Navigating Transporter Sciences in Pharmacokinetics...

Medicine Design

Navigating Transporter Sciences in

Pharmacokinetics Characterization using

Extended Clearance Classification System

(ECCS) Manthena Varma Med Design, Pfizer, Groton CT

This document provides an outline of a presentation and is incomplete without the accompanying oral commentary and discussion. Conclusions and/ or potential strategies contained herein are NOT necessarily endorsed by Pfizer management. Any implied strategy herein would be subject to management, regulatory and legal review and approval before implementation.

SSX India-2018

Oct 11th 2018

Medicine Design 2

MATE

Transporters and Enzymes – Drug Clearance

Major proteins

- Uptake transporters

- Efflux transporters

- CYPs

- UGTs

- Other enzymes

Medicine Design 3

Permeability cut off =

• 5 X 10-6 cm/sec

Ionization:

• Acids/Zwits vs Bases/Neutrals

Molecular Weight cut off:

• 400 [Class 1/3]

Extended Clearance Classification System [ECCS] Clearance mechanism (rate-determining step)

• Varma et al., Pharm Res. 2015, 3785-3802 • El-Kattan and Varma. Drug Metab Dispos. 2018, 729-739. • Varma et al., Adv Drug Deliv Rev. 2017 Jul 1;116:92-99. • Varma et al., Clin Pharmacol Ther. 2017, 33-36 • El-Kattan et al., Pharm Res. 2016, 3021-3030. • Varma and El-Kattan. J Clin Pharmacol. 2016, S99-S109.

Introduction

Medicine Design

ECCS Class Intestinal Transporters Hepatic uptake transporters

Renal secretory transporters

IA P-gp, BCRP (OAT2)

1B P-gp, BCRP OATP1B1, OATP1B3

2 P-gp, BCRP

3A P-gp, BCRP (PEPT1) OAT1, OAT3

3B P-gp, BCRP (PEPT1, OATP2B1) OATP1B1, OATP1B3 OAT1, OAT3

4 P-gp, BCRP (OATP2B1) OAT1, OAT3, OCT2, MATEs

Lumen

BCRP

Enterocytes

- SLC transporters

- ABC transporters

Blo

od

Inte

stin

e

Basolateral

Apical

P-gp

OAT1

OAT3

OCT2

OATP1B3

OATP1B1

Lum

en

Kid

ney

Urine

Liv

er

Hepatocyte

P-gp

BCRP

Bile

CYPs/others

CYPs/others

R

OH

R

Bases/NeutralsAcids/Zwitterions

Hig

h P

erm

eab

leL

ow

Perm

eab

le

Class 1

Class 3

Class 2

Class 4

Metabolism

Renal clearance

Class 1A Class 1B

Metabolism Hepatic uptake

MW ≤400 MW >400

Class 3A Class 3B

MW ≤400 MW >400

Renal

clearance

Hepatic uptake

(or) Renal

clearance

R

OH

R

R

OH

R

ECCS Class and Drug Transporters

Varma et al. CPT 2017, 33-36.

MATEs

Medicine Design

Transporter Victim DDIs with probe inhibitors Clinical probe inhibitors

Varma et al. CPT 2017, 33. El-Kattan & Varma, DMD, 2018, 729.

0.5

5

AU

C r

atio (

+ c

yclo

sporine)

B) DDIs with cyclosporine, an OATP1B1/1B3 and P-gp/BCRP probe inhibitor

1x1.25x

2x

5x

1x1.25x

2x

5x

ECCS 1A 1B 2 3A 3B 4

20 -

1 -

20 -

1 -

N= 2 4 7 1 6 3


N= 2 7 14 1 10 9

Lumen

BCRP

Enterocytes Blo

od

Inte

stin

e

Basolateral

Apical

P-gp

OATP1B3

OATP1B1

Liv

er

Hepatocyte

P-gp

BCRP

Bile

CYPs/others

CYPs/others

Lumen

BCRP

Enterocytes Blo

od

Inte

stin

e

Basolateral

Apical

P-gp

OATP1B3

OATP1B1

Liv

er

Hepatocyte

P-gp

BCRP

Bile

CYPs/others

CYPs/others

A) DDIs with rifampicin, an OATP1B1/1B3 probe inhibitor

R

OH

R


Hig

h P

erm

eab

leL

ow

Perm

eab

le

Class 1

Class 3

Class 2

Class 4

Metabolism

Renal clearance

Class 1A Class 1B


MW ≤400 MW >400

Class 3A Class 3B

MW ≤400 MW >400

Renal

clearance

Hepatic uptake

(or) Renal

clearance

R

OH

R

R

OH

R

Medicine Design

Transporter Victim DDIs with probe inhibitors Clinical probe inhibitors

B) DDIs with cimetidine, an OCT2/MATEs probe inhibitor

A) DDIs with porbenecid, an OAT1/3 probe inhibitor

0.5

1

1.5

2

2.5

3

AU

C r

atio

(+

pro

be

ne

cid

)


N= 0 0 13 16 9 6

1x

1.25x

2x

0.5

1

1.5

2

2.5

3

AU

C r

atio

(+

cim

etid

ine)


1x

1.25x

2x

N= 0 0 3 6 0 16

Blood

MATE2-K

OAT1

OCT2

OAT3

Passive

diffusion

Luminal

MATE1

Nep

hron

Blood

MATE2-K

OAT1

OCT2

OAT3

Passive

diffusion

Luminal

MATE1

Nep

hron

0

Varma et al. CPT 2017, 33. El-Kattan & Varma, DMD, 2018, 729.

ECCS and renal transporters


Lo

w P

erm

eab

le

Class 3

Class 3A

OAT1

OAT2

OAT3

OATPs

OAT3

Class 3B

MW ≤400 MW >400

Class 4

OAT2

OAT3

OCT2

MATEs

Medicine Design

Compound Uptake

ESF Source

valsartan 5 Poirier A, et al, (2009) JPKPD 36

fexofenadine 10 Poirier A, et al, (2009) Mol Pharm 6

pravastatin 3.7 Watanabe T, et al, (2009) JPET 328

pravastatin 31 Varma MV, et al, (2012) Pharm Res 29

repaglinide 12 Gertz M, et al, (2013) Pharm Res 30

repaglinide 17 Varma MV, et al, (2013) Pharm Res 30

glyburide 2 Varma MV, et al, (2014) AAPS J 16

rosuvastatin - Jamei M, et al. (2014) Clin Pk 73

cerivastatin 30 Varma MV, et al, (2015) DMD 1108

Montelukast 22 Varma MV, et al, (2016) CPT

7

Jones HM et al. DMD, 2012, 1007.

• SF are estimated by fitting clinical

data

• Can we use such ESF to predict

PK of other compounds?

No SF

with SFs

PK profile prediction

In vitro – in vivo translation (PBPK)

1 or 5-C liver

“Middle-out” PBPK reports

Medicine Design

In vitro – in vivo translation (intrinsic hepatic CL)

8

)CLCL(CL

)CLCL().CLCL . (SFCL

bileint,CYPint,passive

bileint,CYPint,

passiveactiveactivehint,

Varma et al. JPET, 2014, 214.

Kimoto et al. JPS, 2017

CLuptake, CLpssive, CLbile

CLmet

‘Bottom-up’

Empirical

SF of 10.6

‘Middle-out’

Atorvastatin Pravastatin

Bosantan Rosuvastatin Cerivastatin Valsartan Fluvastatin Pitavastatin Repaglinide Glyburide

ECCS 1B ECCS 3B

IVIVE

No uptake

‘no consideration

to uptake’

Medicine Design 9

In vitro – In vivo Extrapolation for

Metabolic CL compds

Heps HLM SF ~4-5

needed to

recover

CLint.

Skew in

IVIVE

Medicine Design

Challenging Class 1B compds: Montelukast case

1 1 0 1 0 0

0

5 0

1 0 0

1 5 0

T im e (m in )

Ce

ll a

cc

um

ula

tio

n

(pm

ol/

mg

)

C on

tro

l (3 7

C )4

C

+ Rif

a mp

icin

(3

M)

+ Rif

a mp

icin

(1 0

M)

+ C y c losp

or i

ne A

(1 0

M)

+ Rif

a my c in

SV

(2 0

M)

+ Rif

a my c in

SV

(1 m

M)

+ Ge m

fib

roz il

(10 0

M)

+ Ge m

-glu

(1 0 0

M)

+ MK

5 7 1 (5 0

M)

0

5 0

1 0 0

1 5 0

2 0 0

% o

f c

on

tro

l U

pta

ke

CL

int

(0.5

-5m

)

ECCS 1B 1

10

100

1000

0 3 6 9 12 15 18 21 24

Mo

nte

luka

st p

lasm

a co

nc.

(n

g/m

L)

Time (h)

0.01

0.1

1

10

0 3 6 9 12 15 18 21 24

Rif

amp

icin

fre

e p

lasm

a co

nc.

(µ

M)

Time (h)

1

10

100

1000

10000

0 3 6 9 12 15 18 21 24

Mo

nte

luka

st p

lasm

a co

nc.

(n

g/m

L)

Time (h)

1

10

100

1000

10000

100000

0 3 6 9 12 15 18 21 24

Pit

avas

tati

n p

lasm

a co

nc.

(n

g/m

L)

Time (h)

0.1

1

10

0 3 6 9 12 15 18 21 24

Rif

amp

icin

fre

e p

lasm

a co

nc.

(µ

M)

Time (h)

0

0.5

1

1.5

2

Control + Rifampicin

Mo

nte

luka

st C

L (m

L/m

in/k

g)

0

5

10

15

20

25


Pit

avas

tati

n C

L (m

L/m

in/k

g)

Interaction with rifampicin in Cynomolgus monkeys

(D) (E) (F)

Interaction with rifampicin in rats

(A) (B) (C)

1

10

100

1000

0 3 6 9 12 15 18 21 24

Pit

avas

tati

n p

lasm

a co

nc.

(n

g/m

L)

Time (h)

0

5

10

15

20

25

30


Mo

nte

luka

st C

L (m

L/m

in/k

g)

0

5

10

15

20


Pit

avas

tati

n C

L (m

L/m

in/k

g)

*P=0.011 *P<0.001

*P=0.012 *P=0.005

Weak in vitro activity CL reduced with Rifampicin in

rat and monkey

Montelukast

Varma et al., CPT 2017, 406-415.

Case example

Medicine Design

Montelukast clinical DDIs - PBPK modeling

1

1

Montelukast DDIs

Hepatocyte

Bile

Blood

Other

organs

CYP3A4

Passive

Extracellular space

CYP2C8 OATP1B1

Gem Gem-Glu Clari

ECCS 1B

Gem Gem-Glu

Varma et al., CPT 2017, 406-415.

Case example

Medicine Design

ECCS Class Intestinal Transporters Hepatic uptake transporters

Renal secretory transporters

IA P-gp, BCRP (OAT2)

1B P-gp, BCRP OATP1B1, OATP1B3

2 P-gp, BCRP

3A P-gp, BCRP (PEPT1) OAT1, OAT3

3B P-gp, BCRP (PEPT1, OATP2B1) OATP1B1, OATP1B3 OAT1, OAT3

4 P-gp, BCRP (OATP2B1) OAT1, OAT3, OCT2, MATEs

Lumen

BCRP

Enterocytes

- SLC transporters

- ABC transporters

Blo

od

Inte

stin

e

Basolateral

Apical

P-gp

OAT1

OAT3

OCT2

OATP1B3

OATP1B1

Lum

en

Kid

ney

Urine

Liv

er

Hepatocyte

P-gp

BCRP

Bile

CYPs/others

CYPs/others

R

OH

R


Hig

h P

erm

eab

leL

ow

Perm

eab

le

Class 1

Class 3

Class 2

Class 4

Metabolism

Renal clearance

Class 1A Class 1B


MW ≤400 MW >400

Class 3A Class 3B

MW ≤400 MW >400

Renal

clearance

Hepatic uptake

(or) Renal

clearance

R

OH

R

R

OH

R

ECCS Class and Drug Transporters

Varma et al. CPT 2017, 33-36.

MATEs

Medicine Design

0

20

40

60

80

100

120

R-w

arfa

rin

PH

H U

pta

ke

Warfarin uptake by Human Hepatocytes

Both R/S-warfarin behave like

cGMP – Known to be selective

for OAT2

OATPs inh All SLCs OAT2 inh

0

20

40

60

80

100

120

S-w

arfa

rin

PH

H U

pta

ke

0

20

40

60

80

100

120

cGM

P P

HH

Up

take

R-Warfarin S-Warfarin cGMP

0

2

4

6

8

10

12

NTC

P

OA

T2

OA

TP1B

1

OA

TP1B

3

OA

TP2B

1

OC

T1R-w

arfa

rin

Up

take

rat

io

0

1

2

3

4

5

NTC

P

OA

T2

OA

TP1B

1

OA

TP1B

3

OA

TP2B

1

OC

T1S-w

arfa

rin

Up

take

rat

io

R-Warfarin S-Warfarin

OAT2 selectivity was

confirmed using singly

transfected HEK293 cells

Case example

14

Pfizer Confidential

10

100

1000

0 24 48 72 96 120 144 168

R-w

arfa

rin

conc

. (ng

/mL)

Time (h)

10

100

1000

0 24 48 72 96 120 144 168

S-w

arfa

rin

conc

. (ng

/mL)

Time (h)

1

10

100

1000

0 50 100 150 200 250 300 350 400

S-w

arfa

rin

conc

. (ng

/mL)

Time (h)

10

100

1000

0 24 48 72 96 120 144 168

R-w

arfa

rin

conc

. (ng

/mL)

Time (h)

10

100

1000

0 24 48 72 96 120 144 168S-

war

fari

n co

nc. (

ng/m

L)

Time (h)

(A) (B)

(C) (D)

(E)

Control

+Fluconazole

Control

+Fluconazole

CYP2C9*1/*1*1/*3

*2/*3

*3/*3

0

200

400

600

800

1000

0 4 8 12

S-w

arfa

rin

conc

. (ng

/mL)

Time (h)

0

200

400

600

800

1000

0 4 8 12

R-w

arfa

rin

conc

. (ng

/mL)

Time (h)

10

100

1000

0 24 48 72 96 120 144 168

R-w

arfa

rin

conc

. (ng

/mL)

Time (h)

10

100

1000

0 24 48 72 96 120 144 168

S-w

arfa

rin

conc

. (ng

/mL)

Time (h)

CYPs only

OAT2-CYPs interplay

CYPs only

OAT2-CYPs interplay R/S-warfarin PK analysis

Fluco

Ki µM

7.92

-

2

Other organs

Hepatocyte

Bile

Blood

Extracellular space

OATP1B1/1B3/2B1

OAT2

OCT1/NTCP

R-warfarin

S-warfarin

R-warfarin

S-warfarin

CYP2C19

CYP2C9

Case example

Bi et al. Mol Pharma 2018, 1284-1295.

Medicine Design

Co

nt r o

l

10

µM

CS

A

20

µM

RI F

30

µM

Ke

t op

r of e

n

10

0µ

M K

et o

pr o

f en

30

0µ

M K

et o

pr o

f en

0. 1

µM

HB

V p

ep

t i de

1µ

M H

BV

pe

pt i d

e

50

0µ

M Q

ui n

i di n

e

1m

M R

I F S

V

0

5 0

1 0 0

1 5 0

Up

ta

ke

ra

tio

(%

of

co

nt

ro

l)

0 1 2 3 4 5

0

1

2

3

4

T i m e ( m i n )

Up

ta

ke

ra

tio

N T C P

O A T 2

O A T P 1 B 1

O A T P 1 B 3

O A T P 2 B 1

O C T 1

0 2 0 4 0 6 0 8 0

0

1 0

2 0

3 0

4 0

5 0

[ T o l b u t a m i d e , M ]

OA

T2

up

ta

ke

ra

te

(pm

ol/

min

/m

g-

pr

ot

ein

)

K m = 1 9 . 5 4 . 3 M

V m a x = 4 7 . 8 4 . 0 ( p m o l / m i n / m g - p r o t e i n )

**

*

*

*

*

Co

nt r o

l

10

µM

CS

A

20

µM

RI F

30

µM

Ke

t op

r of e

n

10

0µ

M K

et o

pr o

f en

30

0µ

M K

et o

pr o

f en

0. 1

µM

HB

V p

ep

t i de

1µ

M H

BV

pe

pt i d

e

50

0µ

M Q

ui n

i di n

e

1m

M R

I F S

V

on

ic e

0

5 0

1 0 0

1 5 0

2 0 0

Up

ta

ke

ra

te

(%

of

co

nt

ro

l)

0 1 2 3 4 5

0

5 0

1 0 0

1 5 0

2 0 0

2 5 0

T i m e ( m i n )

Up

ta

ke

(p

mo

l/m

g p

ro

te

in)

C o n t r o l ( 3 7 C )

+ R i f S V ( 1 m M )

0 2 0 4 0 6 0 8 0 1 0 0

0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

[ T o l b u t a m i d e , M ]

Up

ta

ke

ra

te

(pm

ol/

min

/m

g-

pr

ot

ein

)

K m = 3 9 . 3 6 . 6 M

V m a x = 4 2 6 . 5 3 0 ( p m o l / m i n / m g - p r o t e i n )

P a s s i v e C L = 1 . 0 1 l / m i n / m g

PHH

Time-course

Transport

kinetics

Phenotyping

HEK-OAT2 cells

MW – 270

pKa – 5.2

RRCK – 31

Tolbutamide

•Low CLmet

• IVIVE disconnect with CLmet

•CYP2C9 clinical probe

HEKs

Medicine Design

1

10

100

0 12 24 36

Tolb

utam

ide

conc

. (µg

/mL)

Time (h)

1

10

100

0 12 24 36 48

Tolb

utam

ide

conc

. (µg

/mL)

Time (h)

OAT2-CYP2C9 interplay

CYP2C9 only

OAT2-CYP2C9 interplay

CYP2C9 only

Sensitivity analysis

Green point – WT

Blue points - *1/*3,

*2/*3, *3/*3 variants

Bi et al. J Pharmacol Exp Ther. 2018, 390-398.

Case example

Tolbutamide: OAT2-CYP2C9 interplay

Hepatocyte

Bile

Blood

Extracellular space

PSactive

PSPassive

CLmet

CLbilePSbaso-efflux

fu,cell

fu,b

17

Pfizer Confidential

PHH +RifSV

HLM +UDPGA/NAD

PH

HEKs OAT2/OAT

P1B1 selectivity

R

OH

R


Hig

h P

erm

eab

leL

ow

Perm

eab

le

Class 1

Class 3

Class 2

Class 4

Metabolism

Renal clearance

Class 1A Class 1B


MW ≤400 MW >400

Class 3A Class 3B

MW ≤400 MW >400

Renal

clearance

Hepatic uptake

(or) Renal

clearance

R

OH

R

R

OH

R

OAT2 Substrate activity

Uptake-determined CL CL prediction for

low MW, high

permeability A/Z

(ECCS 1A)

PSactive

PSpd

CLmet

Metabolism-determined CL Extended CL model

(Transporter-Enzyme interplay)

PSactive

PSpd

CLmet

0.01

0.1

1

10

0.01 0.1 1 10

Pred

icte

d C

L

Observed CL

0.01

0.1

1

10

0.01 0.1 1 10Pr

edic

ted

CL

Observed CL

0.01

0.1

1

10

0.01 0.1 1 10

Pred

icte

d C

L

Observed CL

ECCS (n=36)

(n=25)

(n=25) (n=19)

(n=19)

Approach

18

Pfizer Confidential

Data set ECCS 1A drugs - List of drugs

17.8 334 4.1 A OATP 1B1, OAT2 CYP 2C9/UGT 0.002

6.14 305 4 A OATP 1B1, OAT2 UGT 0.02

5.82 332 4.5 A OATP 1B1, OAT2 - 0.11

4.24 317 3.8 A OATP 1B1 CYP 2C9 0.011

18.5 296 4.4 A OAT2 CYP 2C9, UGT2B7 0.004

34.2 242 4.4 A OAT2 UGT2B7 0.005

16.7 323 6 A OAT2 CYP 2C9 0.05

29.3 206 4.4 A OAT2 CYP 2C9 0.012

22.12 356 4.4 A OAT2 CYP 2C9 0.012

26.9 335 3.9 A OAT2 - 0.035

18 254 4.1 A OAT2 CYP 2C9, UGT2B7 0.021

23.9 351 3.8 A OAT2 CYP 2C9/3A4 0.008

23.3 356 6.1 A OAT2 CYP 2C8 0.012

32.9 331 2.2 A OAT2 CYP 2C9, UGT2B7 0.024

31.9 137 7.9 A OAT2 - 0.515

27.3 357 6.3 Z OAT2 CYP 2C8 0.003

24.2 308 5 A OAT2 CYP 2C9 0.013

8.38 253 5.6 A OAT2 CYP 2C9 0.325

24.2 308 5 A OAT2 CYP 2C9 0.013

31.3 270 5.1 A OAT2 CYP 2C9 0.027

20.9 273 5 A OAT2 UGT 0.002

6.84 366 5.9 Z - - 0.96

22.1 230 4.3 A OAT2 UGT2B7 0.026

11.1 258 7.8 A OAT2 - 0.4

19.9 376 3.3 Z OAT2 CYP 3A4 0.16

Th alid om id e

Tiag ab in e

Tolcap on e

Clin afloxacin

Nap roxen

P ralid oxim e

Ros ig litazon e

R-W arfarin

S u lfam eth oxazole

S -W arfarin

Tolb u tam id e

In d om eth acin

Is oxicam

Ketop rofen

Meloxicam

P iog litazon e

P iroxicam

Diclofen ac

Fen op rofen

Gliclazid e

Ib u p rofen

En tacap on e

Flu ores cein

Nateg lin id e

Brom fen ac

Up ta ke

T ra n s p o rte rsMa in E n z y m e

c

P la s m a fre e

f ra c tio n

( f u , p )d

Dru g

P e rm e a b ilit

y (10- 6

c m /s )a

Mo le c u la r

we ig h tAc id ic p Ka Io n iz a tio n

0 .0 0 .5 1 .0 1 .5 2 .0

0 .0

0 .5

1 .0

1 .5

F lu o re s c e in

T im e

(m in )

To

tal

Ce

ll A

mo

un

t

(pm

ol/

mg

)

0 .0 0 .5 1 .0 1 .5 2 .0

0

1 0

2 0

3 0

4 0

5 0

M e lo x ica m

T im e

(m in )

To

tal

Ce

ll A

mo

un

t

(pm

ol/

mg

)

0 .0 0 .5 1 .0 1 .5 2 .0

0

1 0

2 0

3 0

4 0

P ra lid o x im e

T im e

(m in )

To

tal

Ce

ll A

mo

un

t

(pm

ol/

mg

)

0 .0 0 .5 1 .0 1 .5 2 .0

0

5 0

1 0 0

1 5 0

2 0 0

F e n o p ro fe n

T im e

(m in )

To

tal

Ce

ll A

mo

un

t

(pm

ol/

mg

)

0 .0 0 .5 1 .0 1 .5 2 .0

0

1 0

2 0

3 0

K e to p ro fe n

T im e

(m in )

To

tal

Ce

ll A

mo

un

t

(pm

ol/

mg

)

Emi Kimoto

Black – Control

Red – +RifSV 1mM

Blue – on Ice

Kimoto et al. JPET, 2018, inpress

Mark Niosi & Jian Lin Sumathy & Laurie

19

Pfizer Confidential

0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Pre

dic

ted

CLi

nt

(mL/

min

/kg)

Observed CLint (mL/min/kg)

Extended CL (Uptake + metabolism)

Circles - OAT2 substrates with Hep uptake in PHH Triangles - OAT2/OATP1B1 substrates with Hep uptake in PHH

Square - no Hep uptake in PHH

IVIVE OAT2-mediated uptake IVIVE to Hepatic CLint

1x 3x Bias

𝐶𝐿ℎ,𝑖𝑛𝑡 =𝐶𝐿𝑢𝑝𝑡𝑎𝑘𝑒 ∙ 𝐶𝐿𝑚𝑒𝑡

𝐶𝐿𝑝𝑎𝑠𝑠𝑖𝑣𝑒 + 𝐶𝐿𝑚𝑒𝑡

David Tess

0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Pre

dic

ted

CLi

nt

(mL/

min

/kg)


0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Pre

dic

ted

CLi

nt

(mL/

min

/kg)


Stats †

n 13 CI 90%

DI 90% (±fold) 3.91 [2.6 - 6.9]

Bias ‡ (fold) 0.9 [0.6 - 1.4]

Kimoto et al. JPET, 2018, inpress

Medicine Design

Transporter phenotype per class

Bases/Neutrals Acids/Zwitterions

Hig

h P

erm

ea

ble

Class 1

Class 1A

OAT2 OATPs

Class 1B

MW ≤400 MW >400

Lo

w P

erm

ea

ble

Class 3

Class 3A

OAT1

OAT2

OAT3

OATPs

OAT3

Class 3B

MW ≤400 MW >400

Class 2

Class 4

OAT1

OAT3

OCT2

Medicine Design

3A

4

2C

9

Re

na

l Tr

an.

OA

TP

Effl

ux

Tran

. U

GT

QSA

R

Re

nal

H

ep

atic

U

pta

ke

Me

tab

ol

Lead Identification and Optimization

Physiologically Based Pharmacokinetics (PBPK) to project human PK/target conc and DDI Liabilities

Lead Development

Invigoration of Human Based In Vitro Reagents as Driver for Accurate Human Clearance and

DDI Prediction

Varma, Lai and El-Kattan. Adv Drug Deliv Rev 2017, 92-99.

ECCS

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRw&url=http://www.pepid.com/drug-interactions/&ei=AMRKVfvrJYzFggTV-YDoBw&psig=AFQjCNE4tbXaAdr1ttY_geYUqFld05Krwg&ust=1431049593909313

Acknowledgments

Transporter Sciences Group Yi-an Bi

Emi Kimoto

Sumathy M

Sarah Lazzaro

Mark West

Chester Costales

Bo Feng

Manthena Varma

Larry Tremaine

David Rodrigues

Project leads & ADME CoE

Dennis Scott George Chang James Gosset John Litchfield Li Di Amit Kalgutkar Anthony Carlo Matt Troutman Jian Lin Mark Niosi

Theunis Goosen

Systems Modeling & Simulations group

David Tess

Rui Li

Tristan Maurer 22

ECCS team Manthena Varma

Stefanus Steyn

Charlotte Allerton

Ayman El-Kattan

Navigating Transporter Sciences in Pharmacokinetics...

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