Needs and Future Perspectives of Modelling Skin Permeability and Metabolism

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1 Needs and Future Perspectives of Modelling Skin Permeability and Metabolism Mark Cronin School of Pharmacy and Chemistry Liverpool John Moores University England

2 Reasons for Studying Skin Penetration Topical delivery of drugs Risk assessment of chemicals Deliberate Occupational Accidental

3 Risk Assessment Risk is a function of hazard and exposure Identified from toxicity testing Rinse off, leave on, occupational etc

4 Identifying Hazard: Repeat Dose Toxicity Testing Aims to derive a concentration that causes no effect 100% Effect(s) 50% LOAEL NOEL NOEL = No Observed Effect Level 0% Dose

5 Other Dermal Risks following Exposure Skin sensitisation Skin irritation and corrosion Skin cancer Lethality

6 The Cosmetics Industry > 5 billion personal hygiene products sold per year in the EU Approx. 1.7 million people employed directly and indirectly in the EU cosmetic industry Skin care products have the biggest market share (27%) Europeans use 450 million personal hygiene products daily The average consumer spends the same amount of money on cosmetics as they do on bread EU Cosmetic Industry was Worth Approximately 70 Billion in 2011

7 Ensuring the Safety of Cosmetics and Global Regulation of Cosmetics Cosmetics are a vanity product. European Union Cosmetics Regulation No testing on products No further testing on ingredients US FDA colours and food substances How are we going to ensure safety of existing and new cosmetics ingredients?

8 The Project Integrated In Silico Models for the Prediction of Human Repeated Dose Toxicity of COSMetics to Optimise Safety Mio EUR 15 Partners EC FP7 Cosmetics Europe COSMOS is an EU project developing methods for determining the safety of cosmetic ingredients for humans, without the use of animals, using computational models.

9 Aims of COSMOS Collate, curate and quality control new sources of toxicological data Establish thresholds of toxicological concern Develop innovative strategies to use existing and novel in silico approaches to predict toxicity Establish kinetic and PBPK models for in vitro, in silico and other relevant data to predict target organ concentrations and long term toxicity to humans Integrate open source and open access modelling approaches into adaptable and flexible in silico workflows

10 Project Threshold of Toxicological Concern (TTC) New Toxicological Databases PBPK and In Vitro In Vivo Extrapolation In Silico Models

11 What's in A Name? that which we call a rose, by any other name would smell as sweet Aqua Paraffinum Liquidum Benzyl alcohol Methylchoroisothiazolinone CI 15510

12 COSMOS Inventory of Cosmetics Ingredients A reference list of chemicals or substances that may have been used in cosmetics formulations (or may now be banned) COSING 19,000+ INCI names 3,500+ INCI names PCPC INCI name: International Nomenclature for Cosmetics Ingredients Cosing database: Cosmetics ingredients database PCPC: Personal Care Products Council, US trade organization Thanks to

13 Over 4,400 Substances in the COSMOS Cosmetics Ingredients Inventory: Use Classes Thanks to

14 Cosmetics Ingredients: Types of Chemistry Thanks to

15 How to Assure Safety with no Data Risk is a function of hazard and exposure If you are not exposed at a high enough level to a hazard, there is minimal or no risk Can we define a generic threshold for chemicals below which we assume exposure has minimal risk Many caveats and exceptions to be noted

16 Define a Threshold With Minimal Risk No Effect Concentration Levels (NOELs) available for many compounds 5 th Percentile Munro IC et al (1996) Fd. Chem. Toxicol. 34: 829

17 the TTC approach, in general, [is] scientifically acceptable for human health risk assessment of systemic toxic effects caused by chemicals present at very low levels, as based on sound exposure information.

18 Are the Current TTC Values Acceptable for Cosmetics? There are enormous implications Safety of consumers Regulation and Industry NGOs Scientific credibility of this approach must be assured Moving on from the Cramer Classes Models are required to assess the dermal route of exposure

19 TTC is Derived from Oral NOEL Values: Is the Oral Route Protective of Dermal Exposure? Scenario 1 Oral absorption high Dermal absorption high Scenario 3 Oral absorption low Dermal absorption high Scenario 2 Oral absorption high Dermal absorption low Scenario 4 Oral absorption low Dermal absorption low absorption/permeability via dermal and oral routes metabolism differences between skin and liver

20 Predicting Dermal Absorption We have reasonably robust models Potts and Guy Bunge ten Berge Kasting Dancik Magnusson. and many others Are the models fit for purpose? The purpose being to identify compounds with significant dermal penetration

21 COSMOS Dermal Absorption Database Data for 380+ compounds in vitro studies (rat, mouse, pig, human) in vivo studies (rat, mouse, pig, human, monkey) Thanks to

22 Example of the 42 Entries for 2-Ethoxyethanol: Data for in Vitro Human (Flow-through) Membrane Area (cm2) Vehicle Exposure (Hour) % Absorbed Flux Dermatomed 0.64 Methanol Dermatomed 0.64 Neat Dermatomed 0.64 Water Dermatomed 0.64 Water Dermatomed 0.64 Water Dermatomed 0.64 Water Dermatomed 0.64 Water Dermatomed 0.64 Water Dermatomed 0.64 Water Dermatomed 0.64 Neat Dermatomed 0.64 Neat Full thickness 0.64 Water Full thickness 3.14 Neat Full thickness 3.14 Acetone Dermatomed 0.64 Neat Dermatomed 0.64 Water Dermatomed 0.64 Water kp

23 Molecular Size vs Hydrophobicity: Experimental Skin Permeability vs COSMOS Inventory MW log P

24 Very Initial Analysis of Potts and Guy (K p ) and Magnusson (J max ) Models Difficulty in identifying data for modelling or validation Depth of detail captured Intrinsic experimental variation Encouraging fit despite variability of data Few / no highly absorbed compounds are poorly predicted

25 Skin Metabolism In ADME, metabolism important factor for toxicokinetic bioavailability Sites of metabolism: Liver, GI tract, kidneys, lungs Cosmetic ingredients: Skin Reactive metabolites cause toxic effects

26 Skin Metabolism Difficulties in terminology Clearance amount systemically available Detoxifying or toxifying effect new compounds For the four box risk assessment approach we need to be able to predict Toxic metabolites from the skin that may not be produced by the liver Compounds rapidly cleared by the liver but not by the skin (although they will proceed from the skin to the liver in systemic circulation )

27 Predicting Metabolites in the Skin Prediction of potential metabolites is feasible Existing rule-based software can be used prediction-metabolismmetaprint2d

28 Metabolism Rules Being Developed Transparent set of metabolism rules Xenobiotic > Oxidoreductase > Carbonyl reductase CBR3 > Quinone Metabolism type (xenobiotic, lipid, protein,...) Classification (oxidation, hydrolysis,...) Enzyme activity type (skin: incl. enzyme isoform) Compound class Liver metabolism profiler Skin metabolism profiler Human Thanks to

29 Metabolism Rules - Details Metabolism type Classification (EC enzyme nomenclature) Enzyme (skin) Enzyme activity type (liver) Specification Xenobiotic Lipid (essential ingredient in cosmetics) Steroid Protein Carbohydrate Phase I Oxidoreductase Hydrolase Isomerase Ligase Lyase Phase II Transferase Enzyme activity type Alcohol dehydrogenase Aldo-keto reductase Monoamine oxidase Carboxylesterase... Enzyme + isoform Skin metabolism ADH1B = Short chain ADH5 = Long chain alcohols Compound class Primary amine Aliph. alcohol Ketone in ring... Thanks to

30 Metabolism Parameters Rule set enhanced by metabolism parameters Metabolism probability Kinetics (Michaelis-Menten constants for enzymatic reactions) Skin/liver ratio (low ratio low probability of transformation in skin) Detection rate of enzyme in skin (population variance) All parameters related to human metabolism / enzymes Direct integration into KNIME nodes Thanks to

31 More Future Needs Understanding formulations Vehicles Other effects of mixtures Predicting permeability of nanoparticles

32 A Vision for the Future Rapid risk assessment from chemical structure Decision tree related to TTC (Profs Guy and Williams and an ILSI Expert Group) Identification of high risk chemicals through prediction of High dermal absorption Relevant metabolites Clearance Clear appreciation of effects of formulation

33 Conclusions The Threshold of Toxicological Concern (TTC) provides a risk assessment approach Needs to be updated for dermal exposure Current predictive models for skin absorption are rough and ready Probably acceptable to identify highly absorbed compounds Predictive models for metabolism are being developed

34 Acknowledgements The European Community s Seventh Framework Program (FP7/ ) COSMOS Project under grant agreement n and Cosmetics Europe Co-workers in Liverpool, EU, USA