Prediction differences between DA and IA not very large DA often yields more conservative predictions No documented case where IA is more conservative and correct

22 Low dose mixture effects Do chemicals work together when combined at low, ineffective doses? How many chemicals need to be combined to observe effects?

23 Hass et al. 2007, EHP 115 (Suppl 1), 122 Something from nothing

24 Something from nothing also observed with Estrogenic chemicals in the rat uterotrophic assay (Tinwell and Ashby 2004 EHP 112, 575) Estrogenic chemicals and vitellogenin induction in fish (Brian et al EHP 113, 721) Thyroid disrupting chemicals in the rat (Crofton et al EHP 113, 1549)

25 Determinants of cumulative effects Number of chemicals Potency Mixture ratio (prevalence) Total dose

26 Implications for regulation Dose (concentration) addition: a good first approximation of expected mixture effects

27 Mixtures risk assessment Mixture NOAEL Mixture NOAEL Human Animal Rel potency values

28 Issues with TEF To guestimate toxicity, not mixture effects TEFs are not endpoint-specific Comparatively little known about EDC relative potency values Requirement of parallel doseresponse curves

29 Ulla Hass and colleagues Some antiandrogens

30 Grouping criteria for cumulative risk assessment Stick with EAT Driver: similarity of effect (phenomenological approach) MOA important for interpretations, but should not be starting point for assessments

31 Acknowledgements Financial support from European Union: ACE project EDEN project

32 Thank you