Novel in vitro and in silico models for the prediction of chemical toxicity Dominic Williams The University of Liverpool [email protected] Adverse Drug Reactions patient morbidity & mortality 4th – 6th leading cause of death in USA1 precludes otherwise effective drug therapy drug withdrawal (4%, (4% 1974 - 1994)2 €2B/p.a. in vivo toxicity testing 3 Drug attrition Liver, skin, blood, cardiovascular 1Lazarou et al., 1998 et al., 1994 3Andersen et al., 2009 2Jefferys Lessons for the future Inform on mechanism and pathogenesis Inform Medicinal Chemists Inform Clinicians Inform Regulators I f Inform th the Public P bli – what h t iis ffeasible ibl Develop better biomarkers Improve in vitro models Classification of Adverse Drug Reactions ON TARGET ADRs • Predictable from the known primary or secondary pharmacology of the drug • Exaggeration gg of the p pharmacological g effect of the drugg • Clear dose-dependent relationship OFF TARGET ADRs • Not predictable from a knowledge of the basic pharmacology of the drug • Exhibit marked inter inter-individual individual susceptibility (idiosyncratic) • Complex dose dependence ADR = f1 Chemistry of drug + f2 Biology of individual Drug-Induced Liver Injury Leading cause of acute liver failure1 Drugs cause 58% of all ALF High g morbidityy & mortalityy2 20% survival without transplant Main reason for late stage termination or withdrawal2 76 drugs found to be significant cause of hepatotoxicity across 3 DILI Registries (US, Sweden, Spain)3 Cause off liliver iinjury ≥ 5 cases/registry C j / i 1 Lee AASLD, 2009; 2 Verma & Kaplowitz 2009; 3 Suzuki et al., 2010 Drugs withdrawn from major markets due to hepatotoxicity 2 H N O O H H O H N Drug: - Alpidem* Aspirin (children) - Bendazac* Benoxaprofen - Bromfenac* Chlormezanone** - Dilavelol* Ebrotidine* - Fipexide Fipexide* Nefazodone* - Nimesulide Nomifensine - Oxyphenisatin h i i Pemoline* - Perhexilene Temafloxacin* Temafloxacin - Tolcapone* Tolrestat* - Troglitazone* T Trovafloxacin* fl i * Ximelagatran- Zimeldine Therapeutic area: Anxiolytic NSAID NSAID NSAID NSAID Anxiolytic Anti-hypertensive H2 receptor antagonist Stimulant Anti-depressant NSAID Anti-depressant Laxative i ADHD Anti-anginal Anti-infective Anti infective Anti-parkinson’s Anti-diabetic Anti-diabetic A ibi i Antibiotic Anti-coagulant Anti-depressant * Need et al., Nat Genetics 2005 Drug Metabolism: Pharmacology Cellular accumulation accu ua o DRUG RESPONSE Concentration Concentration in in Plasma ORGANS – CELLS - ORGANELLES Phase I/II Drug Stable metabolites Disposition Metabolism Absorption Excretion Excretion i Drug&plasma level Drug Metabolites Pharmacological Pharmacological g & exposure Toxicological exposure Pathogenic Mechanisms of DILI DRUG & METABOLITES Acute fatty liver with lactic acidosis Acute hepatic p necrosis Acute liver failure Acute viral hepatitis-like liver injury Autoimmune-like hepatitis Bland cholestasis Cholestatic hepatitis Cirrhosis Immuno-allergic hepatitis Nodular regeneration Non-alcoholic fatty liver Sinusoidal obstruction syndrome Vanishing bile duct syndrome DILI can present with multiple: varying phenotypes clinical & histopathological features A single i l ‘h ‘hepatotoxicity i i signature’ i ’ is i unlikely lik l Well characterised patients provide mechanistic clues Tujios & Fontana, Nat Rev Gastroenterol Hepatol; 2011 Pathogenic Mechanisms of DILI SM EC CLEARANCE DRUG METABOLITE REACTIVE METABOLITE mitochondria lysosome bioaccumulation organelle impairment inhibition of biliary efflux CLEARANCE Intrahepatic cholestasis hypersensitivity i immunoallergic ll i toxicity t i it Organelle impairment phospholipidosis microvesicular steatosis hepatocyte apoptosis hepatocyte necrosis Drug Metabolism: Toxicology Cellular accumulation DRUG Phase I/II/III Stable metabolites Lysosome Mitochondria BSEP bioactivation Chemically reactive metabolites bioinactivation Excretion • • • • Inhibition of protein function • apoptosis/necrosis • Recognition by immune system • covalent/non-covalent l t/ l t Drug Metabolism: Toxicology Cellular accumulation DRUG Phase I/II/III Inhibition Of P450s Lysosome Mitochondria BSEP bioactivation Chemically reactive metabolites bioinactivation Excretion • • • • Heme complex formation • Protein alkylation Ideal working relationship between chemistryy & drugg metabolism detoxication bi bioactivation ti ti cell defence apoptosis necrosis innate immunity adaptive immunity Park et al., Nat. Rev. Drug Disc. 2011 Improve translation = Improved Drug Safety Improved Translation Chemistry of the drug g Biology of the system In vitro mechanistic evaluation of hazard/risk f1 IImproving i drug safety science Variabilityy of the patient + f3 + f2 Improved Translation Chemistry of drug Biology of model system Biology of individual Requirement for novel, translational, in vitro models for hepatotoxicity Hepatic drug toxicity is a big problem for pharmaceutical industry: the physiological gap between incubations and liver the lack of physiological integration for amplification/adaptation inability to assess how minor chemical stress leads to major toxicity in some people lack of consideration of systemic effects However, systemic disposition and toxicity is an issue across the whole chemical industry Biocides, pesticides, food additives, cosmetic ingredients, consumer products etc. US National Research Council: ‘Toxicity testing in the 21st Century: A vision & a strategy’ Use human cells to predict human toxicity Reduce animal use Require novel in vitro models, based on human cells, to quantitatively assess chemical hazard Improved in vitro to in vivo extrapolation in chemical safety risk assessment for systemic toxicity Interdisciplinary collaboration between: Mathematical modellers Chemical/tissue engineers Toxicologists SimCyp Develop a zonated hepatic hollow fibre bioreactor for chemical safety assessment Engineer Bioanalysis Mathematically Model Safe human in vivo dose Replicating liver physiology for toxicology N Paracetamol (mouse) BSEP SER Bile canaliculus M Central vein 4 Hepatic sinusoids Perivenous / Centrilobular ↓ Oxygen ↓ Hormones Glycolysis Chemical detoxification Lipogenesis Hepatocytes Kupffer cell 1 2 Periportal ↑ Oxygen ↑ Hormones Gluconeogenesis Ureagenesis 3 Hepatic arteriole Portal vein Bile duct CL PP PP CL Methapyrilene(rat) Design an in vitro hepatic sinusoid A hollow fibre bioreactor Plasma-like compartment Liver Sinusoid Centrilobular -like region Periportallike region Cell number Viability Morphology Bile-like Bile like compartment Oxygen level Pressures Flow rates Glucose Albumin Urea Glycogen Design an in vitro hepatic sinusoid End view off ffibres extra-capillary t ill space hepatocytes media hollow fibre membrane A single fibre: Defining Operating Characteristics Engineers / Mathematicians: Scaffold design & production tertiary system spinning conditions dope additives post-spinning treatment Choice of & scaffold characterisation asymmetric / symmetric wall pore size fibre dimensions porosity Fluid transport / lumen pressures Albumin permeation & fouling Nutrient & oxygen transport Cell seeding / confluence Mass transfer limitations of traditional scaffolds Mathematicians / Modellers: Scalable in silico PBPK model In silico sinusoid composed of: HepG2 freshly isolated rat hepatocytes freshly isolated human hepatocytes Toxicologists / Modellers: 2D baseline characteristics of cell type Quantitatively assess how 3D environment maintains or improves functional drug metabolism & toxicity f3 Biology of model system Quantitative Bioanalytical Endpoints Paracetamol provides functional enzymatic coverage: CYP’s 2E1, 1A2, 2A6, 3A4, 2D6 Glucuronidation & sulphation MRP2,, 3,, 4 & BCRP Incorporation of bioactivation & covalent binding Demonstrates zone specific toxicity Toxicity induces inflammatory cytokine and toxicity biomarker release Weighting of results to in vivo (rat, chronic infusion) or fresh human hepatocyte data Considerable literature data well characterised compound Allows evaluation of biology / pharmacology within the model system e.g. bioreactor Paracetamol (APAP; acetaminophen) • • • Recommended dose - 4g. Toxic dose >4g • • • Centrilobular damage Most common form DILI in US & UK 400-500 deaths/yr, 70-100,000 hospital visits/yr Pharmacophore = Toxicophore Excellent translational ‘tool’ • Evaluation of novel models Lee W.B. AASLD 2009 Paracetamol (APAP; acetaminophen) • • • Recommended dose - 4g. Toxic dose >4g • • • Centrilobular damage Detoxication Most common form DILI in US & UK 400-500 deaths/yr, 70-100,000 hospital visits/yr Pharmacophore = Toxicophore Excellent translational ‘tool’ • Evaluation of novel models Bioactivation Overdose GSH COVALENT BINDING TOXICITY GLUCURONIDE SULPHATE Baseline 2D Operating Characteristics Freshly isolated rat hepatocytes (12x106 cells) Cultured rat hepatocytes Freshly isolated human hepatocyte (resection) Hep G2 cellll liline Toxicity Metabolism 79% 16% 2% I II III IV V VI VII 3% Parent compound (500M) disappearance Paracetamol-glucuronide Paracetamol glucuronide Cysteinyl-paracetamol Paracetamol Paracetamol-sulphate Paracetamol-glutathione 3-methoxy-paracetamol h l NAC-paracetamol Values are the mean ± SEM, n=4 Baseline 2D Operating Characteristics Toxicity Freshly isolated rat hepatocytes Cultured rat hepatocytes (2x106 cells; monolayer & sandwich culture) Freshly isolated human hepatocyte (resection) Hep G2 cellll liline UV Absorb bance at 254 4nm (mAU) Metabolism (72h) Monolayer 12% I III 9% II 0.5% IV 0.5mM Paracetamol Increased metabolism in sandwich culture hepatocytes III 87% Sandwich d h 10% I 2% II Time (min) I II III IV 78% Parent compound disappearance Paracetamol glucuronide Paracetamol Paracetamol sulphate Paracetamol glutathione 0.5% IV Wistar Rat Cl in vivo 6.6 ml/min Values are the mean ± SEM, n=4 *Raftogianis et al., 1995; Aanderud & Bakke, 1983 Rat Cells IVIVE clearance (ml/min) Hepatocyte suspensions 2 96 2.96 Sandwich culture 1.37 Monolayer culture 0.85 APAP Glutatthione Conjuggate (M) Baseline 2D Operating Characteristics Paracetamol Glutathione Conjugate formation 12 10 8 Rat Hepatocyte Suspensions (APAP 500µM): 6 plateau’ss after 3h Formation of APAP-GSH APAP GSH plateau 4 2 0 0 1 2 3 4 5 6 APAP Glutath hione Conjugaate (M) Time (h) 9 8 7 6 5 4 3 2 1 0 Monolayer Sandwich Hepatocytes in Culture (APAP 500µM): Increased bioactivation in hepatocytes cultured with matrigel overlay 0 20 40 Time (h) 60 Baseline 2D Operating Characteristics %P Paracetamol Remaining Cultured rat hepatocytes on different polymers Parent compound disappearance 120 100 Collagen 80 PS PLGA Metabolism (24h) I II III IV Paracetamol glucuronide Paracetamol Paracetamol sulphate Paracetamol glutathione 60 61% 40 20 26% 12% 0 0 20 40 0 2% 0.2% 60 Time (h) 69% Bi Biomaterial t i l IVIVE clearance l (ml/min) Collagen 0.73 PS coated t d 0 85 0.85 PLGA 22% 0.5% 9% 49% 0.66 37% 14% 0 5% 0.5% Baseline 2D Operating Characteristics Metabolism in fresh human hepatocyte suspensions (6h) 1,400 APAP 79% 1,000 APAP-glucuronide 16% 500 APAP-sulphate 4% APAP-GSH 1% 0 -200 200 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.0 Toxicity in suspension (6h) Viaability (% ccontrol) U UV Absorbance e at 254nm (m mAU) Freshly isolated rat hepatocytes Cultured rat hepatocytes Freshlyy isolated human hepatocyte p y ((resection)) Hep G2 cell line Trypan blue ATP Paracetamol ((mM)) Time (min) Metabolite : Parent Compound Ratio 0.5mM APAP-G APAP-S APAP-GSH 0.653 (±0.420) 0.139 (±0.053) 0.025 (±0.015) Values are the mean ± SEM, n=4 Interindividual variabilityy Inter-isolation variability Quality of resection hepatocytes Baseline 2D Operating Characteristics Metabolism Freshly isolated rat hepatocytes Cultured rat hepatocytes Freshly isolated human hepatocyte Hep G2 cell line HepG2 G2 cellll line li resistant i to APAP cytotoxicity i i Low P450 activity (CYP3A4) Variation in enzyme activities (source and culture conditions) UV Absorb bance at 254nm (mAU) Paracetamol Paracetamol Sulphate (2%) Time (min) 15 ATP (nmol/mgg protein) A Toxicity Paracetamol metabolites in HepG2 cells (24h; 2 x106) No coating 10 PS PLGA 5 0 0 Time (h) 24 Wang et al 2002 ; J Toxicol Sci Vol 27 (2002); Hewit and Hewit Xenobiotica (2004) In silico rat hepatocyte All data from published literature No assumptions in the model Modelling directs ‘wet-lab’ research Allows visualization of enzyme capacity Kim et al., 1992; McPhail et al., 1993 Visualisation of enzymatic capacities Rat Hepatocytes 100M APAP Rate off Sulphation R S l h i limited by: • • [APAP] A Amount & binding bi di affinity of sulphotransferase Kim et al., 1992; McPhail et al., 1993 Explore different scenarios through modelling Rat Hepatocytes 1mM APAP Sulphation: • Saturated • PAPS depletion • Rate limited by PAPS synthesis • Media [sulphate] GSH depletion occurring; [GSH] prevents toxicity GSH gives cell a time window for Phase II to clear APAP Kim et al., 1992; McPhail et al., 1993; Willson et al., 1991; Ochoa et al., 2013; Sweeny & Reinke, 1988. Explore different scenarios through modelling Rat Hepatocytes 5mM APAP • • • • • GSH depleted ~200 200 mins APAP-SG limited by rate of GSH synthesis GSH synthesis <<NAPQI formation = Covalent binding CYP450 activity not saturated [APAP] = faster & earlier GSH 6h shows little [APAP] media, GSH depletion insensitive to changes in other Phase II pathways Kim et al., 1992; McPhail et al., 1993; Willson et al., 1991; Ochoa et al., 2013; Sweeny & Reinke, 1988. In silico rat hepatocyte zonation periportal rat hepatocyte sulphation periportal centrilobular l t il b idl tiratt hepatocyte glucuronidation h t t centrilobular Well-mixed periportal centrilobular Araya et al., 1986 In silico rat hepatocyte sinusoid bile sinusoid bile Each individual cell has its own set of parameters D Decreased d bi bioactivation i i enhanced h d sulphation l h i iin PP regions i Expandable to include cell death & other cell types In silico sinusoid allows PBPK refinement Allows refinement of PBPK models Can be used for head-to-head evaluation of novel in vitro models of drug metabolism liver microsomes In vitro clearance Scale up Whole liver clearance PBPK model Prediction 1 Prediction 2 l single cell Prediction 3 sinusoid Evaluation of in vitro models of drug metabolism Summary Collaboration with mathematical modellers has enhanced experimentation Get more out of each experiment Directs experimentation to areas of importance or data deficiency In vitro mechanistic evaluation of hazard/risk = f1 Chemistry of drug + f2 Biology of individual + f3 Biology of model system Improved in vitro recapitulation of in vivo physiology = improved predictions R fi t off PBPK models d l Refinement Evaluation of novel in vitro models of drug metabolism Thank You Y University of Liverpool: Sophie Regan Ian Sorrell Steve Webb ([email protected]) Universityy off Bath: Marianne Ellis UCL: Rebecca Shipley University of Loughborough: John Ward Dennis Reddyhoff SimCyp: Iain Gardner
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