5 “All things are toxic and there is nothing without poisonous qualities: it is only the dose which makes something a poison”PARACELSUS ( )Pharmaco/ToxicokineticsHow the chemical is eliminated from the body or activated into a toxic species (ADME )Pharmaco/ToxicodynamicsHow the chemical exerts its pharmacological effect/ toxicityTarget receptor/cell/organ
6 RISK ASSESSMENT METHODS INTAKE WITH NO APPRECIABLE EFFECTS eg ADI LOW - DOSEEXTRAPOLATIONRISK ASSOCIATEDWITH THE KNOWN INTAKEQUANTITATIVERISK ASSESSMENTNO THRESHOLDTHRESHOLDNOAEL ANDSAFETY FACTORSINTAKE WITH NO APPRECIABLE EFFECTS eg ADINON - QUANTITATIVERISK ASSESSMENT
7 Derivation of the Acceptable Daily Intake (ADI) ADI (mg/kg/day) = NOAEL(mg/kg) / 100
8 The use of uncertainty or safety factors (UFs) SPECIES DIFFERENCESHUMAN VARIABILITY1010KINETICSDYNAMICSExtrapolation from group of test animals to average human and from average humans to potentially sensitive sub-populations
9 100 - FOLD UNCERTAINTY FACTOR INTER-SPECIESDIFFERENCES10 - FOLDINTER-INDIVIDUALTOXICO-DYNAMIC10 0.42.5KINETIC10 0.64.0TOXICO-DYNAMIC10 0.53.2KINETICChemical specific adjustment factors can replace the default uncertainty factors (WHO, 2001; IPCS, 2006)
10 Towards a more flexible framework ToxicokineticsToxicodynamicsData-derivedorPathway-relatedUncertainty factorsgeneral defaultData-derivedorprocess relatedUncertainty factorsgeneral defaultInterspecies differencesHuman variabilityUFs for main routes of metabolism in test species and humans –intermediate option between default factor and chemical specific adjustment factorsAdapted from Dorne and Renwick, 2005 Toxicol Sci 86, 20-26
11 Major Routes of chemical metabolism and excretion Phase I enzymesCytochrome P-450, ADH, EsterasesPhase II enzymesConjugation reactionsGlucuronidationSulphationN-acetylation (Polymorphic)Amino acid conjugation% of Pharmaceuticals Metabolized by Individual Cytochrome P450’s in manP4502D6P4501A2P4502A6P4503AP4502C9P4502C19P4502E1Renal excretionCYP2C9, CYP2C19, CYP2D6* Polymorphic (Extensive and Poor metabolisers, EMs and PMs)*Caucasian 8% PMs 92% EMs
12 CYP2D6 Substrates Antiarrhythmics Encainide S-mexiletine Analgesics DextromethorphanCodeineTramadolAntipsychoticsRisperidoneHaloperidolAntidepressantsFluoxetineParoxetineAmitriptyllineDesipramineImipramineVenlafaxinePesticidesChlorpyrifosDiazinonMethoxychlorBeta BlockersBufuralolPropafenoneMetoprololpropranololCarvedilolAdapted from Dorne et al., 2002 FCT 41,
13 Introducing metabolic and toxicokinetic data into risk assessment
14 Aims Quantify human variability in kinetics for major metabolic routes Markers of chronic exposure (plasma Clearance)Markers of acute exposure (plasma peak concentration Cmax)Prefer the oral route (gut + liver): relevance to environmental contaminantsComparison to the IV route (liver)Identify susceptible subgroups of the populationDerive pathway-related uncertainty factors for each subgroup
15 Methods Literature searches Medline, Toxline and EMBASE (1966-current) Compounds metabolised by single route (complete oral absorption, >60% of dose)In vitro metabolism data (cell line, liver microsomes): metabolic routeIn vivo excretion data: HPLC detects parent compound and metabolitesIn vivo pharmacokinetic studies for human subgroups
16 Methods IIMeta-analysis of studies reporting PK parameters for each compound/ parameter/ subgroup of the population:Mean, SD and CVN (normal distribution) transform togeometric mean and GSD, CVLN (lognormal distribution)Derive Coefficient of variation (CV) for each compound/parameter and pool CVs to get overall value for metabolic route (pathway-related variability)Derive Pathway-related uncertainty factors (to cover 95, 97.5 and 99th centiles) using CV and magnitude of difference in internal dose (clearance or Cmax) between healthy adults and subgroups
17 Results Database for >200 compounds HPLC method for the detection of parent compound and metabolitesIn vitro metabolism of compound inter-species and humanIn vivo metabolism data (% excretion for compound and each metabolite HPLC data)Kinetic studies for each compound (> 2500 studies)Subgroups of the human population (healthy adults, genetic polymorphism, interethnic differences, neonates, children and the elderly)
18 Healthy adults Monomorphic pathways Low variability in healthy adults (<30%), exception of CYP3A4 : role of gut CYP3A4, P-glycoprotein, polymorphismPathway n compounds n CV Pathway-related UFs (99th)CYP1ACYP3AGlucuronidationRenal excretionPathway-related UFs below the kinetic default factor (3.2)
19 Polymorphic pathwaysVariability for polymorphic pathways larger than for monomorphic pathwaysLarge difference in internal dose between EMs and PMs for CYP2D6 (9-fold) and CYP2C19 (12-fold)Pathway-related uncertainty factors above the current kinetic default factor (3.2)Pathway n compounds n CV Pathway-related UFs (99th)CYP2C19 (EM)CYP2C19 (PM)CYP2D6 (EM)CYP2D6 (PM)
20 Quantitative involvement of dose handling on kinetic differences: CYP2D6RatioEM/PM20406080100% CYP2D6 metabolism in EMsExponential relationships between ratio EM/PM and % CYP2D6 metabolismPMs covered by pathway-related UFs for substrates with up to 25% (dose) of CYP2D6 metabolism in EMs
21 Quantitative involvement of dose handling on kinetic differences: CYP2C19PMs covered by UFs for substrates with up to 20-25% (dose) of CYP2C19 metabolism in EMs.
22 Results: Subgroups of the population Interethnic differences Historically smaller database for non-Caucasian subjects: Modern man : mixture of ethnic groups and more so in the future !Less variability in Asian vs Caucasian for CYP2D6 and CYP2C19 (+ different frequencies of phenotypes)Pathway-related uncertainty factors above kinetic defaultfor CYP2C19 and NAT metabolismEx relationship for CYP2C19 and ratio EMs/PMs in Asian healthy adults (R2=0.87) : Slope 100% metabolism via CYP2C19 gives a ratio of 30 (80 in Caucasian !)
23 Children and neonatesPotential susceptible subgroups of the population:-Immaturity of phase I, phase II and renal excretion (particularly for neonates)-Quantify differences in internal dose from in vivo PK database-Provide pathway-related UFs for these subgroups-Identify datagaps
24 NeonatesThe most susceptible subgroup for all pathways with data: immaturity of phase I, II metabolism and renal excretion. No reliable data available for polymorphic pathways.Pathway Nc n CV Ratio Pathway-related UFs GM 95th 99thCYP1ACYP3AGlucuronidationGlycine ConjugationRenal excretionAll data from the IV route
25 ChildrenLimited data-Susceptible subgroup for both polymorphic CYP2C19 and CYP2D6Pathway Nc n CV Ratio Pathway-related UFs GM 95th 99thCYP1A2*CYP2CCYP2DCYP3AGlucuronidationRenal Excretion** IV data (all other data PO route)
26 Polymorphism in metabolism and Children and neonates: Examples Fluoxetine and paroxetine metabolised largely via CYP2D6 and other CYP isoforms (CYP2C9, CYP3A4 and CYP2C19)Large inter-individual differences in kinetics in healthy adults and children: up to fold variation in clearance in healthy adults PMs (including 2 PM children)Holden, C. Prozac Treatment of Newborn Mice Raises Anxiety. Science Oct 29;306(5697):792.Ibuprofen and indomethacin in preterm neonates : up to 10-fold difference decrease in clearance : immature CYP2C9, glucuronidation and renal excretion.Lansoprazole (CYP2C19-CYP3A4): 1 neonate and 1 infant PM (3- and 7-fold decrease in clearance)
27 Predicting human variability in toxicokinetics using Monte Carlo modelling
28 Latin hypercube sampling: variant of Monte Carlo (random), stratified sampling throughout the distribution.Compounds handled by multiple pathways : predict variability and uncertainty factors for healthy adults, children and neonates. Combine distributions describing pathway –related variability and quantitative metabolism data.Compare Simulated data and published kinetic data.
29 Poor metabolisers, neonates and children : -GM ratio of internal dose (mean) compared to healthy adults and pathway-specific variability (GSD) for each pathway.-Neonates and children: ideally use metabolism data but often not available: liver microsome / in vitro and/or healthy adult data-Polymorphic pathways : Combine distribution for EM and PM using frequency of EM and PMs ( for CYP2D6 7.4% PM in Caucasian)
32 Pharmacokinetic interaction between probe substrates of polymorphic CYPs Literature searches for interaction studies between major probe substrates (> 70% of the dose metabolised by each CYP) of CYP2D6 and CYP2C19, inhibitors and inducers of each enzyme.UFs to cover percentiles for subgroup of populationRelevance: a number of pesticides are substrates and inhibit polymorphic CYPs (chlorpyrifos, diazinon)..Extensive metabolisers (EMs) are at risk if the metabolite produced the toxicant. Poor metabolisers (PMs) would be at risk if the parent compound is the toxicant.
33 CYP2D6 CYP2D6 NON-COMPETETIVE CYP2D6 INHIBITION BY CIMETIDINE DRUG A ACTIVE SITECYP2D6CYP2D6Cimetidine binds away from active site, changing structure so that Drug A can no longer fitsCimetidineCimetidine
34 Paroxetine binds reversibly with drug A to the active site COMPETITIVE INHIBITION OF CYP2D6 BY PAROXETINEDRUG AParoxetineACTIVE SITEParoxetine binds reversibly with drug A to the active siteCYP2D6CYP2D6
35 CYP Enzyme Induction ↑↑CYP expression Pregnane X receptor ↑↑ mRNA transcriptionHyperforinCYP3 A4 inductions by SJW occurs when Hyperforin, the active ingredient in SJW binds to the pregnane x receptor. Pregnane x receptor binds with retinoid x receptor which that resulting in mrna transcription and finally cyp3a4 transcriptionRifampinPregnane X receptorRetinoid X Receptor
36 Polymorphic CYP inhibition CYP2D6 Inhibition will increase internal dose in EMs and UF for toxicokinetic UF (3.16) would not cover this subgroup for binary mixtures. PMs not affected : alternative pathways of metabolism, slow extensive metabolisers (SEMs) are an intermediate
37 INHIBITION/ INDUCTION Inhibition/induction of polymorphic CYP increase/decrease exposure to therapeutic drugs in EMs (and PMs for induction). Current UF for human variability in toxicokinetics (3.16) would not cater for these interactionsResults variable ; detailed analysis to classify interaction according to constant of inhibition (Ki)In vivo database on therapeutic doses much higher than pesticide levels but only in vivo data quantifying human variability in toxicokinetic interactions.
38 RELEVANCE TO HUMAN RISK ASSESSMENT Current levels of exposure of organophosphates (< 10 uM) : shown to inhibit imipramine metabolism in human recombinant enzymes and liver microsomes (Di Consiglio et al., 2005).Many pesticides known to either inhibit or induce cytochrome P-450 isoforms in animals and manMore work to characterise their potential in vivo effects at the current level of exposure using recombinant technology and toxicokinetic assays (Hodgson and Rose, 2005).
39 CONCLUSIONS Human data are essential Most susceptible subgroups To replace default uncertainty factors with chemical-specific dataTo identify high risk subgroups regarding susceptibility to chemical toxicityMost susceptible subgroupsPoor metabolisers (Healthy adults), neonates, children for polymorphic enzymes but very little dataMost suceptible subgroups (mixtures)Extensive metabolisers for polymorphic enzymes with inhibitors if metabolite toxicNeed for well characterised metabolism before compound on the market Use of in vitro techniquesMany pesticides metabolised via polymorphic CYPs
40 CONCLUSIONS II Advanced statistical techniques Uncertainty analysis, Probabilistic and Bayesian approachesAnalysis of toxicodynamics (mechanisms of toxicity)Very little data, use of pharmacodynamic dataIn vitro, in silico data and OMICSRegulatory bodies, Risk managers ?Integrate data (including susceptible subgroups…) in the risk assessment processIndustryIntegrate relevant data (compound specific metabolism PK, PD, TK, TD…) and relevant modelling techniques for risk assessment of compounds before market
41 Many thanks toProfessor Emeritus Andrew Renwick OBEand-The Department of Health (UK),-Health and Safety Executive (UK),-Food Standard Agency (UK),-European Commission within NO MIRACLEfor funding this work