incorporating in vitro information into models which integrate...
TRANSCRIPT
Incorporating In Vitro Information into Models which Integrate Intestinal and Renal
Drug Transport
Amin Rostami-Hodjegan, PharmD, PhD, FCP, FJSSX, FAAPS
Professor of Systems Pharmacology University of Manchester, Manchester, UK
& Vice President R&D
Simcyp , Sheffield, UK
Blood Enterocyte
Lumen
PepT1,
PepT2,
OATP1A2,
OATP2B1,
OCT3,
OCTN1,
OCTN2, IBAT,
CNT1, CNT2,
MCT1, MCT4,
MCT5
MDR1 (P-gp)
MRP
BCRP
Intestine
The Blood-CSF Barrier
Cerebrospinal fluid (CSF)
apical
basolateral
Endothelial cells
Astrocyte feet
Blood
Brain parenchyma
The Blood-Brain Barrier
luminal
abluminal
MRP4 MRP4 BCRP
BCRP
MDR1 (P-gp)
MDR1
(P-gp) OATP1A2
OATP2B1
Choroid epithelium
Blood
Hepatocyte
OATP1B
1
OATP1B
3
OCT1
MDR1 (P-gp)
MRP2
BCRP
MRP
3
Liver
Basolateral
(blood)
Apical
(urine) Kidney cell
MRP1
MRP3
MRP6
OAT1
OAT2
OAT3
OCT2 MATE1
MATE2-K
OCTN1
OCTN2
OAT4
URAT1
OATP1A2
MRP2
MRP4
MDR1 (P-gp)
BCRP
Kidney
Drug Transporters: Local vs Systemic PK
Scaling from In Vitro Assays
In vitro data
Jmax/Km or
CLuint T
SF 1:
PTC In vitro
CLuint, T
CLuint, T
per
g Kidney
SF 2: SF 3:
CLuint, T
per Kidney
REF/RAFPTC PTCPGK Kidney Weight
Kidney
Jmax/Km or
CLuint T
SF 1:
HHEP In vitro
CLuint, T
CLuint, T
per
g Liver
SF 2: SF 3:
CLuint, T
per Liver
REF/RAFHHEP HPGL Liver Weight
Liver
In vitro data
Jmax/Km or
CLuint T
SF 1:
H-BMv In vitro
CLuint, T
CLuint, T
per
g Brain
SF 2: SF 3:
CLuint, T
per Brain
@ BBB
REF/RAFH-BMv H-BMvPGB Brain Weight
Brain
In vitro data
Caco-2, MDCK- II,
LLC-PK1 etc.
Jmax/Km or
CLuint T
SF 1:
CLuint, T
In Jejunum I
Intestine
REF/RAFJejunum I
Replacement / Additional Organ
Jmax/Km or
CLuint T
CLu, T
per whole
organ
User needs to scale to whole organ!
SF: Scaling Factor
Scaling via the
Permeability and
Surface area
product
Du
od
en
um
Jeju
nu
m I
Jeju
nu
m I
I
Ileu
m I
Ile
um
II
Ileu
m I
II
Ileu
m I
V
Co
lon
Segregated Blood Flows
Gastric
Emptying
Luminal
Transit
The Advanced Dissolution, Absorption & Metabolism - ADAM
Relative P-gp Distribution
CYP3A Distribution
Biopharmaceutics & Drug Disposition 34: 2–28 (2013)
Interplaying Factors: Transporters
0.0
0.5
1.0
0.001 0.1 10 1000
fa (
AD
AM
) (S
ub
)
0.0
0.5
1.0
0.001 0.1 10 1000
REF (intestinal P-gp)
0.0
0.5
1.0
0.001 0.1 10 1000
As REF ↑ for a P-gp (apical efflux) substrate fa ↓…
0.0
0.5
1.0
0.01 0.1 1 10 100 1000 10000 100000
fa (
AD
AM
) (S
ub
)
Dose [mg]
REF = 0.001
0.0
0.5
1.0
0.01 1 100 10000
fa (
AD
AM
) (S
ub
)
Dose [mg]
REF = 100
…effect is less marked as dose ↑
0.002 mg 400 mg 2000 mg
Effect of REF and Dose on Fa
nentgut
nTranappCfuKmA
JP
,
,,
max
In vitro apparent active
permeability per gut segment.
Transfer Papp,Tran,n to in vivo effective active
permeability using the selected prediction model.
nentgutnTran CfuCL ,,
nTraneffP ,,
Scale up Peff,Tran,n to transport clearance in the
gut segment. nTrannTrannnTraneff REFFSP ,,,,
Amount of drug pumped backed into lumen
(efflux) per gut segment.
A = area of filter; Sn = Surface area of gut segment; FTrans,n = relative abundance of transporter in gut segment.
In calculations for uptake transporters Clumen is used.
In Vitro-In Vivo Extrapolation of Transporters PK
R² = 0.0266
0
1
2
3
0 1 2 3 4 5
Hepatic MRP2 protein
expression [rel. Units/mg
protein]
Intestinal MRP2 protein expression [rel. Units/mg protein]
Data from: H. Gläser, thesis 2003
No correlation between the intestinal and hepatic content of MRP2
Therefore they are independently assigned within Simcyp
Co-variation of transporters and metabolising enzymes currently under investigation
Correlations? (e.g. MRP2 in Gut vs. Liver)
Quantitative Proteomic in Manchester - QconCAT
Schematic of the QconCAT method.
Russell et al 2013, J Proteomics, Revised version under Review
Quantitative Proteomic in Manchester - QconCAT
Cy
toc
hro
me
P4
50
en
zy
me
ab
un
da
nc
e (
pm
ol/
mg
)
CY
P1
A2
CY
P2
A6
CY
P2
B6
CY
P2
C8
CY
P2
C9
CY
P2
C1
8
CY
P2
D6
CY
P2
J2
CY
P3
A4
CY
P3
A5
CY
P3
A7
CY
P3
A4
3
CY
P4
F2
0
5 0
1 0 0
1 5 0
2 0 0
B )
Achour et al, in Preparation
CYP Abundance and Interindividual Variability
UG
T e
nz
ym
e a
bu
nd
an
ce
(p
mo
l/m
g)
UG
T1
A1
UG
T1
A3
UG
T1
A4
UG
T1
A6
UG
T1
A9
UG
T2
B4
UG
T2
B7
UG
T2
B1
5
0
1 0 0
2 0 0
3 0 0
B )
Quantitative Proteomic in Manchester - QconCAT
Achour et al, in Preparation
UGT Abundance and Interindividual Variability
CY
P
1A
2
CY
P
2A
6
CY
P
2B
6
CY
P
2C
8
CY
P
2C
9
CY
P
2C
18
CY
P
2D
6
CY
P
2J
2
CY
P
3A
4
CY
P
3A
5
CY
P
3A
7
CY
P
3A
43
CY
P
4F
2
UG
T
1A
1
UG
T
1A
3
UG
T
1A
4
UG
T
1A
6
UG
T
1A
9
UG
T
2B
4
UG
T
2B
7
UG
T
2B
15
CYP1A2 1 0.44 NS NS NS 0.45 NS 0.58 NS NS NS 0.63 0.47 0.42 0.36 0.48 NS 0.45 0.67 0.70 0.57
CYP2A6 1 0.59 0.56 0.68 NS NS NS 0.50 NS NS 0.41 0.35 0.43 NS 0.51 0.38 0.36 0.45 0.59 0.53
CYP2B6 1 0.56 NS NS NS NS 0.63 NS NS NS NS 0.35 NS 0.48 NS NS NS 0.36 0.49
CYP2C8 1 0.56 NS 0.44 NS 0.62 NS NS NS NS NS 0.42 0.38 NS NS NS NS NS
CYP2C9 1 0.57 NS NS NS NS NS 0.47 NS 0.43 0.42 0.70 0.48 0.45 0.64 0.66 0.61
CYP2C18 1 NS 0.39 NS NS -0.43 0.61 0.39 NS NS NS NS NS NS 0.43 NS
CYP2D6 1 NS 0.37 NS 0.58 NS NS NS NS NS NS NS NS NS NS
CYP2J2 1 NS NS NS 0.42 NS NS NS 0.48 NS NS 0.45 NS NS
CYP3A4 1 0.36* 0.50 NS NS 0.51 NS 0.48 NS NS 0.45 NS NS
CYP3A5 1 0.39 NS 0.37 NS NS 0.43 0.62 0.50 0.43 NS NS
CYP3A7 1 NS NS NS NS NS NS NS NS NS NS
CYP3A43 1 NS NS 0.46 0.51 NS NS 0.51 0.39 NS
CYP4F2 1 0.42 NS NS 0.49 0.45 0.38 0.61 0.46
UGT1A1 1 NS 0.41 0.42 NS 0.65 0.50 0.55
UGT1A3 1 0.57 0.56 0.55 0.46 NS NS
UGT1A4 1 0.75 0.75 0.82 0.55 0.61
UGT1A6 1 0.82 0.72 0.50 0.61
UGT1A9 1 0.73 0.61 0.69
UGT2B4 1 0.65 0.71
UGT2B7 1 0.91
UGT2B15 1
Error! No text of specified style in document.
Inter-correlations: A Realistic Virtual Patient
Time-variant, Compartmental Luminal Fluid Volumes
Fasted State
250 mL fluid taken with dose:
Average healthy individual
1
10
100
1000
0.01 0.1 1 10 100
Lum
inal
Flu
id V
olu
me
s (m
L)
Time (hours)
Fasted Gut Lumen Fluid Volumes (250 mL taken with dose)
Whole Gut
Stomach
Duodenum
SI Total
Colon
Ileum I - IV
I
IIJejunum
Luminal Fluid
Volumes (mL)
),(
),(),(
tsegmentVolumeFluid
tsegmentmassDissolvedtsegmentCbulk
Inter-individual
variability not shown
Time (hours)
Substrate and Inhibitor with ADAM - DDIs
Segregated Blood
Flows
Luminal Transit
Du
od
enu
m
Jeju
nu
m I
Jeju
nu
m II
Ileu
m I
Ileu
m II
Ileu
m II
I
Ileu
m IV
Co
lon
Segregated Blood
Flows
Luminal Transit
Du
od
enu
m
Jeju
nu
m I
Jeju
nu
m II
Ileu
m I
Ileu
m II
Ileu
m II
I
Ileu
m IV
Co
lon
Substrate Main inhibitor
Note an inhibitor could be an excipient etc
CYPs/ Efflux/ Influx Transporters
Kidney: Inter-Species Differences and Transporters
(Shitara et al., 2006)
Rat
CLrenal
[mL/min/kg]
Famotidine alone 42 ± 9
with probenecid 46 ± 10
Human
CLrenal
[mL/min/kg]
CLsecretion
[mL/min/kg]
297 ± 19 196 ± 21
107 ± 5 22 ± 4
probenecid
OCTNs
MRP2,4
OAT4 Decrease in the
renal clearance
OAT1
OAT3
OCT2 Increase in the plasma
concentration
famotidine
Human
Octn
Mrp2,4
Oat-K1
Oat1
Oct1
probenecid
famotidine No change
Urine Blood
Oat-K2
Oct2 Oatp1
Oat3
Rat
Renal proximal tubule cell
Model Structure: Mechanistic Kidney (Mech KiM)
Glomerulus
Proximal
tubule
Henle’s
loop
Distal
tubule
Collecting
duct
Bladder Blood Urine
Urinal tubule Renal mass Renal blood
Vur-glom Vbl-glom
Vur-pt1 Vce-pt1 Vbl-pt1
Vur-pt2 Vce-pt2 Vbl-pt2
Vur-pt3 Vce-pt3 Vbl-pt3
Vur-dt Vce-dt Vbl-dt
Vur-cd1 Vce-cd1 Vbl-cd1
Vblad Vbl-vein
Vur-he Vce-he Vbl-he
Vbl-cd2 Vce-cd2 Vur-cd2
Qbypass=a
bypassQ
kid
ney Qur-pt1
Qbl-glom=(1-abypass)Qkidney
Qvein
Qbl-pt1
Qur-pt2 Qbl-pt2
Qur-pt3 Qbl-pt3
Qur-cd1 Qbl-cd1
Qblad
Qbl-vein1
Qur-he
Qbl-he=bbypassQbl-pt
Qur-dt
GFR
Quc-pt1
Quc-pt2
Quc-pt3
Quc-dt
Quc-cd1
Quc-he
Qcb-pt1
Qcb-pt2
Qcb-pt3
Qcb-dt
Qcb-cd1
Qcb-he
Qbl-pt
Qbl-cd2
Qbl-dt=(1-bbypass)Qbl-pt
Qur-cd2
Qbl-vein2
Qcb-cd2
Qurine
Quc-cd2
PSuc-pt1
PSuc-pt2
PSuc-pt3
PSuc-dt
PSuc-cd1
PSuc-he
PScb-pt1
PScb-pt2
PScb-pt3
PScb-dt
PScb-cd1
PScb-he
PScb-cd2 PSuc-cd2
CLincb-pt1
CLinuc-pt1
CLout-uc-pt1
CLout cb-pt1
CLout uc-pt2 CLincb-pt2
CLinuc-pt2 CLout cb-pt2
CLout uc-pt3 CLincb-pt3
CLinuc-pt3 CLout cb-pt3
CLce-pt1
CLce-pt2
CLce-pt3
Modelling Kinetics in the Kidney (Mech KiM)
Transporters are available in all
three Proximal Tubule Cell
compartments on the apical and
basal membrane. Thus, the model
can address:
Regional distribution and changes in
activity for transporters as known for
PepT1/PepT2
Nephrotoxicity as well as change in
systemic exposure due to:
• interplay between transporter on
the apical and basal membrane
• interplay between uptake, efflux
and passive permeation on the
same membrane
• interplay between metabolism and
transporter
Filtration
Secretion (passive + active)
Reabsorption (passive + active)
Urinal tubule Cell (renal mass)
Renal blood
PT – S1
PT – S2
PT – S3
HL
DT
Medu-CD
Cort-CD
Bladder
Considerations
• Passive permeability at basal and apical sides of each of the renal cell
compartments (passive components of reabsorption and secretion);
• GFR directly from the glomerular blood compartment to the glomerular
urinal compartment (filtration);
• Fluid balance within the kidney, i.e. the fluid flow into and out from
the urinal tubular compartments, the renal blood compartments, as
well as the renal mass cell compartments (reabsorption and
secretion);
• Metabolic clearance within the proximal tubular cell compartments;
• Transporters on basal and apical sides of each of the proximal tubular cell
compartments (active components of reabsorption and secretion);
Input data - Renal In Vitro Models
• Commonly used Renal Cell Lines are MDCK, LLC-PK1, OK, however they are
from animal origin.
• Transfected Cells are used in the industry
- CHO and HEK for the basolateral uptake transporters,
- MDCK and LLC-PK1 for the efflux transporters
• Human Kidney Slices are from intact tissue, however the assay is limited to
basolateral transporters and not a HTS method in the industry (expensive,
technical advanced, tissue demanding)
• Human Proximal Tubule Cells (HPTC):
- HRPT, Caki-1, Caki-2, RPTEC, HK-2, HKC-5
Scaling Factor for Renal Transporters
HEK-293,
CHO etc.
Jmax/Km
CLuint T Scaling
Factor 1
PTC
In vitro
CLuint, T
CLuint, T
per
g Kidney
Scaling
Factor 2
Scaling
Factor 3
CLuint, T
per Kidney
REF/RAFPTC PTCPGK Kidney Weight
Input Units
Dimensionless factor that reflects the difference in activity and/or
expression between the in vitro system and the in vivo system
Assuming activity of PTC in vitro equals PTC in vivo REF = 1
REF/RAF:
PD Inputs from Mech KiM
• PD will be possible for the cell and the urinal compartments for PT-S1, PT-S2
and PT-S3.
• The cumulative amount in the cells and urine will be available for PD
simulations (planned for V.12 Release 2).
PD Basic 1
PD Basic 2
PD Link 2
PD Basic 3
PD Link 3
PD Basic 3
PD Link 3
Output
Output
Output
Output
Output
Output
Output
PBPK to Help with Understanding ‘Local Exposure’
(DDI & Genetic Polymorphism of Transporters)
out
insys
tissueCL
CLAUCAUC
.
C
t
E
C
Hysteresis
E
PD Basic Response Compound
PK Effect compartment
X(t) Xe(t)
a
0.01
0.1
1
10
100
0 48 96 144
Co
nce
ntr
ati
on
(m
g/L
)
Time (h)
Upper proximal tubule
Mid proximal tubule
Lower proximal tubule
Loop of Henle
Distal tubule
Cortical collecting duct
Medullary collecting duct
Reabsorption of Water – Concentrated Drug
0
0.2
0.4
0.6
0.8
1
0 48 96 144
Syst
em
ic C
on
cen
trat
ion
(m
g/L
)
Time (h)
CLPD = 0
CLPD = 0.0001
CLPD = 0.001
b
Impact on Systemic Drug Concentrations
0
20
40
60
80
100
120
0 48 96 144
Am
ou
nt
of
sub
stra
te e
xcre
ted
un
chan
ged
in u
rin
e (
mg)
Time (h)
CLPD = 0
CLPD = 0.0001
CLPD = 0.001
c Impact on Excreted Drug
0
20
40
60
80
100
120
0 24 48
Am
ou
nt
of
sub
stra
te e
xcre
ted
u
nch
an
ged
in u
rin
e (
mg)
Time (h)
pH 8pH 7.4pH 5
0
7
14
0 24 48
Am
ou
nt
of
sub
stra
te in
Kid
ne
y ce
lls
(mg)
Time (h)
0
0.25
0.5
0 24 48
Syst
em
ic C
on
cen
trat
ion
(m
g/L
)
Time (h)
a b c
Drug in Plasma, Urine, Kidney Cells
Impact of Urine pH: A weak base (pKa 10) (100 mg iv)
80% renally cleared
CLPD = 0.05 ml/min per million cells
Accumulated Drug
in Urine
Drug Concentration
in Tubular Cell
Drug Concentration
in Plsma
20
25
30
35
40
45
0 4 8 12 16 20 24
Time (h)
Alkaline Urine (pH 8)
20
25
30
35
40
45
0 4 8 12 16 20 24P
lasm
a C
on
cen
trat
ion
(µ
g/L)
Time (h)
Acidic Urine (pH 5)
Memantine – CLrenal pH-dependency
Memantine
primary amine
pKa = 10.27
logP = 3.2
95% renally cleared
Burt et al., 2012 Gordon Conference
• CLPD: 50 µl/min/million cells (PE
from urine pH 7)
• OCT2 (basal uptake):
4.7µl/min/million cells
• ASSUMED apical efflux in the
same range!
Acidic Urine (pH 5) Alkaline Urine (pH 8)
0
0.002
0.004
0.006
0.008
0.01
0 6 12 18 24
Co
nce
ntr
atio
n in
th
e u
pp
er
pro
xim
al
tub
ule
blo
od
co
mp
artm
en
t (m
g/L)
Time (h)
0
0.002
0.004
0.006
0.008
0.01
0 6 12 18 24
Co
nce
ntr
atio
n in
th
e u
pp
er
pro
xim
al
tub
ule
uri
ne
co
mp
artm
en
t (m
g/L)
Time (h)
0
0.002
0.004
0.006
0.008
0.01
0 6 12 18 24
Co
nce
ntr
atio
n in
th
e u
pp
er
pro
xim
al
tub
ule
ce
ll co
mp
artm
en
t (m
g/L)
Time (h)
0
10
20
30
40
50
0 6 12 18 24
Intr
insi
c u
pta
ke c
lear
ance
on
b
aso
late
ral i
nte
rfac
e (
L/h
)
Time (h)
0
0.0005
0.001
0.0015
0.002
0.0025
0 6 12 18 24Sy
ste
mic
Co
nce
ntr
atio
n (
mg/
L)
Time (h)
a b
c d e
Transporter Inhibition/Induction/Genetics
No Inhibition
Inhibition of Minor Route
Inhibition of Major Route
Uptake CL Systemic Drug C(t)
Efferent Blood C(t) Urine Drug C(t) Tubular Drug C(t)
0
20
40
60
80
0 12 24
Co
nce
ntr
atio
n in
me
du
llary
co
llect
ing
du
ct c
om
par
tme
nt
(m
g/L
)
Time (h)
Physiological Variability
Further Details
Howard Burt [email protected]
Linzhong Li [email protected]
Gaohua Lu [email protected]
Sibylle Neuhoff [email protected]
Springer Book Chapter: Bente Steffansen & Yuichi Sugiyama; Editors