ATP ADP + Pi

Jashvant (Jash) UnadkatMilo Gibaldi Endowed Professor

Dept. of PharmaceuticsSchool of Pharmacy

University of WashingtonSeattle, WA

jash@uw.edu 1

The Next Frontier in ADME Science: Predicting and Verifying Tissue Drug Exposure

https://sop.washington.edu/people/jashvant-unadkat/

ATP ADP + Pi

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GAPS in ADME: Drug Development Failure Rate and Reasons

Smietana et al., Nature Reviews Drug Discovery 15, 379–380 (2016) Harrison, Nature Reviews Drug Discovery 15, 817–818 (2016)

ATP ADP + Pi

One Possible Reason for Lack of Drug Efficacy & Safety

• Unable to routinely measure (or accurately predict) tissue drug conc.-time profile for drugs that are transported across tissue:blood barrier

• Transporters at the tissue:blood barrier (e.g. blood:brain barrier, BBB, liver:blood barrier)– Unbound tissue conc ≠ unbound plasma conc. i.e. asymmetry in

tissue:blood conc. – Impact differs between non-eliminating (e.g. brain) and

eliminating organ (e.g. liver)3

4Eyal et al., Clin Pharmacol Ther. 2010

Time (min)

0 10 20 30 40 50

Brain

11C-

radioa

ctivit

y / D

ose (

L-1)

0.01

↑~2-fold

Time (min)

0 10 20 30 40 50

Plasm

a 11C-

radioa

ctivit

y / D

ose (

L-1 )

0.01

0.1Plasma

Brain

- CsA + CsA

+ CsA -CsA

Asymmetry in Drug Conc. at the Human Brain:Blood Barrier: P-gpEfflux of 11C-Verapamil

11C-verapamil AUCbrain:AUCblood (20 min) - 0.42±0.04

ATP ADP + Pi

Asymmetry in Hepatic:Blood Conc. of 11C-Rosuvastatin in the Rat

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Coronal 2 min SUV images of 11C-Rosuvastatin

He et al., Mol Pharm., ‘14

BileBlood

ROS

Hepatocyte

OATPsBCRP/MRP2

-RIF +RIF

ATP ADP + Pi

Hepatic Uptake and Biliary Excretion of 11C-Rosuvastatin in the Rat

6He et al., Mol Pharm., ‘14

ATP ADP + Pi

Asymmetrical change in rosuvastatin conc. in liver and blood in the presence of rifampin

7He et al., Mol Pharm. 2014

2.3-fold increase in plasma AUC but no significant increase in liver

AUC

Rat Blood Rat Liver

% o

f Dos

e

% o

f Dos

e

Time (min)

Time (min)

OATPs

BileBlood

ROS

Hepatocyte

BCRP/MRP2

ATP ADP + Pi

Aorta

L KidneyR Kidney

Liver

Gallbladder

Aorta

L KidneyR Kidney

Liver

Gallbladder

RSV

[11C]Rosuvastatin biodistribution in a human volunteer

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ATP ADP + Pi

1 min 5 min 10 min 30 min

0

400

RSV

RSV

+ CS

A

GallBladder

GallBladder

LiverLiverLiverLiver

LiverLiverLiverLiver

Hepatic Uptake and Biliary Excretion of [11C]Rosuvastatin ± CsA

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ATP ADP + Pi

How Can we Predict/Measure Tissue Drug Conc. and Tissue:Blood Asymmetry in Humans? One could actually measure tissue drug conc:• PET imaging (MRI and other imaging modalities do not have the required

sensitivity):– Requires sophisticated equipment and radiochemistry – Costly (about $20-40K/experiment/subject)

• Therefore we need alternative methods that will allow us to predict tissue conc. of drugs in humans– Predict all clearances associated with the tissue:blood barrier– Possible using REF but not RAF approach

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OATPs

Hepatocyte

BCRP/MRP2

ATP ADP + Pi

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In vitro CLCL via transport of interest in cell line expressing the

transporter

Relative Expression Factor (REF)1. Transporter expression/g of

tissue 2. Tissue weight

In vivo CLContribution of individual

transporter in tissue uptake/efflux

REF = [T]ex vivo in organ

[T]in vitro

REF Method to Predict Tissue Drug Conc.Hypothesis: Predict tissue drug conc. by scaling in vitro CL in transporter expressing cells to in vivo using relative expression factor (REF)

ATP ADP + Pi

• https://sop.washington.edu/department-of-pharmaceutics/research/research-affiliate-program-on-transporters-uwrapt/

ATP ADP + Pi

Can the use of these Quantitative Proteomics Data Successfully Predict Transporter-

Mediated CL and Tissue Conc. of Drugs?

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• Changes due to hepatic impairment (e.g. chirrohsis)

• Renal secretory CL of drugs

• Hepatic CL and tissue conc. of drugs – rat and human

Criteria of success: within 2-fold of observed value

ATP ADP + Pi

Improved PBPK Prediction of Repaglinide Pharmacokinetics in Liver Cirrhosis Patients When the Effect of Cirrhosis on

OATP1B1 Abundance is Incorporated

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Without

0.1

1

10

100

0 1 2 3 4 5 6 7 8 9 10

Syst

emic

co

ncen

tratio

n (n

g/m

L)

Time (h)

Virtual population (10 trials and n=12 for each trial)

With

0.1

1

10

100

0 1 2 3 4 5 6 7 8 9 10

Syst

emic

co

ncen

tratio

n (n

g/m

L)

Time (h)

Wang et al., DMD, 2016

ATP ADP + Pi

Metformin renal clearance is reasonably well-predicted using OCT2 expressing

cells

Kumar et al., DMD 2018

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Observed metformin renal secretory clearance in humans: 432 (range 215-643) mL/min

0

100

200

300

400

500

600

700

Total abundance PM abundance PM abundance andPM potential

Met

form

in re

nal s

ecre

tory

cle

aran

ce

(mL/

min

)

215

643

432

ATP ADP + PiATP ADP + Pi

Renal Secretory CL by OATs: RAF vs. REF

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• 31 drugs secreted by renal OATs• RAF used tenofovir (OAT1), acyclovir and ganciclovir (OAT2), and benzylpenicillin/oseltamivir acid

(OAT3) as probe substrates • REF used quantitative proteomics data on renal OATs in human kidney cortex and transfected cells

which were also used to determine in vitro uptake CL of the drugs.

Collaboration with Manthena Varma (Pfizer)

ATP ADP + PiATP ADP + Pi

Hypothesis: Predict Transporter-Mediated In-Vivo Hepatobiliary CL and Hepatic Concentrations of Drugs

in Rats/Humans using REF

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Predict in-vivohepatobiliary CLusing REF and traditional approach

1. transporter-mediated drug CL2. transporter abundance using

quantitative proteomics3. Obtain REF

Transporter-expressing cells

Verify predictions using PET imaging

ATP ADP + Pi

REF (using HEK293 cells or PHH) better predicts Hepatic Uptake CL of metformin (as measured by PET imaging) vs. PHH

Gormsen, et al., J NuclMed 57(12): 1920-1926.

FF (Blood

radioactivity)

Liver

Cl h,s,in

Cl s, efflux

17M

GP

GL

ba

se

d I

VIV

E C

Lh

,s,i

n

A D RF E A

JE LY T W

A v e rag e

0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0In vivo CLh,s,in

Human Hepatocytes

RF

E b

as

ed

IV

IVE

CL

h,s

,in

H E K 2 9 3 ce lls

A D RF E A

JE LY T W

A v e rag e

0

2 0 0

4 0 0

6 0 0

8 0 0

1 0 0 0

T o ta l a b u n d a n d a n c e b a s e d

P M A c o rre c te d

In vivo CLh,s,in

REF approach

ATP ADP + Pi

Hepatic Uptake and Biliary Excretion of 11C-Rosuvastatin in the Rat

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Coronal 2 min SUV images of 11C-Rosuvastatin

He et al., Mol Pharm., ‘14

BileBlood

ROS

Hepatocyte

OATPsBCRP/MRP2

-RIF +RIF

ATP ADP + Pi

0

20

40

60

80

Clea

ranc

e (m

L/m

in/k

g bo

dy w

eigh

t)

Previous PET imagingstudy

SCRH not corrected forOatp expression

p<0.05

CLs,uptake CLs,efflux CLbile

Successful prediction of the hepatobiliary clearance of rosuvastatin using cell lines, sandwich-cultured rat hepatocytes and quantitative proteomics

CLs,uptake; sinusoidal uptakeCLs,efflux; sinusoidal effluxCLbile; canalicular efflux

0

2

4

6

8

10

Oat

p ex

pres

sion

(fmol

/µg

mem

bran

e pr

otei

n)

SD rat liverSCRH

p<0.05

p<0.05p<0.05

Ishida et al., DMD, 2018 19

0

20

40

60

80

100

120

CLs,

upta

ke(m

L/m

in/k

g bo

dy w

eigh

t)

ATP ADP + Pi

Rat Hepatic Rosuvastatin Conc. well Predicted

20Ishida et al., DMD 2018

0

500

1000

1500

2000

2500

3000

3500

0 3 6 9 12 15

Hepa

tic c

once

ntra

tion

(kBq

/mL)

Time (min)

Observed valuepredicted value95% CI of observed data

Can Rosuvastatin Hepatobiliary CL and Hepatic Conc. be Predicted in Humans?

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ATP ADP + PiATP ADP + Pi

Total transporter abundance in suspended (SH), plated (PH), sandwich-cultured (SCH) hepatocytes and liver tissue

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Kumar et al., DMD 2019

ATP ADP + PiATP ADP + Pi

Plasma membrane transporter abundance in suspended (SH), plated (PH), sandwich-cultured (SCH) hepatocytes cf liver tissue

Kumar et al., DMD 2019

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ATP ADP + Pi

• Predicting transporter-mediated CL & tissue concentrations and therefore efficacy and toxicity of a drug is the next frontier in ADME research

• The hepatic ECL model clarifies when transporters will or will not affect the systemic and tissue PK of a drug

• Tissue conc. measurement is possible using PET. However, this method cannot be routinely applied

• IVIVE using transfected cells and quantitative transporter proteomics is a promising technique to predict tissue drug conc

• These predictions should be validated using PET imaging probes that interrogate multiple drug transporters

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Summary

ATP ADP + Pi

Bhagwat Prasad Anand Deo25

YuYang Jiake He

Major Contributors

Sarah Billington

Li WangGabriela Patilea-Vrana

Kazuya IshidaVineet Kumar

ATP ADP + Pi

Other CollaboratorsDept. of Radiology: Jeanne Link, David Mankoff, Todd Richards, Janet Eary, Satoshi Minoshima, Ken Maravilla, Mark Muzi, Steve Shoner, Shirely Rene, David Lewis, Jean Lee and the PET suite teamDept. of Medicine: Ann Collier and her team; Scott Lee and his team Dept. of Anesthesiology: Karen Domino, Matthew PenningtonDept. of Pharmaceutics: Bhagwat Prasad, Edward Kelly, Carol Collins, Joanne Wang Kidney Research Institute: Jonathan HimmelfarbUniv. of Greifswald: Stefan Oswald and teamChildren’s Mercy Hospitals: Steven Leeder and teamAarhus University Hospital, Aarhus, Denmark, Dr. Gormsen

Acknowledgement: NIH P01DA032507, MH63641, P50 HD44404, RR 00166, HD47892, AG031485, RC1NS068904, BioIVT, Solvo Biotech., UWRAPT funded by Genentech, Merck, Biogen, Gilead, BMS, Takeda, Pfizer, Amgen

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