Assessing the role of hepatic uptake in drug clearance - Pharmacokinetic and experimental considerations Peter Webborn ISSX Short course Toronto 2013 1
Defining the why, when and how of Transporter studies is rapidly maturing Methods Brouwer et al (2013) In vitro methods to support transporter evaluation in drug discovery and development Regulatory Drug Transporter White Paper. Nature Reviews Drug Discovery 9, 215 236, (2010) Modelling Chu et al (2013) Intracellular drug concentrations and transporters: Measurement, modelling and implications for the liver 2 Key challenge: Predicting human kinetics Plasma clearance Free intracellular concentrations Fraction of clearance though biliary secretion
This talk addresses two Key issues using hepatocytes for clearance predictions You need to know precisely what you are trying to measure and predict. Understand the PK models that underpin the test system Making measurements of key compounds is often at the limits, - it s really important to have a good understanding of the test system and the variability in measurements Characterise the biological system you are using Simultaneously model as much data as possible In this talk there is no discussion of specific transporters or compounds, the focus is on underlying principles and scenarios 3
Hepatic uptake adds a layer of complexity / risk to candidate drugs CYP DDI Transporter DDI Target organ toxicity Predicting Human kinetics Higher clearance / lower bioavailability 4 Unless the drug target is within hepatocytes - Uptake needs to be managed /reduced/avoided
How would you know a chemical series is susceptible to active uptake? Charged molecules (Acid /zwitterions) Higher Vss than expected Screened for it Clearance could not be predicted by standard methods Transporters will only affect the kinetics of a minority of compounds 5
Hepatocyte based experimental systems Binary systems = media + cells Used for metabolism and/or uptake studies eg suspended cells Tertiary systems = media + cells + canaliculi eg sandwich / 3D cultured hepatocytes Used for metabolism and/or uptake studies Key Issue Expression levels/activity System must be appropriate for compounds
What is happening in a hepatocyte assay used to estimate rate of metabolism (int) of a permeable compound? Total Conc Cell Cell and Medium Time Medium int 0.693V T 1 2 Binding dominates early phase, followed by elimination int is corrected for binding in the system to obtain int,u int,u = int / fu inc This correction is really for defining to the true medium concentration (on the assumption that this equals the free intra-cellular concentration)
Log(Qh* b )/(Qh- b ) Even in the simplest case (highly permeable compounds, eliminated by metabolism) hepatocytes do not directly predict hepatic clearance Raw int In vitro scaling factors, fu P, R b, fu inc Scaled int Lab specific correction Predicted In vivo int Well stirred model (WSM) Predicted in vivo clearance A regression approach adjusts for systematic underpredictions observed when scaling in vitro int directly using the well stirred model, unbound fractions in blood and the in vitro matrix, and physiological scaling factors. Riley, McGinnity and Austin (2005) Log(int*SF*fu b /fu inc ) All evidence suggests transporter assays underestimate in vivo parameters - Correction factors will need to be established and applied
Uptake is the rate-limiting step in the overall hepatic elimination of pravastatin at steady-state in rats Yamazaki, M., Akiyama, S., Nishigaki, R., Sugiyama, Y. 1996 Pharmaceutical Research 13 (10), 1559 What is this really saying? Consider this example: in a 3 step reaction: For the formation of D (excretion into bile) - The rate determining step is always the slowest step in the process. For loss of A, the rate determining step is always k1 (plasma clearance) In this scenario: The rate of conversion of A to B depends on K1, K2 and K4. For poorly permeable compounds uptake is the rate determining step in the plasma clearance of active uptake substrates (because the back-rate is insignificant) 9
Modelling Uptake substrates: The well-stirred model applied to uptake substrates Standard WSM - metabolism + highly permeable compounds Q Q h h. f ub f. ub. int, met int, met WSM - uptake and metabolism (intracellular free extracellular free) Q Q h h. f ub f. ub. int, app int, app int, app int, met [ Cu ] [ C ] u liver plasma [ C [ C u u ] ] liver plasma int, uptake int, met int, pass int, pass int, app int, met int, uptake int, met int, pass int, pass Webborn et al 2007
Low permeability uptake substrates Clint,uptake >>Clint,pass Clint,met >>Clint,pass int, app int, met int, uptake int, met int, pass int, pass int, app Cl int, uptake Plasma clearance determined by uptake rate ( Uptake is the rate limiting step in the hepatic elimination of pravastatin in the rat )
Simulation of the effect of changes in passive diffusion and uptake on hepatic extraction. Cl int,met fixed to give a hepatic extraction of 0.5 (if no transporters involved + permeable) int,uptake was varied from 1 to 1000 ml/min 1.2 int,app int,met int,uptake int,met int,pass int,pass E h 1.0 0.8 0.6 0.4 0.2 0.0 1 3 10 32 100 316 1000 1 10 100 1000 10000 Estimate parameters Apply Model Assess predictivity Good example Umehara and Camenish (2012) (radiolabelled drugs) Cl int,pass
Experimental / Data handling challenges 1. Uptake into suspended hepatocytes 2. Biliary clearance estimates using sandwich cultured hepatocytes 13
The Core Issues Uptake For permeable compounds active uptake gets difficult to measure Because acidic/zwitterionic compounds have low volumes, clearance must be low for half-life to be reasonable: Small contributions from transporters can be critical. Efflux Estimation of biliary Clearance using Sandwich culture systems requires a subtraction step Drug in cells + Bile minus Drug in cells = Drug in bile IVIVE is challenging in complex systems In vivo measurements are difficult (and rare) in man When measurements are at the limits, it s really important to have a real understanding of the errors in the system 14
pmol/million cells Uptake assays - Data Measuring int,uptake int = V/S (S<<<Km) or int = Vmax / Km 140 Compound + inhibitor Measure rate (V in pmol /min) not rate constant (k min -1 ) Requires [S] to be constant. Is it? What about the Intercept? Concentration dependence can yield Vmax, Km and int,pass (Pdiff) V = (Vmax*S)/(Km+S) + Pdiff*S 120 100 80 60 40 20 0 0.0 0.2 0.4 0.6 0.8 Time (min) Model whole data set a in one step - Include all replicates 15
pmol /10^6 cells Uptake assays - Data Measuring int,up int = V/S (S<<<Km) or int = Vmax / Km 500 450 Measure rate (V in pmol /min) not rate constant (k min -1 ) Requires [S] to beconstant. Is it? What about the Intercept? Concentration dependence can yield Vmax, Km and int,pass (Pdiff) V = (Vmax*S)/(Km+S) + Pdiff*S 400 350 300 250 200 150 100 50 0 0 0.25 0.5 0.75 1 1.25 Time (min) 1 um 5 um 10 um 25 um 50 um 100 um 150 um Model whole data set a in one step - Include all replicates 16
Initial rate (pmol/min/million cells) Uptake assays - Data Measuring int,up int = V/S (S<<<Km) or int = Vmax / Km Measure rate (V in pmol /min) not rate constant (k min -1 ) Requires [S] to beconstant. Is it? 8000 7000 6000 5000 37 C Exp87 37 C Exp86 4 C Exp87 4 C Exp86 Active Passive Total AZ12441665 What about the Intercept? 4000 Concentration dependence can yield Vmax, Km and int,pass (Pdiff) V = (Vmax*S)/(Km+S) + Pdiff*S 3000 2000 1000 0 0 50 100 150 200 250 300 Conc. µm Model whole data set a in one step - Include all replicates 17
Model the data 18 Menochet et al (2012) Drug Met Disp 40:1744-1756
Model the data 19 Menochet et al (2012) Drug Met Disp 40:1744-1756, see also Poirier et al (2009)
Predictions of human kinetics based on uptake data - scaling factors Menochet et al (2012) Large and variable scaling factors 20
Predicting biliary Clearance Some basics int,app What do we mean by biliary clearance? What do we mean by biliary intrinsic clearance? int,biliary int, biliary = V/S, int, biliary = rate of efflux/ Free intracellular conc Not that useful, in itself for predicting Plasma clearance? What you really want to know is the contribution of canalicular efflux to plasma clearance int, biliary app = V/S, concentration int, biliary app = rate of efflux/ media Note: For highly impermeable compounds, int,app =int,up For mixed canalicular efflux/ metabolism /uptake substrates - Use the int,app concept int,app ( int,biliary int,met ) int,biliary int,uptake int,met int,pass int,pass 21 Are transporter / metabolism systems active at physiological levels? - That s the real challenge. How good are your sandwich /3D cultures?
Sandwich Cultured hepatocytes Abe et al (2008) JPET 326,3 983-990 BEI = (Drug in cells + Bile) minus (Drug in cells) / (Drug in cells) Technical Challenge Estimation of int,biliary also requires the subtraction step Errors in BEI often less than expected from non-paired data What could drive this? 22
Sandwich Cultured hepatocytes IVIVE the real test Abe at al (2009) Use of Sandwich-Cultured Human Hepatocytes to Predict Biliary Clearance of Angiotensin II Receptor Blockers and HMG- CoA Reductase Inhibitors Nakakariya et al (2012) Predictions 7-300 fold out How to apply regression based corrections in multiparameter systems? 23
Two expressions for biliary clearance int,app Nakakariya et al (2012) int,biliary int,biliary from SCRH a better predictor of int,biliary in vivo Than int,app from SCRH predicts int,app in vivo Implies Uptake transporters are deficient in SCRH Not a useful approach for human predictions? Not an issue in SCHH? 24
Prediction of plasma clearance of compounds eliminated in bile Clint Clint,app Passive Uptake Biliary* Metabolic Apparent KPuu % in bile Biliary ** 200 0 0 10 10 1.0 0 0 200 0 10 10 18 0.9 50 9 1 50 10 10 49 2.4 50 24 1 50 20 10 49 1.6 67 33 1 50 30 10 50 1.2 75 37 1 50 40 10 50 1.0 80 40 1 30 40 10 30 0.6 80 24 1 10 40 10 11 0.2 80 9 int,app ( int,biliary * Biliary Clint based on free intracellular concentration ** Biliary Clint,app based on media concentration KPuu int,biliary int,uptake Both approaches should get to the correct answer, if activities conserved int,met ) int,met int,pass int,pass 25
Prediction of plasma clearance of compounds eliminated in bile and also metabolised Clint Clint,app Passive Uptake Biliary* Metabolic Apparent KPuu % in bile Biliary ** 1 50 10 10 49 2.4 50 24 1 50 10 0 46 4.6 100 46 1 50 30 0 49 1.6 100 49 int,app int,biliary x int,met int,biliary int,uptake int,met int,pass int,pass * Biliary Clint based on free intracellular concentration ** Biliary Clint,app based on media concentration Care needed if metabolic component estimated separately, eg from microsomes 26
Final Word Characterise your cells thoroughly, make extensive use of reference compounds In vitro transporter data should be relative to measured media concentrations If IVIVE not yet robust, performance of project compound relative to compound X can be useful. eg If the human kinetics was similar to valsartan, would our compound be credible Hepatic uptake can be the key process that determines the plasma clearance of compounds eliminated in bile this should direct your IVIVE experiments Emerging transporter expression level data may aid IVIVE issues 27 Set area descriptor Sub level 1