Presentation on theme: "The Role of Drug Metabolism Studies in Optimizing Drug Candidates"— Presentation transcript:
1The Role of Drug Metabolism Studies in Optimizing Drug Candidates Kenneth Santone, PhDBristol-Myers SquibbMetabolism and Pharmacokinetics / Pharmaceutical Candidate Optimization
2Why All the Chemist's Wonderful Compounds Don't Become Drugs! ALTERNATE TITLE:Why All the Chemist's Wonderful Compounds Don't Become Drugs!
3Our Focus Unmet medical need First in class Best in class Need for efficiency and productivity enhancement
4What are we faced with? Industrialization of pharmaceutical research Unprecedented increase in identification of targetsCorresponding increase in throughput of chemistryBlurring of traditional discovery-development interfaceFocus and emphasis on “developability” (early go/no go decisions)Improve success rateReduce development timelineNecessity for increasing efficiency and productivity
5Drug Discovery Paradigm Shift ‘Old’ Modelof Drug DiscoveryValidated HitsDetailed Physicochemical,ADME &Tox WorkupDevelopmentCompoundEfficacy &SelectivityTestingHitsLeadCandidatesPhysicochemical, ADME&ToxWorkupSelectivity TestingDesign& SynthesisPATScreening &Predictions‘New’ ModelMore informed decision making during Lead Optimization, through quicker and earlier evaluation of PAT attributes
6*why great compounds don’t always become drugs The Hand-off from Drug Discovery to Development: The Top Ten Quotations We All Know and Love*10.9.8.7.126.96.36.199.2.1.“The molecular weight? Why? Is that a problem?”“We’ll need eight different capsule strengths for Phase I.”“The compound is very potent in the in vitro screen but does not work well in the animal efficacy model.”“Now that you mention it, our solutions were a little cloudy.”“The compound is highly insoluble but Pharmaceutical Development will fix the problem.”“BMS-XXXXXX is a highly potent and selective inhibitor of (the target). In mouse models, the optimal dose was 200 mg/kg.”“Toxicity?! It’s not the drug; must be a metabolite unique to that animal species.”“Animal bioavailability ranged from 65% to <1%, depending on species.”“Gee, we didn’t have any problems when we gave it in DMSO.”“It’s a great compound, but it has formulation problems.”Partially adapted from R.A. Lipper*why great compounds don’t always become drugs
7Critical Interfaces in Drug Discovery* ChemistryBiologyActivitySafetyMetabolism & PharmacokineticsPharmaceuticsOptimized Compound*Analytical Chemistry (Bioanalysis) involved in every one of these disciplines
8* Absorption, Distribution, Metabolism, Excretion Role of ADME* StudiesSelection of quality drug candidate for developmentDevelopabilityFirst-in-class vs. best-in-classCrisp go/no go decisionsOptimization of drug discovery and early development processesMulti-tiered approach for ADME studiesEqual partnership with all functional areasLead Discovery Biology Chemistry Pharmaceutics Drug Safety Analytical R&D Clinical Pharmacology Process ChemistryBlurring of traditional discovery-development interface* Absorption, Distribution, Metabolism, Excretion
9Selection of Drug Candidates: Focus on Developability PermeabilityTransportMetabolic stabilityP-450 mediated drug interactionsPK/PD assessmentDistributionProtein bindingBiopharmaceuticsActive/reactive/ toxic metabolitesIn vivo PK/bioavailability in animalsPrediction of PK and efficacious doses in humans
10Tiered-Approach for ADME Studies Hits to LeadIn vitro StudiesPermeabilityP450 inhibitionMetabolic StabilityIn silico predictionsObjectiveDevelop SARChemotype selection
11Tiered-Approach for ADME Studies Lead OptimizationIn vitro StudiesPermeability/transportP450 inhibitionMetabolic StabilityReaction phenotypingProtein bindingIn vivo PKCassette dosingIndividual PKTissue penetrationEarly biotransformationObjectiveIdentify a lead compoundFeedback to chemistry/biology
12Tiered-Approach for ADME Studies Lead SelectionAbsolute bioavailability in pharmacology/toxicology modelsDose dependency in PKMechanism of absorptionAssess potential for DDICharacterization of metabolites, routes of eliminationAssess formation of active metabolitesInterspecies differences in metabolism and in vitro-in vivo correlationExtrapolation of ADME properties to man from in vitro and in vivo dataDetermination of PK/PD relationships; help selection of doses for First in Human studiesObjectiveCharacterize the lead compoundIdentify risks/opportunities
13How In Vitro Metabolic Stability Relates to Clearance? TBC = CLhepatic + CLrenal + CLotherCLhepatic = CLmetabolism + CLbiliaryCLmetabolic = fB * CLintrinsic * Qh / fB * CLintrinsic + Qhwell stirred model of organ extractionIntrinsic Clearance (CLi) = Vmax / Km = vo / Cuthrough rearrangement of the Michaelis-Menton eqn, assuming drug conc is < KmDepletion or Half-Life Method:CLi = (0.693 * liver wt) / (in vitro t1/2 * amount of liver)3
14Tools to Predict Metabolic Clearance In Vitro SystemsLiver microsomeshigh throughput and most commonmostly oxidative (CYP & FMO)S9 fractionhigh throughputPhase I & Phase II metabolismHepatocyteslow throughputcell membrane/transportersintracellular concentrationIn Vivo Animal ClearanceIn SilicoIn Vitro - In Vivo Correlation3
15Metabolic Stability to Select Compounds with Potentially Longer Half-LifeHuman Metabolic Stability: Microsome vs Hepatocyte0.4R2= 0.80.3Microsome Total Metabolic Rate0.2BMS:Y0.10.0-112345Hepatocyte Metabolic RateLead compound is primarily glucuronidated in humansHuman in vitro systems with combination of oxidation andglucuronidation employed for selection of back up
17Major Reactions Involved in Drug Metabolism HYDROLYSIS REACTIONS (Esterase, ?LM+NADPH)Ester Hydrolysis: aspirin, cocaineAmide Hydrolysis: lidocaine, procainamideCONJUGATION REACTIONS (Phase II, hepatocytes)Glucuronidation: morphine, ibuprofenSulfation: acetaminophenAcetylation: sulfonamides, isoniazid
18Metabolic Stability Summary Not all metabolism is hepatic.Incubation concentration < Km balanced with assay sensitivity.Need to correlate with in vivo model.Fast in vitro clearance generally implies fast in vivo clearance, the reverse need not be true.Confounding physical-chemical properties.solubility, stability, purity, non-specific bindingReal concentration at enzyme active site?protein binding, cell penetration, non-specific bindingIn vitro systems generally underestimate CLi due to non-specific binding.Can the stability be too good? Yes, in certain situations.Many unknown factors to can contribute to a poor in vitro - in vivo correlation or poor estimation of human metabolic stability.Nonetheless, in vitro methods are still the best method for predictions15
19Drug-Drug Interaction Summary Major drug interactions are caused by either inhibition or induction of drug metabolizing enzymes.Semi-quantitative predictions of drug interactionsmany unknown factorshuman ADME properties in vivoModels provide numbers that must be placed in context with multiple factors:therapeutic areatherapeutic index, route of administrationmarket competitionAnimal models are not predictive of human interaction potential ???Static nature of in vitro systems compared to the dynamic in vivo systemMixtures of interaction mechanisms from the same compound are extremely difficult to predict:reversible + irreversible inhibitioninhibition + induction
20Assessment of Active Metabolites IssueSimilar metabolism and in vitro activity profile but different in vivoactivity profileApparent PK/PD disconnectSolutionRapid in vitro metabolism and biological activity assays
21Assessment of Active Metabolites Structural identification of active metabolitesMS/MS indicated presence of monohydroxylationNMR showed site of hydroxylationSubsequent stepsMonohydroxylated metabolite synthesizedActivity and PK properties confirmed
22Assessment of Reactive Metabolites A number of functional (chemical) elements have been associated with problems in drug discovery leading to toxicityMetabolic activation to reactive intermediatesInterference with metabolic processesClinical manifestations include (preclinical measure)Cellular (hepatic) necrosis (animal toxicity)Idiosyncratic toxicity (glutathione adducts, protein covalent binding, immunogenic response)Drug-drug interactions (mechanism-dependent CYP inhibition)
23Examples of Reactive Metabolites FuransFuran substructure is associated with toxicity (eg. aflatoxin) and with CYP inhibition (eg. bergamottin)
24Examples of Reactive Metabolites ThiophenesThiophene substructure has been associated with several types of toxicity (predominately hepatotoxicity). Other thiophene containing drugs: ticlopidine, clopidigrel, raloxifene.
25Examples of Reactive Metabolites Anilines, NitroaromaticsAnilines are associated with a number of types of toxicity (eg. methemoglobinemia, skin rashes, etc.). Nitroaromatics are primarily activated by initial reduction, often in the gut, followed by N-oxidation.Anilines of polycyclic aromatic systems are often potent mutagens and carcinogens (eg., naphthylamine, aminofluorene) through conjugation of the hydroxylamine and subsequent loss of the conjugate to leave a nitrenium ion.
26Examples of Reactive Metabolites Amines, alkylaminesThe metabolism of amines or alkylamines is generally related to time- dependent inhibition of CYP enzymes, with the nitroso species forming a tight complex with the heme iron, known as a MI complex. Other compounds that undergo this type of transformation and inhibit CYPs are TAO, erythromycin and verapamil
27Examples of Reactive Metabolites Quinone, QuinoidQuinone-like compounds can exert their effects through direct alkylation of nucleophiles or through redox cycling between their oxidized and reduced forms
28Examples of Reactive Metabolites AcetylenesAcetylenes have been found to be time-dependent inhibitors of CYP enzymes.
29Examples of Reactive Metabolites Acyl glucuronidation formationAcyl glucuronides have been implicated in both direct hepatic damage and idiosyncratic toxicities
30Challenges and Opportunities HTS screens for prediction of permeability, metabolic stability, metabolic reactivity and DDIHow are we using these data?Retrospective analysis on return of investmentThe numbers in gray zone!Secondary assays for better predictabilityApplication of animal PK/bioavailability data for lead optimizationAdequacy of permeability and metabolic stability dataAnimals vs. humans: quantitative and qualitative differences in ADME propertiesInformed decision based on drug metabolism and pharmacokinetic dataLow bioavailability vs. oral efficacyRole of metabolite(s), reactivity of metabolite(s)Protein bindingIn vitro- in vivo correlation in animals and extrapolation to humansIssue of enzyme induction in humansIn-vitro models and predictabilityFalse and real alarm from in-vivo animal dataHTS screens for prediction of permeability, metabolic stability and DDIHow are we using these data?Any retrospective analysis on return of investment?The numbers in gray zone!Cost / benefit ratio?Application of animal PK/bioavailability data for lead optimizationAdequacy of permeability and metabolic stability dataAnimals vs. humans: quantitative and qualitative differences in metabolic clearanceInformed decision based on drug metabolism and pharmacokinetic dataLow bioavailability vs. oral efficacyShort half-life vs long PD effectsRole of metabolite(s)Long half-life vs short PD effectsProtein bindingIn-vitro P-450 inhibition values and predictions for the potential of DDI in humansWhat is our success rate?Are these data used intelligentlyTime-dependent and mechanism based inhibition – the relevance issuePredator vs. prey issueThe IC50 values in gray zoneLack of animal models
31Challenges and Opportunities Use of biomarkersIn-vivo biology, animals vs. humansDevelopment and validation of assaysTransfer from preclinical to clinical laboratoriesBiomarkers = Surrogate marker = Efficacy/ToxicityA balancing act of emerging scienceThe feedback loopsTo and from chemistryTo and from biologyTo and from drug safetyTo and from pharmaceuticsTo and from clinical pharmacologyVolume of dataConversion of information into knowledgeTiming and availability
32A Focused Application of ADME Studies Active involvement earlier in the Discovery ProcessTimely guidance to Chemistry to select chemotypes with desirable ADME propertiesMaximize informed decision making during Lead OptimizationImproved ability to predict human metabolism and pharmacokineticsStronger partnerships with Drug Discovery and all areas of Pharmaceutical Development
33Our MissionTo ensure that no development candidate fails in the clinic due to anunforeseen metabolic orpharmacokinetic property
34Saeho Chong, Punit Marathe, Wen Chyi Shyu and Mike Sinz AcknowledgementsDavid Rodrigues and Griff HumphreysSaeho Chong, Punit Marathe, Wen Chyi Shyu and Mike SinzAnd finally ….