Supplementary material for the article PharmRes6848:
Cyclosporine inhibition of hepatic and intestinal CYP3A4, uptake and efflux transporters:
Application of PBPK modeling in the assessment of drug-drug interaction potential
Michael Gertz, Catherine M. Cartwright, Michael J. Hobbs, Kathryn E. Kenworthy, Malcolm
Rowland, J. Brian Houston and Aleksandra Galetin
Summary of in vitro inhibition data from the literature
A systematic search for any reports on cyclosporine potency against main uptake transporters,
efflux transporters and metabolic enzymes was performed. The main transporter/enzymes for which
IC50 (or Ki) data were available included the uptake transporters: NTCP, OATP1B1, OATP1B3 and
OATP2B1; the efflux transporters: BCRP, BSEP, P-gp, MRP2 and the metabolic enzyme: CYP3A4.
The search included hits for any of the different pseudonyms for some of the transporters: OATP1B1
(OATP-C, LST-1, OATP2), OATP1B3 (OATP8), OATP2B1 (OATP-B), BSEP (BAT, SPGP), MRP2
(cMOAT), BCRP (MXR) and cyclosporine (cyclosporin, ciclosporin). In addition to searches in
Pubmed, the online based databases TP-search (http://125.206.112.67/tp-search/login.php) and UCSFFDA TransPortal (http://bts.ucsf.edu/fdatransportal/#content) were sourced for additional data.
Table SI: Summary of IC50 or Ki (in italic) values of cyclosporine A against efflux and uptake transporters and CYP3A4; IC50 values highlighted with
an asterisk indicate CsA concentration used for IC50 determination exceeded its solubility
Transporter
IC50 (Ki) (µM)
System
Efflux transporter
Probe
Reference
ATPase activity
Estrone-sulfate
Methotrexate
ATPase activity
Pheophorbide a
(Özvegy et al. 2001)
(Xia et al. 2007)
(Xia et al. 2007)
(Pawarode et al. 2007)
(Gupta et al. 2006)
BCRP
(ABCG2)
0.50
6.7*,1
7.8*,1
1.40*
4.3*,2
Membrane vesicles
HEK cells expressing BCRP
BSEP (ABCB11)
9.5*,3
7.5-7.8*
0.88*
2.0*
(sensitive to cholesterol)
Membrane vesicles
SK-E2 cells
BSEP vesicle transport assay
Taurocholate
Taurocholate
Taurocholate
(Byrne et al. 2002)
(Wang et al. 2003)
(Morgan et al. 2010)
(Kis et al. 2009)
1.3
([CsA] not specified)
0.46
(single [CsA] of 2.5µM)4
0.35
(single [CsA] of 0.5µM)4
4.7
([CsA] not specified)
1.3
([CsA] not specified)
0.8*
2.5*
0.62*
3.7*
5.1*
Caco-2
Digoxin (B-A)
(Choo et al. 2000) (Wandel et al. 1999)
Digoxin (B-A)
(Tang et al. 2002)
Digoxin (B-A)
(Horie et al. 2003)
Calcein-AM
(Ekins et al. 2002)
Vinblastin
(Ekins et al. 2002)
Calcein-AM
Digoxin (B-A)
Digoxin (ER)
Doxorubicin
Vinblastin
(Schwab et al. 2003)
(Sugimoto et al. 2011)
(Sugimoto et al. 2011)
(Kusunoki et al. 1998)
(Kusunoki et al. 1998)
P-gp (ABCB1)5
LLC-PK1 cells expressing
MDR1
2.2
(single [CsA] of 2.5µM)4
1.6*
6.18*
1.36*
2.22*
MDCK cells expressing
MDR1
5.0*,6
Membrane vesicles from
HeLa cells expressing MRP2
8.11
(single [CsA] of 5µM)4
10
([CsA] not specified)
3.0-3.9*
4.7*,7
21*,8
MDCK cells expressing
MRP2
Digoxin
(Tang et al. 2002)
Digoxin (B-A)
Vinblastin (B-A)
Colchicine (B-A)
Calcein-AM
(Rautio et al. 2006)
(Rautio et al. 2006)
(Rautio et al. 2006)
(Rautio et al. 2006)
MRP1 (ABCC1)
(Leier et al. 1994)
MRP2 (ABCC2)
Vinblastin (B-A)
(Tang et al. 2002)
Calcein AM
(Wortelboer et al. 2003)
A549 and MES-SA/Dx5
Calcein-AM
Membrane vesicles from
LLC-PK cells expressing
MRP2
Uptake Transporter
(Munic et al. 2011)
(Chen et al. 1999)
(Kamisako et al. 1999)
NTCP (SLC10A1)
0.27*
([CsA] not specified)
1.0*
LLC-PK1 cells expressing
NTCP
HeLa cells expressing NTCP
Taurocholate
(Mita et al. 2006)
Taurocholate
(Kim et al. 1999)
0.37*
HeLa cells expressing NTCP
Taurocholate
(Ho et al. 2006)
0.50*
HEK293 cells expressing
OATP1B1
HEK293 cells expressing
OATP1B1
HEK293 cells expressing
OATP1B1
OATP1B1
(SLCO1B1)
0.209
0.05
+ pre-incubation
(Fehrenbach et al. 2003)
Estradiol-glucuronide
(Campbell et al. 2004)
Estradiol-glucuronide
(Hinton et al. 2008)
0.47
largest number of [CsA]
0.02 (Ki ~ 0.014)
+ pre-incubation
largest number of [CsA]
0.37*
0.31*
0.24*
* includes IC50 data in
human hepatocytes
0.24
([CsA] not specified)
3.5
([CsA] not specified)
HEK293 cells expressing
OATP1B1
HEK293 cells expressing
OATP1B1
Atorvastatin
(Amundsen et al. 2010)
Atorvastatin
(Amundsen et al. 2010)
HeLa cells expressing
OATP1B1
HeLa cells expressing
OATP1B1
MDCK cells expressing
OATP1B1
Estradiol-glucuronide
(Tirona et al. 2003)
Rosuvastatin
(Ho et al. 2006)
Cerivastatin
(Shitara et al. 2003)
MDCK cells expressing
OATP1B1
MDCK cells expressing
OATP1B1
Pitavastatin
(Hirano et al. 2006)
Bromo-sulphthaleine
(Letschert et al. 2006)
Fexofenadine
(Matsushima et al. 2008)
Rosuvastatin
(Ho et al. 2006)
Bromo-sulphthaleine
(Letschert et al. 2006)
Amanitin
(Letschert et al. 2006)
Rosuvastatin
(Ho et al. 2006)
Bromo-sulphthaleine
(Letschert et al. 2006)
OATP1B3
(SLCO1B3)
0.57*
0.06*
0.3
([CsA] not specified)
0.3
([CsA] not specified)
HEK293 cells expressing
OATP1B3
HeLa cells expressing
OATP1B3
MDCK cells expressing
OATP1B1
MDCK cells expressing
OATP1B3
OATP2B1
(SLCO2B1)
0.07*
20
([CsA] not specified)
HeLa cells expressing
OATP2B1
MDCK cells expressing
OATP2B1
Metabolising enzymes
CYP3A4
0.36-24.2
37
2
1.1
0.209
0.20
0.30
0.9811
1
HLM
HLM
HLM
HLM
HLM
HLM
HLM
HLM
Various
Tacrolimus
Midazolam
Nifedipine
Repaglinide (M1)
Zonisamide
Etoposide
Midazolam
(Foti et al. 2010)
(Lampen et al. 1995)
(Gascon et al. 1991)
(Combalbert et al. 1989)
(Kajosaari et al. 2005)
(Nakasa et al. 1998)
(Kawashiro et al. 1998)
(Amundsen et al. 2011)
Eadie-Hofstee plots (4 concentrations of the E3S (1, 1.5, 3 and 6µM) or methotrexate (0.375, 0.75, 1.5 and 3mM) and CsA at 0, 5, 10 and 20µM)
EC50 value
3
Dixon plots (3 concentrations of the substrate (3-6µM) and CsA at 0, 10 and 30µM)
4
based on relative apparent permeability values in the absence and presence of a single concentration of a test and a control inhibitor (Gao et al. 2001)
5
Additional studies reporting IC50 values of CsA in other cells lines and membrane vesicles (Rao et al. 1994; Tiberghien et al. 1996; Wigler 1999; Tiberghien et al. 2000;
Wang et al. 2001; Munic et al. 2010)
6
Dixon plots (5 concentrations of the substrate (up to 75µM and CsA at 0 and 10µM)
7
Double reciprocal Lineweaver-Burk plots (5 concentrations of the substrate (up to 100µM) and CsA at 0, 3, 10 and 30µM)
8
Double reciprocal Lineweaver-Burk plots (5 concentrations of the substrate (up to 12µM) and CsA at 0 and 15µM)
9
Dixon plots (3 concentrations of the substrate (0.2-5.4µM) and CsA at 0, 0.1, 0.2, 0.4 and 0.8µM
10
no inhibition of CYP2C8
11
no inhibition of CYP3A5
2
Summary of physiological and cyclosporine specific parameters
A summary of the employed PBPK model and all system parameters relating to blood flows, tissue volumes, extracellular and vascular space of the
tissues as well as parameters defining CsA distribution in blood and tissue is provided here. The PBPK model and the local tissue models have been defined
in previous work and the findings of those studies were applied here (Kawai et al. 1998; Tanaka et al. 1999; Tanaka et al. 2000). The drug independent
parameters (V, Q, fvv, and fcv) have been collated from the literature (ICRP 1975; Davies et al. 1993; Brown et al. 1997; ICRP 2002).
Table SII: Drug independent parameters of the employed PBPK model
Mass1
Blood flows2
% of body weight
% of cardiac output
Adipose4
20.1 (32.1)
6.83 (10.33)
0.01
0.135
0.92
Bone
14.6 (13.0)
5.0 (5.0)
0.041
0.10
1.30
Brain
2.01 (2.17)
12 (12)
0.037
0.004
1.04
Gut5
2.028 (2.247)
19 (20.5)
0.066
0.103
1.04
Heart
0.458 (0.417)
4.0 (5.0)
0.262
0.100
1.03
Kidney
0.43 (0.458)
19 (17)
0.105
0.200
1.05
2.5 (2.33)
25.5 (27)
0.115
0.163
1.08
Hepatic artery
-
6.5 (6.5)
-
Portal vein6
-
19.0 (20.5)
-
0.694 (0.700)
100
Liver
Lung
fvv3
fvic3
Specific
density
g/mL
0.262
0.188
0.996
Muscle7
40.3 (29.2)
17 (12)
0.026
0.120
1.04
Skin
4.58 (3.83)
5.0 (5.0)
0.019
0.302
1.10
rest
rest
0.026
0.120
1.04
Arterial blood
2.59; 1.649
(2.28; 1.399)
-
1.06
Venous blood
5.18; 3.279
(4.56; 2.799)
-
1.06
Plasma
4.28
-
1.03
Red blood cells
3.50
-
1.09
Rest of the body8
1
Reference men/women (72/59kg, excluding contents of stomach, small and large intestine); V are taken from ICRP report 89 Table 2.8 and Q are taken from ICRP report 89
Table 2.40 and cardiac output Table 2.39; tissue densities were available in the ICRP reports from 1975 and 2002; values excluding tissue blood; values in parenthesis
represent reference women
2
Cardiac outputs of 390 and 354 L/h for men and women, respectively
3
Refers to vascular fraction (fvv) and interstitial fraction (fvic) of tissues (data taken from rat and assumed equivalent in human)
4
Adipose includes thymus given their comparable tissue concentration time profiles (Kawai et al. 1998)
5
Gut combines small and large intestine, stomach and pancreas (and spleen) volumes and flows; consequently Q G equal the hepatic input from the portal vein (for the oral
simulations, enterocytes are modelled as separate gut compartment with the shown illustrated tissue volume and blood flow); fvv, fvic and tissue specific density were
combined weighted by volume of the different tissues
6
Sum of gut and hepatic artery equals hepatic vein; for oral simulations gut was divided into gut and enterocytes; for the enterocyte compartment V and Q were 0.175% and
4.62% (this was deducted from the V and Q values of the gut listed above)
7
Includes the rest of the body (4.495 and 6.675% of body weight and 7.5 and 8.5% of the cardiac output for men and women, respectively)
8
The rest of the body was assigned to the muscle compartment
9
Blood residing outside the tissue vasculature; the volume of blood residing inside the vasculature is approx. 2.86 and 2.66% of total body weight for men and women,
respectively
Table SIII: Parameters defining tissue distribution; all tissue except adipose and liver show permeability rate limited distribution and different local models
(1-4) are applied for the various tissues in accordance with the findings in rats (Tanaka et al. 1999)
Model 1
Organ
Muscle
Adipose
PSTC1
fuTC
Kass
Lh-1
133
BFL
kdis
mL.h-1
34.3
129
0.0595
0.0530
mL.h-1
4.22
0.304
Model 2
fuTC
Lung
Heart
Bone
Skin
BT
16.7
12.7
34.8
11.6
KD,TC
µg-eq.mL-1
10.2
4.47
22.5
31.1
0.0185
0.0230
0.893
1.0
µg.mL-1
0.0572
0.0262
0.333
0.327
Model 3
fuTC
Kidney
Liver
Gut
36.1
BFL
124.7
BT
kon
µg-eq.mL-1
125
46.6
94
0.0306
0.0097
0.950
koff
mL2. µg-1.h-1
2.85
34.6
7.06
KD,TC
mL.h-1
1.71
6.44
6.31
µg.mL-1
0.600
0.186
0.894
Model 4
fuTC
Rmax
KD,EF
Kass
kdis
µg.h-1
µg.mL-1
mL.h-1
mL.h-1
Brain
22.9
1.0
232
0.113
10.9
0.258
BFL, blood flow limited (in this case PSTC = 100x blood flow was incorporated); 1 Allometric scaling of PSTC was applied according to: PSTC = A(V)0.75, where V refers to
the tissue volume (A was calculated for the rat data by rearranging the above equation for A; A was then applied to human tissue masses to extrapolate human PSTC values);
fractions unbound in the interstitial fluids were calculated assuming binding to lipoprotein only using Eqs 1 and 2 ; fuI was 0.57 for skin, 0.015 for liver and spleen, and 0.03
for all other tissues
Table SIV: Parameters defining blood distribution of CsA in human
KD,BC (µg.mL-1)
0.1341
(Legg et al. 1988; Kawai et al. 1998)
-1
nPT (µg-eq.mL )
4.1451
(Legg et al. 1988; Kawai et al. 1998)
PSBC (mL.h-1 per ml of blood)
560
(Kawai et al. 1993)
0.03
fup
0.45
Hct
1
These values represent the values reported originally by Legg et al. (1988); however, for the current analysis these values were recalculated for a fup value of 3% to recover
the relationship between blood-to-plasma concentration ratio and total plasma concentrations described elsewhere (Legg et al. 1988)
Table SV: Addition parameters for the modeling of CsA oral absorption
Drug related parameters
Peff (µm/s)
3.3 (1.65 – 4.95)
FG
0.44
SHIF (fasted, fed) (µg.L-1)
16, 247
r (Neoral, Sandimmune) (µm)
0.018, 1.88
h1
0.018, 1.88
D (cm2/min)
1.76x10-4
ρ (g/mL)
1.2
System related parameters
Ktst (h-1)
2.5
Ktduo (h-1)
4.29
Ktjej (h-1)
1.69
Ktil (h-1)
1.56
VL,st (mL)
250+50
VL,duo (mL)
46
VL,jej (mL)
300
VL,il (mL)
240
Vent,duo (mL)
19
Vent,jej (mL)
69
Vent,il (mL)
40
1
For r > 30 µm, h = 30 µm, for r < 25µm, h = r (Hintz et al. 1989); 2 (Avdeef et al. 2004)
(Chiu et al. 2003)
(Ducharme et al. 1995; Ku et al. 1998)
(Persson et al. 2005)
(Andrysek 2003; Hirunpanich et al. 2008)
Same as r1
Based on molecular weight2
Default value in Gastro plus and SimCYP
(Yu et al. 1996; Yu et al. 1998)
Default values in Gastro plus
(Paine et al. 1997)
Table SVI: The fraction unbound of cyclosporine in human plasma
fup (%)
1.3
1.6 (1.0-2.4)
1.6 (1.0-2.4)
1.3 (0.5-4.2)
1.34-1.59
1.5
1.53 (0.52-3.94)
1.33-1.99
3.1-4.5
17.0
Method
ED
ED
ED
ED
ED
MD
ED
ED
UC
EP
Reference
(Henricsson 1987)
(Lindholm et al. 1988)
(Lindholm et al. 1988)
(Lindholm et al. 1989)
(Lindholm 1991)
(Yang et al. 1996)
(Akhlaghi et al. 1999)
(Akhlaghi et al. 1999)
(Legg et al. 1987)
(Zaghloul et al. 1987)
ED, equilibrium dialysis in steel chambers; MD, microdialysis; UC, ultracentrifugation; EP; erythrocyte partitioning
Summary of employed rate equation to simulate cyclosporine concentration-time profiles
A summary of the rate equations defining the PBPK model of cyclosporine is provided below.
It has been adapted into Matlab v.7.12 from previous reports by Rowland and co-workers (Kawai et
al. 1994; Kawai et al. 1998; Tanaka et al. 2000). The set of ordinary differential equations were solved
by the stiff solvers ODE15s or ODE23s.
Terms
Unit
Description
C
µg/L
Drug concentration
Cu
µg/L
Unbound drug concentration
V
L
Volume
Q
L/h
Blood flow
Hct
scalar
Hematocrit
PS
L/h
Permeability surface area product
fu
scalar
Fraction unbound
fcv
scalar
Coefficient that related extracellular to plasma
concentration in the tissue
fci
scalar
Coefficient that related extracellular to interstitial
concentration in the tissue
p
plasma
BC
Red blood cells
AB, VB
Arterial, venous blood
E
Combined plasma-interstitial compartment
I
Interstitial fluid
TC
Tissue-cellular compartment
R
Rapidly equilibrating tissue pool in tissue
S
Slowly equilibrating tissue pool in tissue
NB
Nonspecific binding pool in tissue
SB
Specific binding pool in tissue
Binding to interstitial plasma protein. Cyclosporine is predominately bound to lipoproteins and the
fraction unbound in plasma is given by Eq. 1; where N and KD represent the number of available
binding sites and the dissociation constant, respectively. The fraction unbound in the interstitial fluids,
fuI, of different tissues can therefore be estimated using the interstitial-to-plasma concentration ratio
(IPR) assuming negligible contribution of albumin to cyclosporine binding.
Eq. 1
Eq. 2
IPR for skin 0.25, liver and spleen 1.0 and rest of the body 0.5 (summarized in Kawai et al. 1994)
a. Arterial blood (AB) concentration; equations describing the change of concentration-time
profiles in the blood cells, the unbound concentration in the blood cells, the plasma concentration and
the overall arterial blood concentration are defined below:
Eq. 3
Eq. 4
Eq. 5
Eq. 6
b. Venous blood (VB) equations; the venous blood concentration represents the differential of all
tissues outflow concentrations except gut and spleen (for which the venous blood enters the liver).
The observed data was compared against predicted venous blood concentration (Eq. 9)
Eq. 7
Eq. 8
Eq. 9
c. Rate equations for the extracellular concentration in all tissues; the capillary blood cell and the
extracellular drug concentration were defined by the equations below (Eq. 11a represents the
extracellular concentration in the brain):
Eq. 10
Eq. 11
Eq. 11a
The coefficients fcv and fci are defined by the equations below (Eq. 12 and Eq. 13) and define the
coefficients to convert between CE (concentration in the extracellular space; including the vascular
plasma and the interstitial space of a tissue) and concentrations in plasma (CP) or interstitial fluid (CI),
respectively.
Eq. 12
Eq. 13
d. Tissue concentrations were defined by different models in accordance with previously
reported data in rat.
i. Model 1 representing the muscle, adipose and brain (Eq. 14a); R, rapidly equilibrating and S,
slowly equilibrating pools in tissue
Eq. 14
Eq. 14a
Eq. 15
ii. Model 2 representing the lung, heart, bone, skin and thymus
Eq. 16
where
Eq. 17
iii. Model 3 representing the spleen, gut, kidney and liver (Eq. 19a); NB and SB refer to non-specific
and specific binding pools in tissue
Eq. 18
Eq. 19a
Eq. 20b
1
in case of the liver an addition compartment was included to monitor the hepatic inlet concentration to allow
simulations of the interaction potential; for this, differential of the splanchnic organs, the hepatic artery and the
input from the intestinal absorption were combined using a volume of 100mL (approximated portal blood
volume) – like for the other blood compartments, this compartment was separated into red blood cells and
plasma and the drug distribution between them
e. Intestinal absorption; applied to the simulation of CsA concentration time profiles after oral
doses of CsA Sandimmune and Neoral and in the assessment of the interaction potential at the level of
intestinal (enterocytic) efflux and metabolism
Terms
Unit
Description
A
µg
Amount of drug
Kt
h-1
Transit rate constant
ka
-1
h
Absorption rate constant
FG
scalar
Fraction escaping intestinal extraction
rSI
cm
Intestinal radius
Peff
µm/s
Effective permeability
D
cm2/min
Diffusion coefficient
ρ
g/mL
Particle density (1.2mg/mL)
h
µm
Diffusion layer thickness; same as CsA particle radius
r
µm
Particle radius
CS
µg/L
CsA solubility
Vn
L
Volume residing in the different intestinal luminal segments, n
The relevant rate equations for intestinal absorption of cyclosporine are summarized below and are
based on the compartmental absorption and transit model (Yu et al. 1999).
Eq. 21
Eq. 22
Eq. 23
(n = 2-7)
Eq. 24
Eq. 251
Eq. 26
dAun,n
dt
dAdis,n
dt
 Aun, n1  Kt n 1  Aun, n  Kt n 
 Adis, n1  Kt n1 
Adis,n

3D
 Aun,n   C S ,n 
 rh
Vn

Adis,n

3D
 Aun,n   C S ,n 
 r h
Vn





  Adis, n  Kt n  Adis, n  k a ,n

Eq. 27
Eq. 28
1
modelling of intestinal absorption and metabolism based on in vitro clearance data failed and consequently
intestinal metabolism was modelled semi-mechanistically by incorporating the term FG (Eq. 24)
Summary of in vitro inhibition data
Model fitting was performed in R using generalized nonlinear least square regression analysis with a
combined error model. The code is provided below (example CsA OATP1B1 no pre-incubation, Exp
1). The model was fitted to the untransformed uptake clearance values or alternatively to the
percentage of control; this did not affect the IC50 estimates.
library(nlme)
modIC50<-function(concentration_inhibitor,range_CL,IC50,s_factor,B)
{range_CL/(1+(concentration_inhibitor/IC50)**s_factor)+B}
datIC50<-data.frame(concentration_inhibitor,uptake_rate)
runIC50<-gnls(uptake_rate~modIC50(concentration_inhibitor,range_CL,IC50,s_factor,B),
data=datIC50,start=c(range_CL=800,IC50=200,s_factor=1,B=75),
weights=varConstPower(fixed=c(power=1),const=50))
summary(runIC50)
Table SVII: Summary of IC50 values, standard errors and 95% confidence intervals of
cyclosporine against OATP1B1 and OATP1B3 with (+) and without (-) pre-incubation
Before pre-incubation
IC50 (nM)
SE
After pre-incubation
CI95
IC50 (nM)
SE
CI95
OATP1B3
Exp1
201
27.0
156, 257
28.4
10.2
15.3, 60.3
Exp2
244
47.2
164, 344
18.7
3.62
13.1, 26.5
Exp3
248
56.6
158, 386
11.6
3.47
5.7, 21.1
Exp4
100
27.8
68, 170
18.9
8.20
13.2, 44.2
32.5
8.25
19.6, 51.8
34.7
7.9
24.4, 51.1
OATP1B3
Exp1
163
Exp2
23.4
126, 213
n/a
Exp3
217
21.3
183, 284
32.4
9.91
19.5, 57.8
Exp4
106
23.7
72, 163
28.0
5.26
19.6, 39.7
1
Confidence intervals were computed using -2loglikelihood profiling
Table SVIII: Summary of IC50 values, standard error and 95% confidence intervals of AM1
against OATP1B1 and OATP1B3 with (+) and without (-) pre-incubation
Before pre-incubation
IC50 (nM)
SE
After pre-incubation
CI95
IC50 (nM)
SE
CI95
OATP1B3
Exp1
395
66.5
292, 557
n/a
Exp2
382
88.3
244, 587
126
32.4
79, 201
Exp3
681
157
430, 13742
71.6
37.6
21.3, 189
Exp4
346
111
210, 641
88.0
28.4
46.2, 160
Exp5
252
98.9
124, 551
87.3
27.5
45.5, 140
OATP1B3
Exp1
210
58.8
87.0, 327
n/a
Exp2
283
30.1
228, 340
65.6
14.7
43.5, 103
Exp3
180
25.5
138, 232
55.8
7.56
42.9, 72
Exp4
114
37.4
failed
73.6
9.39
58.5, 93.6
Exp5
168
50.1
95.6, 302
39.6
12.1
23.0, 77.5
1
Confidence intervals were calculated using -2loglikelihood profiling
2
Poorly defined profiles
1
2
3
4
500
200
CLuptake (µL/(sqcm.min))
1000
1000
500
CLuptake (µL/(sqcm.min))
200
500
200
CLuptake (µL/(sqcm.min))
100
500
200
100
50
CLuptake (µL/(sqcm.min))
1000
CsA - OATP1B1
2
5
10
20
50
100 200
500
2000
5000
2
5
10
20
CsA concentration (nmol/L)
50
100 200
500
2000
5000
2
5
10
20
CsA concentration (nmol/L)
50
100 200
500
2000
5000
2
5
10
20
CsA concentration (nmol/L)
50
100 200
500
2000
5000
2000
5000
CsA concentration (nmol/L)
140
100
80
60
CLuptake (µL/(sqcm.min))
40
200 250
150
50
100
CLuptake (µL/(sqcm.min))
100
80
60
40
CLuptake (µL/(sqcm.min))
100
50
CLuptake (µL/(sqcm.min))
150
140
CsA - OATP1B3
2
5
10
20
50
100 200
500
CsA concentration (nmol/L)
2000
5000
1
5
10
50
100
500
CsA concentration (nmol/L)
5000
2
5
10
20
50
100 200
500
CsA concentration (nmol/L)
2000
5000
2
5
10
20
50
100 200
500
CsA concentration (nmol/L)
1
2
3
4
5
1200 1600
800
600
200
400
CLuptake (µL/(sqcm.min))
500
200
100
CLuptake (µL/(sqcm.min))
1000
1000
500
50
100
200
CLuptake (µL/(sqcm.min))
500
200
100
CLuptake (µL/(sqcm.min))
500
200
100
CLuptake (µL/(sqcm.min))
1000
AM1 - OATP1B1
2
5
10
20
50 100
500
2000 5000
2
5
10
AM1 concentration (nmol/L)
20
50 100
500
2000 5000
2
5
10
AM1 concentration (nmol/L)
20
50 100
500
2000 5000
2
5
10
AM1 concentration (nmol/L)
20
50 100
500
2000 5000
5
10
AM1 concentration (nmol/L)
50
100
500
5000
AM1 concentration (nmol/L)
150
250
100
50
CLuptake (µL/(sqcm.min))
200
150
100
CLuptake (µL/(sqcm.min))
200
100
CLuptake (µL/(sqcm.min))
50
150
100
50
CLuptake (µL/(sqcm.min))
100
50
20
CLuptake (µL/(sqcm.min))
250
200
AM1 - OATP1B3
1
5
10
50
500
AM1 concentration (nmol/L)
5000
2
5
10
20
50 100
500
CsA concentration (nmol/L)
2000 5000
1
5
10
50
500
AM1 concentration (nmol/L)
5000
5
10
50
100
500
AM1 concentration (nmol/L)
5000
5
10
50
100
500
5000
AM1 concentration (nmol/L)
Figure S1: Individual log-log plots of 3H-estradiol-glucoronide uptake rate over cyclosporine or AM1 concentrations in the absence (black) and presence (red) of 30 minute
pre-incubation in HEK cells transiently transfected with either OATP1B1 or OATP1B3; lines represent the lines of best fit obtained by generalized last square regression
analysis for the experiments with no pre-incubation (black) and with pre-incubation of 30 minutes (red)
Summary of clinical data and model performance
PBPK model performance was evaluated against a number of studies reported after i.v. dose of cyclosporine and after oral doses of cyclosporine
Sandimmune and Neoral. The relevant analytical assays employed in the studies considered for this assessment included HPLC, EMIT and RIA (both Sandoz
and Incstar). Although only HPLC shows absolute specificity for cyclosporine, the other assays were included as they showed low cross-reactivity for
cyclosporine metabolites (Steimer 1999) and good correlation to HPLC-analyses with coefficients close to one (McBride et al. 1989; Speck et al. 1989; Wolf
et al. 1989; Yatscoff et al. 1990; Dasgupta et al. 1991; Dusci et al. 1992; McBride et al. 1992; Winkler et al. 1992; Beresini et al. 1993; Schutz et al. 1998).
Table SIX: Summary of studies collated to assess PBPK model performance for the prediction of cyclosporine intravenous concentration time profiles
Study
Dose (mg)
Infusion (h)
Group
Age (mean, y)
N
(individual)
N
(concentrations)
VSS reported (L/kg)
slope
R2
VSS (2C)+ (L)
VSS (NCA) + (L)
CLb (2C) + (L/h)
CLb (NCA) + (L/h)
1
190, 114
3
Healthy volunteers
27.6, 28.2
22
2
256
2.5
Healthy volunteers
29
8
3
104.6
2
HLuTx
31
10
4
111.5
3
Healthy volunteers
29
11
5
62.3
2
Pre-HTx
50
7
23
16
15
16
12#
82(L), 118(L)
1.33
0.956
89, 80
81, 86
18.8, 16.4
18.6, 16.3
1.23
1.75
0.935
95
90
22.0
21.7
3.1-4.0
1.77
0.965
72
68
14.3
13.6
1.1
1.35
0.997
82
77
16.6
16.4
n/d
1.68
0.989
125
125
20.7
21.3
1 (Ducharme et al. 1995; Ku et al. 1998) – used for CLintH optimization, 2 (Gupta et al. 1990), 3 (Tsang et al. 1994), 4 (Min et al. 2000) and 5 (Lehle et al. 2007); # reported
concentrations below 10 ng/mL were not consiered (common LLOQ); +compartmental (2 compartments, 2C) and non-compartmental analysis (NCA) using the mean
reported blood concentration time profiles were performed in Phoenix (v. 6.2.1.51, temporary licence); HLuTx and HTx, refers to heart-lung and heart transplant patients,
respectively
Table SX: Summary of studies collated to assess PBPK model performance for the prediction of cyclosporine Sandimmune® oral concentration time profiles
Study
Dose (mg)
Group
Age (mean, y)
N
(individuals)
N
(concentrations)
Slope
R2
1
570
single
Healthy
volunteers
27.6
10
2
300
single
Healthy
volunteers
27.9
22
3
300
single
Healthy
volunteers
27
24
4
600
single
Healthy
volunteers
30
7
5
150
single
Healthy
volunteers
35
12
6
152 (b.i.d)
Steady-state
HTx
7
177 (b.i.d)
Steady-state
KTx
8
302 (q.d.)
Steady-state
KTx
9
151 (b.i.d)
Steady-state
KTx
54
11
46
12
27.9
12
41.9
10
10
20#
19#
10
15
8
10
16
9
0.90
0.897
0.73
0.732
1.30
0.951
0.71
0.895
1.2
0.951
0.87
0.956
1.12
0.933
1.04
0.967
1.27
0.785
1 (Ducharme et al. 1995) – used for optimization, 2 (Mueller et al. 1993), 3 (Mueller et al. 1994), 4 (Edwards et al. 1999), 5 (Drewe et al. 1992), 6 (Akhlaghi et al. 2001), 7
(Bleck et al. 1996), 8 (Hollander et al. 1995) and 9 (Lang et al. 1989); # reported concentrations below 10 ng/mL were ignored (common LLOQ); HTx, KTx refer to heart and
kidney transplant patients, respectively; b.i.d., twice daily; q.d., once daily
Table SXI: Summary of studies collated to assess PBPK model performance for the prediction of cyclosporine Neoral ® oral concentration time profiles
Study
Dose (mg)
Group
Age (mean, y)
N
(individuals)
N
(concentrations)
Slope
R2
1
380
single
Healthy
volunteers
28.2
12
2
180
single
Healthy
volunteers
27
24
3
371.5
single
Healthy
volunteers
28.6
16
4
300
single
Healthy
volunteers
30
28
5
200
single
Healthy
volunteers
18-55
12
6
152 (b.i.d)
Steady-state
HTx
7
109 (b.i.d)
Steady-state
KTx
8
109 (b.i.d.)
Steady-state
RA
54
11
47
11
55
17
16
19#
20
10
11
8
10
8
1.05
0.885
1.42
0.967
0.984
0.881
1.09
0.953
1.08
0.937
1.08
0.947
0.870
0.918
1.26
0.997
1 (Ku et al. 1998) – used for optimization, 2 (Mueller et al. 1994), 3 (Min et al. 2000), 4 (Zimmerman et al. 2003), 5 (Grenier et al. 2006), 6 (Akhlaghi et al. 2001), 7 (Bauer
et al. 2003) and 8 (Fox et al. 2003); # reported concentrations below 10 ng/mL were ignored (common LLOQ); HTx, KTx and RA refer to heart and kidney transplant patients
and patients with rheumatoid arthritis, respectively
Table SXII: Reported drug-drug interactions with cyclosporine A as inhibitor in white populations
AUCI/AUC
CmaxI/Cmax
SLCO1B1 polymorphic study
Comments
7.4 (Asberg et al. 2001)
6.6
Yes (Pasanen et al. 2007)
a
8.7 (Hermann et al. 2004)
10.7
a
15.3 (Lemahieu et al. 2005)
13.7
b
Bosentan
3.3 (Binet et al. 2000)
2.3
n/a
a, c
Cerivastatin
3.7 (Muck et al. 1999)
3.4-5.0
n/a
a, d
Fluvastatin
3.3 (Park et al. 2001)
4.1-6.0
Yes2
a, d
Lovastatin
17.6 (Olbricht et al. 1997)
>20
n/a
a, d
Pravastatin1
5.5 (Olbricht et al. 1997)
2.9
Yes (Niemi et al. 2004; Niemi et al. 2006)
a
11.8 (Park et al. 2002)
7.0
Repaglinide
2.4 (Kajosaari et al. 2005)
1.75
Yes (Niemi et al. 2005; Kalliokoski et al. 2008)
b
Rosuvastatin
4.8-8.3 (Simonson et al. 2004)
6.9-12.2
Yes (Pasanen et al. 2007)
a, e
Simvastatin
8.0 (Ichimaru et al. 2001)
7.6
Yes3
b
Atorvastatin
a
n/a, not available; 1 Additional and comparable data have been reported in children (Hedman et al. 2006); 2 Fluvastatin AUC not significantly different between SCLO1B1
genotypes (Niemi et al. 2006); 3 Significant effect on simvastatin-acid AUC, no effect on simvastatin-lactone AUC (Pasanen et al. 2006); a, AUC increase was assessed in
comparison to historic data and not in a cross-over study design; b, AUC increase was assessed in the same individuals; c, bosentan is an inducer of its own metabolism and
cyclosporine interaction data reported in Binet et al. (2000) were therefore compared to bosentan AUC at stead-state for the same dose regimen reported elsewhere (Weber et
al. 1999); d, average fold-change of single dose and steady-state data; e, multiple dose levels (10 and 20 mg) and dose regimens (single dose and steady-state) were available
for rosuvastatin
PBPK model sensitivity to parameter variability
In these simulations the sensitivity of the model (total blood, unbound plasma and unbound liver
tissue concentrations) to the variation of certain parameters is illustrated by showing the average
values in red (used for all simulations) and two additional parameters values. These represent upper
and lower limits of the parameter (where available) or possible different states (e.g., for PS BC 10-fold
higher or lower permeability into red blood cells as seen for other cyclosporine derivatives (Kawai et
al. 1993)).
fup
3.0, 1.5 (dashed) and 6.0 (dotted)% - blood and interstitial fluid binding were adjusted
accordingly
2
2
3
10
2
10
1
10
Hct
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
Blood CsA concentration (ng/ml)
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
10
25
0
10
-1
0
5
10
15
Time (hours)
20
10
25
0
5
10
15
Time (hours)
20
25
5
10
15
Time (hours)
20
25
0.45, 0.35 (dashed), 0.25 (dotted)
2
2
3
10
2
10
1
10
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
Blood CsA concentration (ng/ml)
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
25
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
10
25
0
512L/h per L of blood, 0.1x (dashed), 10x (dotted)
2
2
3
10
2
10
1
10
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
10
Blood CsA concentration (ng/ml)
PSBC
1
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
25
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
25
10
0
5
10
15
Time (hours)
20
25
Cardiac blood flow
390, 312 (dashed) and 260L/h (dotted)
2
2
3
10
2
10
1
10
Bw
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
Blood CsA concentration (ng/ml)
10
1
10
0
10
5
10
15
Time (hours)
20
10
25
-1
0
5
10
15
Time (hours)
20
10
25
0
5
10
15
Time (hours)
20
25
74kg, 0.80x (dashed), 1.25x (dotted)
2
2
2
10
1
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
Blood CsA concentration (ng/ml)
3
10
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
25
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
10
25
0
5
10
15
Time (hours)
20
25
780, 600 (dashed) and 1014L/h (dotted)
2
2
3
10
2
10
1
10
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
Blood CsA concentration (ng/ml)
10
FG
0
10
-1
0
10
CLintH
1
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
10
25
1
10
0
10
-1
0
5
10
15
Time (hours)
20
10
25
0
5
10
15
Time (hours)
20
25
0
5
10
15
Time (hours)
20
25
0.44, 0.34 (dashed) and 0.59 (dotted)
2
2
3
10
2
10
1
10
10
Unbound liver tissue CsA concentration (ng/ml)
Unbound plasma CsA concentration (ng/ml)
Blood CsA concentration (ng/ml)
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
25
10
1
10
0
10
-1
0
5
10
15
Time (hours)
20
25
10
Figure S2: Simulation of the impact of parameter variability on CsA blood, unbound plasma and unbound liver
tissue concentrations; simulations in red represent the average values and the dashed and dotted lines represent
additional parameter values (either reported in the literature or based on anticipated variability)
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