PREDICTING PHARMACOKINETICS FOLLOWING TOPICAL APPLICATION USING NON-ANIMAL METHODS IAN SORRELL, MI-YOUNG LEE, RICHARD CUBBERLEY

PREDICTING PHARMACOKINETICS FOLLOWING TOPICAL APPLICATION USING NON-ANIMAL METHODS IAN SORRELL, MI-YOUNG LEE, RICHARD CUBBERLEY

UNILEVER APPLICATIONS KINETICS Need for estimates of local and systemic concentrations of chemical ingredients Efficacy Toxicology Use of kinetics in risk assessments without the use of animal models: Predict internal concentrations with quantified uncertainty IVIVE Support first in man Safety decision making

PREDICTING INTERNAL CONCENTRATIONS Systemic Exposure In Vitro Assays: Kinetic Solubility Thermodynamic Solubility Metabolic Stability -Human Hepatocytes -Human CYP450 Isoforms -Human Hepatic Microsomes Stability in Human Plasma Plasma Protein Binding Partitioning in Human Blood Gastroplus SimulationsPlus Predicting systemic exposure Enabling us to select and test relevant doses Increased role for clinical work to confirm systemic exposure levels PBK Modelling

EVALUATION OF PBK PREDICTIONS FOR TOPICAL APPLICATION ESTIMATING UNCERTAINTY IN PREDICTIONS OF SYSTEMIC CONCENTRATION

PREDICTION VS. OBSERVATION Comparing predicted Cmax with measured clinical data (plasma concentration time profile following topical application) Limited by number compounds Skin penetration in vitro Metabolism hepatocyte suspension Experimental measurements protein binding Gastroplus PBK model

Skin Bioavailabity DERMAL PENETRATION Dermal Kinetics ex vivo human skin Dealing with uncertainty: Bayesian inference Understanding the kinetics of an ingredient in the skin to allow risk assessments for local endpoints Understanding delivery to the systemic circulation following dermal application Davies et al (2011) Toxicol Sci 119, 308-18

EVALUATION IN VITRO HEPATIC METABOLISM ASSAYS METHODS FOR LOW CLEARANCE COMPOUNDS

HEPATIC CLEARANCE Current models for human metabolism Subcellular fraction Easy to use Express phase I/II enzyme Used for clearance, inhibition, covalent binding Pool of large number of donors Can be recovered from frozen tissues Cell line: Lower cost, renewable source Need to be evaluated for target application Cell culture / cell line Easy to use: amenable to high throughput platform Used for toxicity & DDI studies Co-culture with other cells Able to be cryopreserved Available for multiple species De-differentiate in culture Lack representation of intact liver structure Cell line: Lower cost, renewable source Need to be evaluated for target application 3D cell culture Allow better cell-cell & cell-matrix interactions Represent the in vivo-like conditions in terms of cell function, morphology, nutrition, oxygenation, configuration Enabling better prediction of drug toxicity Maintain long term culture; good for chronic drug treatment, slow clearance drug metabolism Low to medium throughput Some 3D formats difficult for imaging Liver cut slices In vivo architecture reserved In vivo-like expression of drug metabolizing enzymes, transporters, and functional bile canaliculi Zone specific metabolism in toxicity may be studied Hepatic function reserved for <24 hrs. Complicated to use Difficult to obtain human tissue Complexity, Ability to predict human metabolism, In Vivo systems resembling, Cost Easy of handling, Reproducibility In Vivo models Animal models not used by Unilever Have inter-species differences High cost Most suitable model to study different organinteraction In Vitro-In Vivo extrapolation Use of in vitro models to predict in vivo information

IN VITRO STUDY OF LOW CLEARANCE CHEMICALS IN VITRO SYSTEMS FOR METABOLISM STUDY Non-cell Cell, primary human hepatocytes preparation Human liver fraction Mono culture Co-culture Types S9 microsomes Suspended culture Plated culture Hanging-drop microtissue Micropatterned culture Incubation time (hr) 2 2 4 24 24-72 (168) 168 Increase incubation time Read-out Drug depletion rates Metabolite profile Cell viability In single concentration (1µM), In vitro clearance (to be extrapolated to in vivo CL) Metabolite formation and possible metabolic pathway (Quantitative and qualitative data) Cell viability spheroid assay during 7 days incubation

SPHEROID AND MICROPATTERNED HEPATOCYTES Spheroids from InSphero Co-culture: Pooled Primary Human Hepatocyte (PHHs) 10 mixed donors Kupffer cells -1 donor Cell number: total 1,000 cells per spheroid, 500 hepatocytes/ spheroid Microtissue size: 225.7 ± 11.1 µm Incubation vol.: 96 well (100 microliters / well) Function: Stable liver function until 4 weeks Solvo Biotechnology Ascendance: HepatoPac External work Co-culture: Primary Human Hepatocyte (PHHs) single donor 3121B 3T3 stromal cells mouse cell line Cell number: 3,200 cells (Hepatocytes), 15,000 cells (stromal) Incubation vol.: 96 well (67 microliters / well) Function: Stable liver function until 4 weeks

Test chemicals Drug Nicotine class B Known Metabolism Routes CYP2A6, 2B6, UGT, Aldehyde oxidase etc. Dextromethorphan B CYP2D6,3A4,1A2,2C19 Imipramine Diclofenac B A CYP2D6,1A2,2C19,3A4 ; UGT1A4 CYP2C9, 3A4, UGT2B7, CL Group ml/ min / kg High CL > 15 intermediate CL 5< CL <15 In Vivo Clearance ml/ min / kg Fu CL nonrenal Ref. Ref. 18 Obach 2008 0.95 8.6 Lin, 2015 8 Lin, 2015 7.6 Lin, 2015 Obach, 2008 0.45 Witherow et al, 1999 0.72 Lutz et al, 2011 0.075 Obach, 2008 0.14 0.005 0.05 https://link.s pringer.com /article/10.1 007/BF005 68901 Obach, 2008 Dancik 2012 Tolbutamide A CYP2C9, 2C19 0.38 Lin, 2015 0.05 Obach, 2008 Low CL Warfarin A CYP2C9, CYP3A4 <5 0.05 Lin, 2015 0.015 Salicylic acid A Glycine conjugation acyl-coa N- acyltransferase, 0.21 Schwarb, 1999 0.14 0.053 Obach, 2008 Dancik 2012 https://www. ncbi.nlm.nih.gov/pubme d/9112064

HepatoPac XB170047 TS1 Tolbutamide Ln % remaining Spheroid XB160099 TS11 Tolbutamide Ln % remaining Tolbutamide Ln % remaining Suspension XB170009 TS4 Tolbutamide Ln % remaining COMPARISON SUSPENSION VS SPHEROID VS HEPATOPAC 5.5 5.0 Tolbutaminde 4.5 4.0 0 1 2 3 4 Time (hour) 5.0 4.8 4.6 4.4 4.2 4.0 0 24 48 72 96 120 144 168 Time (hour) 5.0 4.5 Suspension vs Spheroid vs HepatoPac 5 4 3 2 1 0 0 24 48 72 96 120 144 168 Time (hour) Spheroid Suspension HepatoPac 4.0 3.5 3.0 0 24 48 72 96 120 144 168 Time (hour)

Warfarin Ln % remaining SUMMARY OF CLEARANCE RATES SPHEROID VS HEPATOPAC Spheroid Test article Mean Cl int (µl/min/10 6 cells) Goodness of fit dextromethorphan 1.3 0.02 diclofenac 21.2 0.98 imipramine 14.9 0.77 salicylic acid 0.8 0.01 S-nicotine 4.5 0.85 tolbutamide 3.3 0.40 warfarin 0.8 0.01 Diclofenac HepatoPac Test article Mean Cl int 4 (µl/min/10 6 cells) Spheroid Goodness of fit Dextromethorphan 15.72 3 0.93 5 Diclofenac 2 13.21 0.69 Imipramine 9.30 1 0.99 salicylic acid 2.56 0 0.97 S-nicotine 5.35 Time (hour) 0.99 tolbutamide 2.34 1/slope 43790.97 warfarin 1.19 R square 0.01444 0.99 0 24 48 72 96 120 144 168

METABOLITE IDENTIFICATION Salicylic acid metabolites [nmol] salicylic acid metabolites in media [nmol] salicylic acid metabolites in lysate [nmol] Salicylic acid metabolite formations HepatoPac cultures 0.008 Spheroid 0.025 HepatoPac [media] 0.0008 HepatoPac [lysate] 0.006 0.020 0.0006 0.004 0.002 0.015 0.010 0.005 0.0004 0.0002 0.000 0 24 48 72 96 120 144 168 Time (hour) Hydroxyhippuric Acid Salicylic Acid Acyl Glucuronid Salicylic Acid Phenyl Glucuron Dihydroxybenzoic Acid 0.000 0 24 48 72 96 120 144 168 Time (hour) O-Hydroxyhippuric acid Salicylic Acid Acyl Glucuronid Salicylic Acid Phenyl Glucuron SAAG-stromal** ** SAAG was detected in only media of Stromal cells * No detection of 2,5-dihydroxybenzoic acid 0.0000 0 24 48 72 96 120 144 168 Time (hour) O-Hydroxyhippuric acid Salicylic Acid Acyl Glucuronid Salicylic Acid Phenyl Glucuron SAAG-stromal** ** SAAG was detected in only media of Stromal cells * No detection of 2,5-dihydroxybenzoic acid

Salicylic acid metabolites [nmol] METABOLITE IDENTIFICATION Salicylic acid metabolite formation HepatoPac 0.030 0.025 0.020 0.015 0.010 0.005 0.000 0 24 48 72 144 168 Time (hour) SAAG SAPG O-Hydroxyhippuric acid SAAG SAPG O-Hydroxyhippuric acid, lysate SAAG, lysate SAPG, lysate * No detection of 2,5-dihydroxybenzoic acid

NEXT STEPS Evaluation of PBK models Increase numbers of chemicals in evaluation of systemic predictions using other dosing routes Determine uncertainty in skin penetration studies using alternative literature data Hepatic metabolism Donor cells used from HepatoPac compared with suspension Metabolite identification from HepatoPac More donors and chemicals in HepatoPac Additional low clearance compounds HepatoPac vs. suspension Measure transcriptional changes in HepatoPac assay

ACKNOWLEDGEMENTS Unilever Richard Cubberley Mi-Young Lee Hequn Li David Sheffield Beate Nicol Joe Reynolds Ruth Pendlington Juliette Pickles Solvo Biotechnology