DRUG METABOLISM AND PHARMACOKINETICS (DMPK), H. Lundbeck A/S, LEGU@lundbeck.com November 2015
DMPK in Drug Discovery and Development Agenda Introduction Optimizing pharmacokinetic properties Absorption & bioavailability Distribution Elimination Clearance Understanding clearance mechanisms Drug metabolism Drug transporters Drug drug interactions and interindividual variability Summary: Drug discovery and development 2
H. Lundbeck A/S an introduction A pharmaceutical company with focus on brain diseases More than 700 million people are affected by brain disease worldwide Lundbeck is dedicated to address the global burden of brain disease Psychiatric diseases e.g. bipolar disorder, depression, schizophrenia Neurologic diseases e.g. Alzheimer s, Parkinson s, Huntington s A global company with head quaters in Valby, Denmark Total approximately 5500 employee s Approximately 1700 employees in Denmark Full value chain from research to production Want to know more? Go to: www.lundbeck.com/global/about-us/progress-in-mind www.youtube.com/user/progressinmind 3
Why study Drug Metabolism and PharmacoKinetics? DRUG DISCOVERY Optimise compounds to get... Good bioavailability get to its target Appropriate duration (1-2 doses/day) Low potential for drug-drug interactions predicted to man Provide basics for understanding of Toxicology Pharmacology From Rowland and Tozer, 1995 DRUG DEVELOPMENT Provide understanding of drug disposition Preclinical animal species tox coverage Human data Assess the risk for drug drug interactions (DDI) Decrease risk for drug drug interactions in the clinic Impact on the design of clinical studies Comply with guidelines from regulatory authorities
Reasons for compound attrition Kola and Landis 2004
Pharmacokinetics oral administration Drug concentration in plasma C max t max ADME = Absorption Distribution Metabolism Excretion
DMPK in Drug Discovery and Development Agenda Introduction Optimizing pharmacokinetic properties Absorption & bioavailability Distribution Elimination Clearance Understanding clearance mechanisms Drug metabolism Drug transporters Drug drug interactions and interindividual variability Summary: Drug discovery and development 7
Absorption Lipinski s rule of 5 to predict poor permeability/absorption (Lipinski et al, Adv Drug Delivery Rev 23:3-25, 1997) Mw > 500 Log P > 5 H-bond donors >5 H-bond acceptors > 10 Transporter substrates are exceptions from the rule.
Permeability Caco-2 Is the drug absorbed? No = low bioavailability! Papp: cm/sec x 10-6 correlates to human abs Indication of transporter mechanisms Automated incubations LC-MS/MS analysis Caco-2 Human colon epithelial cell line Differentiates to monolayer with tight junctions Alternative to Caco-2: PAMPA artificial membrane
Bioavailability - oral administration F = F gut x F abs x F hep Gut lumen Gut wall F gut F abs Portal vein Liver F hep F F hep = 1 - E hep
Distribution Drug distribution is the reversible transfer of drug to and from the site of measurement (blood/plasma) Distribution is influenced by -perfusion blood circulation to tissues -diffusion -physicochemical properties -binding to proteins etc From Rowland and Tozer, 1995
Volume of distribution (V) Not a real volume but a mathematical expression of the extent to which a drug distributes into tissues -Low V drug stays in blood/plasma -High V drug distributes extensively into tissues V relates the concentration at site of measurement to the total amount of drug in the body (L/kg) V=Amount drug in body/plasma concentration (L/kg bw)
Elimination: The concept of clearance (CL) Clearance is the apparent volume of plasma completely cleared of drug per unit time Rate of elimination = CL x C CL = Dose / AUC (iv dose) Unit: ml/min/kg
Hepatic clearance Hepatic vein Gall Bladder Bile duct Hepatic portal vein Hepatic artery The liver is the major site of drug metabolism
Drug metabolizing enzymes Route of elimination of the top 200 most prescribed drugs in 2002 Enzymes listed in FDA guidelines CYP: 1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 3A UGT: 1A1, 1A3, 1A4, 1A6, 1A9, 2B7, 2B15 Weinkers and Health Nat Rev Drug Discov 4:825-833, 2005
How to estimate metabolic clearance from in vitro studies?
Phase I +II II Metabolic stability Microsomes or hepatocytes How fast is the drug eliminated by the liver? Fast = low bioavailability! Fast = short duration! CL int - the intrinsic capacity of a system to clear a drug (µl/min/mg protein or cells) metabolites CL int = V max K m = V 0 / [S] ln Substrate Concentration 100 10 1 0 20 40 60 80 0,1 0,01 Time (minutes)
Prediction of in vivo clearance from in vitro data In vitro t 1/2 CL int = ln 2 /( t 1/2 x protein conc) In vitro CL int CL int = CL int x (mg microsomes/g liver) x (g liver/kg bw) Whole liver CL int Hepatic metabolic CL Whole body CL If well-stirred model CL hep,met, = (Q h x f u x CL int )/ (Q h + (f u x CL int ) CL = CL(HepMet)+CL(HepBile)+CL(Renal)+...
Interplay between V and CL Rat pharmacokinetics 10000 Concentration (nmol/l) 1000 100 10 C B A Elimination half-life T 1/2 = ln 2 x V / CL 1 0 5 10 15 Time (hours) CL(mL/min/kg) Vss(L/kg) T½ (h) A 20 14 10 B 70 12 3 C 80 0.6 0.5
Volume of distribution Clearance Absorption Half-life Oral bioavailability Dosing interval? Dose?
DMPK in Drug Discovery and Development Agenda Introduction Optimizing pharmacokinetic properties Absorption & bioavailability Distribution Elimination Clearance Understanding clearance mechanisms Drug metabolism Drug transporters Drug drug interactions and interindividual variability Summary: Drug discovery and development 21
Clearance mechanisms Total CL = CLMetHep + CLMetBile + CLRenal +... Hepatic Metabolism phase I and phase II enzymes Bile excretion sinusoidal and canalicular transporters Renal Passive glomerular filtration Active transport Extrahepatic metabolism Intestinal CYP3A4 Enzymes in blood Other extrahepatic enzymes
Hepatic clearance mechanisms Sinusoidal membrane Blood Drug Hepatocyte Drug Drug uptake transporters Metabolite Drug metabolising enzymes Canalicular membrane Bile canaliculus Efflux transporters
Uptake & Efflux Transporters SLCs Solute Carriers o OAT Organic Anion Transporter o OCT Organic Cation Transporter o OATP Organic Anion Transporting Polypeptides ABC series ATP Binding Cassette transporters o MDR Multi Drug Resistance proteins o MRP Multi drug Resistance-like Proteins o White family Drosophila white eye pigment gene Blood Hepatocyte
Drug transporters that influences drug disposition clinical evidence From International Transporter Consortium Giacomini et al Nature Rev Drug Disc 2010 Modified marking EMA recommended transporters in blue
Pravastatin O O O O O H OChiral 3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitor; key enzyme in cholesterol synthesis Used for the management of hypercholesterolaemia The target is in the liver Has short t 1/2 (~2h), low F (17%) but successful Has a good safety profile compared to other statins WHY? O
Disposition of Pravastatin Oral Oral tablet tablet Substrate for OATP1B1 MRP2 Gut OATP1B1 Liver MRP2 Enterohepatic recirculation t of t Systemic Circulation Active secretion Kidney
Simvastatin-induced myopathy increased due to increased plasma exposure - OATP1B1 polymorphism Niemi, Clin.Pharm.Ther. 2010 Pasanen et al, Pharmacogenet. Genomics 2006 Search study N.Engl.J.Med. 2008
Prediction of Human PK In vitro, human Species differences Scaling CL Absorption (Caco-2) Drug-drug interactions In vitro, animal In vivo, human In vitro/in vivo correlation Allometric scaling Vss (dog, human PPB) Absorption (rat) In vivo, animal
DMPK in Drug Discovery and Development Agenda Introduction Optimizing pharmacokinetic properties Absorption & bioavailability Distribution Elimination Clearance Understanding clearance mechanisms Drug metabolism Drug transporters Drug drug interactions and interindividual variability Summary: Drug discovery and development 30
Interindividual variability Age Sex Genetics Enzyme content Liver weight Organ blood flow... Nature Reviews Drug Discovery 6, 140-148 (February 2007) doi:10.1038/nrd2173 http://www.simcyp.com
Interindividual variation in drug response
CYP2D6 phenotypes in a Swedish population
Codeine metabolism to morphine is metabolised by CYP2D6 CYP2D6 CYP2D6 Poor metabolizer Codeine Prodrug No formation of morphine Morphine Active metabolite Lack of analgesia CYP2D6 Ultra-rapid metabolizer Formation of morphine Overdosing Adverse events
Drug drug interactions - CYP inhibition Does the drug inhibit Cytochrome P450? Yes = Potential drug interactions! P450 P450 metabolite metabolite
Metabolism of terfenadine OH OH CYP3A4 OH OH N N COOH Terfenadine Almost complete first pass extraction in man Active Metabolite Responsible for efficacy in man
Ketoconazole Ketoconazole is an antifungal agent O N N O O Cl O N N Potent inhibitor of CYP3A4 IC 50 value <1µM Antifungal dose is high (400mg twice daily) Circulating concentrations of ketoconazole exceed IC 50 for CYP3A4 inhibition Cl
Ketoconazole terfenadine interaction OH OH CYP3A4 OH OH N N COOH High circulating concentrations of terfenadine Low circulating concentrations of metabolite
Implications of terfenadine ketoconazole interaction High circulating concentrations of terfenadine Potential to prolong QT interval of the ECG Abnormal heart rhythm Small numbers of patients go on to develop fatal Torsade de Pointes (heart stops) Led to withdrawal of terfenadine from the market Increased questioning of Regulatory Authorities on QT and DDIs
CYP inhibition Recombinant enzymes Human liver microsomes CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 3A4 Human recombinant P450 enzymes substrate CYP product * IC50 = µm If IC50 < 10 µm potential interaction If [I]/Ki >0.1 - need to address in clinical study Discovery: Automated fluorescence based Development: LC-MS/MS analysis of metabolite
Induction of P450 enzymes Transcriptional regulation by nuclear hormone receptors Aryl hydrocarbon Receptor (AhR) Ligands: Polyaromatic hydrocarbons, dioxins (TCDD), Omeprazol Target genes: CYP1A1, CYP1A2, CYP1B1 Arnt - NUCLEUS - Constitutive Androstane Receptor (CAR) Ligands: Phenobarbital, CITCO Target genes: CYP2B6 Pregnane X Receptor (PXR) Ligands: Rifampin, Carbamazepine Target genes: CYP3A4, CYP2C8, CYP2C9, CYP2C19 PAH PB Rif AhR Hsp90 CAR PXR, GR? RXR RXR RXR CYP1A CYP2B CYP3A CYP2C Cross-talk between nuclear hormone receptors (AhR, CAR, PXR, GR, Hnf4 etc)
DDI Risk Assessment Victim (substrate) Enzyme/transporter phenotyping Drug disposition e.g. clearance Fraction of total elimination Mechanistic understanding Perpetrator (inhibitor/inducer) Enzyme/transporter IC 50 /K i Concentration plasma, liver, intestine Bound vs unbound Time dependence Also includes polymorphism Complex interactions how to assess the risk? Integration of data my modeling and simulation PBPK Iterative addition of new data Other relevant information - Co-medications - Biopharmaceutical Classification System etc
Physiology Based Pharmacokinetic (PBPK) Modelling and Simulation Jones and Rowland-Yeo 2013
PBPK modelling and simulation A DDI example compound A Compound A is mainly metabolized by CYP3A4 Assessment of DDI risks with compound A as a victim How will the plasma concentration change when codosing a potent CYP3A4 inhibitor How will the plasma concentration curve change when co-dosing with a strong inducer of CYP3A4? Median % fm and fe in absence of inhibitor(s) CYP3A4 Liver CYP3A5 Liver Renal
Prediction of the effect of a CYP3A4 inhibitor on the AUC of compound A 250E+00 Systemic Concentration (ng/ml) 200E+00 150E+00 100E+00 050E+00 200 mg itraconazole QD x 20 days 3 mg compound A on day 12 AUC ratio = 3.1 0.000E+00 0 45 90 135 180 225 270 315 360 405 450 Time - Substrate (h) CSys CSys with Interaction Co-administration of itraconazole (potent CYP3A4 inhibitor) may result in a 3 fold increase in the AUC of compound A A clinical DDI study is required to investigate the effect in vivo 45
Simulation of plasma concentration curves prediction of the effect of a CYP3A4 inducer Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Compound AF34134 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 A rif 600 600 600 600 600 600 600 600 600 600 600 Compound A Co-administration of a strong CYP3A4 inducer, rifampicin, with compound A leads to a decrease in AUC to 20% High risk of loosing the pharmacological efficacy of compound A Perform a clinical study to assess risk in vivo
DMPK in Drug Discovery and Development Agenda Introduction Optimizing pharmacokinetic properties Absorption & bioavailability Distribution Elimination Clearance Understanding clearance mechanisms Drug metabolism Drug transporters Drug drug interactions and interindividual variability Summary: Drug discovery and development 47
Understanding and predicting drug disposition an iterative process of data integration Input data
Why study Drug Metabolism and PharmacoKinetics? DRUG DISCOVERY Optimise compounds to get... Good bioavailability get to its target Appropriate duration (1-2 doses/day) Low potential for drug-drug interactions predicted to man Provide basics for understanding of Toxicology Pharmacology From Rowland and Tozer, 1995 DRUG DEVELOPMENT Provide understanding of drug disposition Preclinical animal species tox coverage Human data Assess the risk for drug drug interactions (DDI) Decrease risk for drug drug interactions in the clinic Impact on the design of clinical studies Comply with guidelines from regulatory authorities
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