RSC, February 2014

Interplay between enzymes andtransporters in defining hepatic drugtransporters in defining hepatic drug

clearance and intracellular concentration of drugs

J Brian HoustonJ Brian HoustonCentre for Applied Pharmacokinetic Research

(CAPkR)(CAPkR)

Three elements of mechanism-based prediction of human PK

In vitro kinetics inIn vitro kinetics in multiple systems

ADME & DDI Predictions

Modelling & Simulation

(static and dynamic)

Simulation (PBPK)

Generic view of drug kinetics in hepatocytes:Various processes defining drugVarious processes defining drug

intracellular concentrationIntracellular binding & trafficking

Transporters Efffux

DMedia

Challenges• To describe all processes• To understand interplay & hence holistically

Intracellular unbound concD D

Mediamodel

Passive diffusion

M

Clearance by microsomal/cytosolic enzymes

Extending Classic Hepatic Clearance Models: Use of CL to delineate transporters &Use of CLint,app to delineate transporters &

enzymes and their ‘Interplay’

Prediction (static) equations well established:ll ti d li d le.g. well-stirred liver model

inth bQ fu CLCL

inth bCL

Q fu CL

Extended with use of Clint app to encompass hepatocellular sequential processes int,app p p q p(Interplay model) based on Sugiyama and Pang.

int, int,active passCL CL

CL CL int, int,

int, int, int,app met

met pass effCL CL

CL CL CL

CLint app – Interplay of transporters andCLint,app Interplay of transporters and enzymes

High passi e permeabilit High passive permeability reduces to CLint,met

Low passive permeability (with minimal effux) reduces to CLint,active

Various intermediate cases. The second term collective –Kpu (partition coefficient for unbound drug)

In vitro tools for assessment of hepatic uptake

• Hepatocytes:• Hepatocytes: Suspension culture - direct cell uptake (oil separation) Plated cells (also sandwich configuration) Si l i i f ll i f k & b li Single time points or full time course of uptake & metabolism

• Comparative scaled activity in hepatocytes relative to i ( b ll l ti )microsomes (subcellular preparation)

• Sometimes rat better option than human Higher activity and less confounding issues surrounding

preparation and storage Minimal inter-individual variation Minimal inter-individual variation Potential extrapolation to human

• CL terms main metric, and for inhibition DDIs Ki, i

where CLi = CLcontrol / 1+Ki

Characterisation of extent of hepatic uptakeWhat are we measuring with Kpu?

CL CL

• Kpu = Cell to medium (plasma) unbound concentration ratio

int, int,

int,

uptake passiveu

passive

CL CLKp

CL

[True Kpu - at steady state when no metabolism or efflux]

int,int, CLCLKp uptakepass

u

[Apparent Kpu]

int,int,int, CLCLCLp

meteffluxpassu

• Contrasts with Kptotal (ratio of total concentrations)which reflects both uptake and intracellular binding

K f KKpu = fucell · Kptotal

Used together estimates intracellular drug concentration

Comparison of microsomes and hepatocytes E id f h ti t k ff tiEvidence for hepatic uptake affecting

CL and DDI prediction

If active uptake process occurring, substrate or inhibitor may show higher ‘affinity’ in hepatocytes compared tomay show higher affinity in hepatocytes compared to microsomes –

i e lower K or Ki asi.e. lower Km or Ki as [S]u,plasma << [S]u,liver or [I]u,plasma << [I]u,liver

,,

,i microsomep ui hepatocyte

KK K ,

, int,

p y

m microsomemicrosome CLK hepatocyte , nt,, int,

m cr mmicrosomem hepatocyte hepatocyteK CL

hepatocytemicrosome

Impact of hepatic intracellular binding?: Ki Microsomes vs. Hepatocytes

(n= 7 inhibitors, n=21 pathways)(µ

M)

10

100 Inhibitor Cell-to-Media Ratio

(Kptotal)

( , p y )at

ocyt

es

1

MCZFXTKCZ

600020101200

K i H

epa

0.1

KCZFVXQUIOMP

120057714316

Ki Microsomes (µM)0.01 0.1 1 10 100

0.01OMPFCZ

164.2

Good agreement between Kivalues in both systems (both corrected for non specific binding)K i t l 1

Miconazole FluconazoleKetoconazole Quinine

Fl Fl Kpu approximately 1Fluoxetine FluvoxamineOmeprazole SaquinavirNelfinavir Ritonavir Brown et al, DMD 2007

Lack of impact of hepatic uptake:p p pMicrosomal & Hepatocyte Ki ratio vs. Kptotal

ocyt

e K i

3

4

/ H

epat

o

2

3os

ome

K i

1

C/M Ratio10 100 1000 10000M

icro

0

Kpt t l

Kptotal differ over 3 orders of magnitude No correlation between Ki ratio and Kptotal (n = 27)

C/M RatioKptotal

i ptotal ( )

Brown et al, DMD 2007

Kpu = 1 – importance of uptake transporters for 16 drugs in rat (Yabe et al DMD 2011)

10000i t i tt k iCL CL

1000

Pdi

ff)

int, int,

int,

uptake passiveu

passive

CL CLKp

CL

100

(CL u

ptak

e/P

10

Kpu

(

1

atin

atin

atin

atin

atin

avir

avir tan tan tan ycin

ycin ide ide dine tan

Pravas

tatRos

uvas

tatAtor

vasta

tCeri

vasta

tPita

vasta

tSaq

uinav

Ritona

vTelm

isarta

Olmes

arta

Valsart

a

Clarith

romyc

Erythro

mycRep

aglin

idNate

glinid

Fexofe

nadin

Bosen

ta

Kpu (CLuptake/Pdiff) 250-fold range (erythromycin and atorvastatin).

Covariate analysisy2.5 0.5

ff 1.5

2

ll

-0.5

0

log

P dif

1

1.5

log

fuce

l

-1.5

-1

0

0.5

-2.5

-2

Log D7.4

-2 0 2 4 6

0

Log D7.4

-2 0 2 4 6

Useful for cross-species and cross-systems extrapolationBut no statistical relationship between:But no statistical relationship between:Log D and any active uptake parameters

Interplay examples - Kpu = 1 :actively transported drugs

(n= 7 inhibitors, n=21 pathways)(µ

M)

10

100 Inhibitor Cell-to-Media Ratio(Kp)

( p y )at

ocyt

es

1

MCZFXTKCZ

600020101200

Saquinavir Enoxacin

K i H

epa

0.1

KCZFVXQUIOMP

120057714316

Ki Microsomes (µM)0.01 0.1 1 10 100

0.01OMPFCZ

164.2

Good agreement between Kivalues in both systems (except the higher affinity inhibitors)K i t l 1

Miconazole FluconazoleKetoconazole Quinine

Fl Fl Kpu approximately 1Fluoxetine FluvoxamineOmeprazole SaquinavirNelfinavir Ritonavir Brown et al, DMD 2007

Example 1:Enoxacin inhibition of ptheophylline oxidation

S b t ti l DDI t d i h d tSubstantial DDI reported in humans and rats

Microsomes Hepatocytes

activ

ity

80

100 THEO 0.5KM

THEO KM

THEO 2KM activ

ity

80

100

% o

f co

ntro

l

40

60M

% o

f co

ntro

l

20

40

60

No significant inhibition Competitive inhibition

1 10 100 1000

%

0

20

1 10 100 1000

%

0

20No significant inhibitionKi >1000 µM

pKi = 120 65µM (n=3)

[Enoxacin] (µM) [Enoxacin] (µM)

Significantly more potent (>20) inhibition in cells vs. microsomesi k f iActive uptake of enoxacin

Similar scenario observed with erythromycinBrown et al, 2010

Example 2: Inhibition of CYP3A byExample 2: Inhibition of CYP3A by HIV protease inhibitors –nelfinavir and saquinavirnelfinavir and saquinavir

Well documented examples of actively transported drugs with substantial DDIstransported drugs with substantial DDIs

Hepatocyte-microsomal difference in Ki to be expectedexpected

Similar scenario to enoxacin and erythromycin?

Saquinavir metabolism and uptake

5050

in ratr)

40

50r)

40

50

Permeability 50ml/min/g liver

n/g

liver

30MetabolismmicrosomesH t tn/

g liv

er

30 Clint >350 ml/min/g liver

nmol

/mi

20

Hepatocytes

nmol

/mi

20UptakeClint 50 ml/min/g liver

v (

10

v (

10

phepatocytes

Clint 50 ml/min/g liver

0 1 2 3 4

0

0 1 2 3 4

0

[SQV] M[SQV] M

Uptake is rate limiting and defines CL

Hepatic uptake and microsomal:hepatocyte Km & Ki ratios

for saquinavir and nelfinavirqMicrosomal:hepatocellular ratio

DDrug (Kptotal)

Km Ki Kpu

Saquinavir (306) 0.16 0.34 6.8

Nelfinavir (3350) 0.03 0.04 5.7

Opposite effect to enoxacin & erythromycin cases

Parker et al, DMD 2008

Framework for interplay of metabolism & t t Ktransporters on Kpu

(Intermediate permeability 0.1 ml/min/M cells)

Enoxacin,erythromycin

Saquinavir,q ,nelfinavir

• No efflux or tissue binding

Example 3: Repaglinide-Gemfibrozil DDIInhibition of both hepatic uptake and metabolismInhibition of both hepatic uptake and metabolism

Pl LiPlasma Liver

RepaglinideRepaglinide

UGTPassive

MetabolitesX XCYP2C8

UGTPassive

OATP1B1CYP3A4

X - inhibition by GFZ and GFZ-glucuronideX inhibition by GFZ and GFZ-glucuronideDDI at both transporter and P450 level - sequential effect

Repaglinide uptake in human hepatocytes

in)

4000 )

100s/

mg p

rote

in/m

i 4000

tota

l upt

ake

(%)

60

80

ke R

ate

(pmo

les

2000

Cont

ribu

tion

to

t

20

40

Repaglinide Concentration (µM)0 20 40 60 80 100

Upt

ak

0

Repaglinide concentration (µM)0.1 1 10 100 1000

C

0

-- Total uptake -- Passive component (4°C)

--- Active component (simulated data)CLuptake 5-fold greater than the passive component

Km = 14.1 µM at therapeutic concentrations

IC50 4 3 and 7 4 µM for GFZ and GFZ-glucuronide respectivelyIC50 4.3 and 7.4 µM for GFZ and GFZ-glucuronide, respectively

Comparison of contribution (based on Clints) f th i it tof pathways across in vitro systems

50

60

70

butio

n

A

50

60

70

utio

n

B

50

60

70

butio

n

CHepatocytes S9 HLM

10

20

30

40

% C

ontri

b

10

20

30

40

% C

ontri

bu10

20

30

40

% C

ontri

b

CYP3A4 CYP2C8 UGT

0

10

M1 M2 M4 Gluc0

10

M1 M2 M4 Gluc0

10

M1 M2 M4 Gluc

● CYP3A4 ● CYP2C8 ● UGT

• M2 contributed similar % in S9 and hepatocytes (66% in vivo), needs aldehyde y ( ) ydehydrogenase to drive pathway.

• 5% contribution of M2 observed in HLM increased importance of M1 and M4

• Similar contribution of CYP3A4 and CYP2C8 in S9 and hepatocytes

Säll et al, DMD 2012

Inhibition of CYP2C8 byInhibition of CYP2C8 by Gemfibrozil in vitro

Using repaglinide depletion and rosiglitazone para-hydroxylationhydroxylation

Competitive inhibition (red bars) 25

406080

(red bars) -Microsomal/hepatocyte ratios 7 and 3 IC

50 (µ

M)

15

20

Time dependant inhibition, with pre-incubation (blue bars) -Mi l/h t t ti

0

5

10

Microsomal/hepatocyte ratio 24 and 44 [greater accumulation of glucuronide?]

Microsomes Hepatocytes

Prediction of Repaglinide-Gemfibrozil DDI

35

40fib

rozil A

Obs Predicted from interplay model

25

30

prese

nce o

f gem

fcu

ronide

10

15

20

ide A

UC in

the p

and i

ts glu

c

0

5

Repa

glini

Summary y• Use of rat hepatocytes provides a comprehensive

package of clearance mechanisms for PBPK modelling to delineate intracellular events.

• Kp parameters particularly useful. Allows resolution of cellular binding and active transportresolution of cellular binding and active transport processes.

• Unbound intracellular drug concentration needed – consequences of transporters.q p

• Certain parameters are translatable to humans (P fu )(Pdiff, fucell)

AcknowledgementsAleksandra Galetin, David Hallifax

Jane Alder, Hayley Brown, Carina Cantrill, Carolina Säll, , ,Alison Wilby, Yoshiyuki Yabe

Member companies of Centre for Applied Ph ki ti R h (CAPkR) C tiPharmacokinetic Research (CAPkR) Consortium

http://www.capkr.manchester.ac.uk

Repaglinide metabolism in human Shepatocytes, S9 and microsomes

M1

M2

UGT1A1/1A3CYP2C8/3A4

Repaglinide Repaglinide - glucuronide

M4

• Previous in vitro study identified M1 and M4 as major metabolitesM0-OH

M5

• M2 reported as major in vivo metabolite (66% of dose excreted in faeces and urine)

• No in vitro data available to confirm predominant role of CYP2C8 in repaglinide metabolism