A generic PBPK model for
predictive DMPK (GastroPlus)
Physiologically Based Pharmacokinetic (PBPK)
Modeling in Drug Development and Evaluation
April 6-10, 2009
Alexandria, VA
Viera Lukacova
Simulations Plus, Inc.
PBPK Workshop
April 6-10, 2009
Outline
• Physiological model of GI tract
– pH-dependent solubility and absorption
– Saturable processes in gut
• PBPK model
– Tissue types
– Transport, clearance and distribution mechanisms
• Examples:
– Midazolam
• Predict human (adult and pediatric) PK using in silico and in
vitro data
– Cilostazol
• Predict human PK using in silico and in vitro data
– Terbinafine
• Predict human PK using in silico properties and rat clearance
PBPK Workshop
April 6-10, 2009
Fa
FDp
(not Fa!)
* Modified from van de Waterbeemd, H, and Gifford, E. ADMET In Silico Modelling:
Towards Prediction Paradise? Nat. Rev. Drug Disc. 2003, 2:192-204
PBPK Workshop
April 6-10, 2009
F
Processes Involved in Oral Absorption
Efflux &
Influx
Transport
Cmesentery/portal vein
Blood
Centerocytes
Passive Absorption
Enterocytes
Gut wall metabolism
Dissolution
Dose
Disintegration
Lumen
Local pH, fluid volume
Excretion
Drug in
solution,
Clumen
Precipitation
Degradation
These phenomena are repeated in each of the compartments of the gastrointestinal tract
PBPK Workshop
April 6-10, 2009
Advanced Compartmental Absorption
and Transit (ACAT) Simulation Model
Enterohepatic
Enterohepatic circulation
circulation
Stomach
Stomach
Duodenum
Duodenum Jejunum1
Jejunum1 Jejunum2
Jejunum2
Ileum1
Ileum1
Ileum2
Ileum2
Ileum3
Ileum3
Caecum
Caecum
Unreleased
Unreleased
Undissolved
Undissolved
Dissolved
Dissolved
Lumenal
Lumenal
Degradation
Degradation
(losses)
Gut
GutWall
Wall
Portal
Portal
Vein
Vein
Gall
Gall
Bladder
Bladder
Metabolism
Metabolism
Liver
Liver
Hepatic
Hepatic Artery
Artery
Systemic
Systemic
Circulation
Circulation
Brain
nd Compartment
22nd
33rdrd Compartment
Adipose
Compartment
Compartment
Muscle
Skin
PBPK Workshop
April 6-10, 2009
Asc.
Asc. Colon
Colon
E
E
xx
cc
rr
ee
tt
ii
oo
nn
GastroPlus Physiologies
•
•
•
•
•
•
•
•
•
•
•
•
Human Physiological Fasted –
PBPK*
Human Physiological Fed
Human Equal Transit Time Fasted
Human Equal Transit Time Fed
Beagle Dog Fasted – PBPK*
Beagle Dog Fed
Rat Fasted – PBPK*
Mouse Fasted – PBPK*
Cynomologous Monkey Fasted –
PBPK*
Rabbit Fasted
Cat Fasted
User-defined
PBPK Workshop
April 6-10, 2009
Each physiology includes default
values for:
• pH in each compartment
• Transit time for each
compartment
• Lengths & radii of each
compartment
• Stomach volume
• Hepatic blood flow rate
• Gut enzyme and transporter
distributions
* Each species shown with PBPK can also be modeled
with a traditional compartmental PK approach
pH-Dependent Solubility
Base
Acid
Zwitterion
PBPK Workshop
April 6-10, 2009
Changing pH Environment
PBPK Workshop
April 6-10, 2009
Oral Absorption of Ionizable Drugs
F
F
F
H
N
O
O CH3
O
H 3C
H3 C
N
CH3
N
H
LAB687
Log P = 4.7
*S+Native Solubility = 0.17 µg/mL
*S+Peff = 1.96 x 10-4 cm/s
Fraction Absorbed: ~8%
Cl
Toremifene
*S+Log P = 6.57
*S+Native Solubility = 0.069 µg/mL
*S+Peff = 12 x 10-4 cm/s
Fraction Absorbed = 100%
*estimated
PBPK Workshop
April 6-10, 2009
O
by ADMET Predictor
LAB687
SolFactor* = 7.8x104
PBPK Workshop
April 6-10, 2009
*
Toremifene
SolFactor=1.2x105
SolFactor = ionized-form solubility / neutral-form solubility
Dissolution
Dissolution rate constant in intestinal lumen compartment number i for bin j:
k diss ( i , j ) =
D
ρr jT
(C
s
− C(i ) )
(1 + 2 s )
s
Cs
C(i)
r
T
D = diffusion coefficient
CS = solubility at local pH
C(i) = lumen concentration in compartment i
T = r0j
ρ = particle density (solid density of API particles after disintegration)
rj = spherical particle radius for bin j
T = diffusion layer thickness (= particle radius up to a limit)
s = shape factor (Length/diameter*) – for spherical particles = 1
*in original Johnson’s equation, s’=Length/radius and the term in equation is
2(1 + s')
s'
PBPK Workshop
April 6-10, 2009
Absorption
Absorption term in compartment number i:
dMabs(i)/dt = α(i) Peff(i) Vlum(i) (C(t)lum(i) – C(t)ent(i))
ka‘(i)
Mdiss(i)
α(i) = absorption scale factor in compartment i (nominal value is surface/volume,
which is 2/Ri)
Ri = radius of compartment i
Li = length of compartment i
Peff(i) = permeability in compartment i*
Vlum(i) = volume of lumen for compartment i
C(t)lum(i) = lumen concentration in compartment i
C(t)ent(i) = enterocyte concentration in compartment i
* permeability may be net, or only passive component
PBPK Workshop
April 6-10, 2009
Ri
Li
Ungell, A.L., et al., 1998, J. Pharm. Sci. 87:360-366
PBPK Workshop
April 6-10, 2009
Rabbit Isolated Tissue Permability
Size of Circle = Pcolon / Pileum Ratio
Rabbit Ileum Peff (cm/s x 10^6)
100
Ratio of 1
10
1
-6
-4
-2
0
log D (7.4)
PBPK Workshop
April 6-10, 2009
2
4
6
Opt logD model Colon ASF estimation
2.5
Default colon ASF
(2/R)
Colon ASF
2
Opt logD
model colon ASF
1.5
1
0.5
0
Fosinopril
(logP=4.5,
JejPeff=1.26)
PBPK Workshop
April 6-10, 2009
Carbamazepine
(logP=1.5,
JejPeff=4.3)
Ranitidine
(logP=0.1,
JejPeff=0.43)
Carrier-mediated Transport
dMent(i)/dt =
Apical Diffusion Rate
+ Apical Carrier-mediated Transport Rate
- Basolateral Transfer Rate
- Gut Metabolism Rate
Enterocytes
Efflux transporter
Blood
B
Gut Wall
Metabolism
Apical Carrier-mediated Transport rate =
DFinflux(i) Vmax,influx C(i) / (Km,influx + C(i))
- DFefflux (i) Vmax,efflux Cu,ent(i) / (Km,efflux + Cu,ent(i))
A
Lumen
Influx transporter
DF = distribution factor for transporter amounts relative to Vmax
measurement environment (when Vmax in a compartment is the same as
Vmax in the measurement environment, then DF = 1.0).
PBPK Workshop
April 6-10, 2009
Transporter Distribution Factors
Lower Vmax
PBPK Workshop
April 6-10, 2009
B
B
A
A
Higher Vmax
Influx Transporter Distribution in Human Gut
Human
Stom. Jejunum Ileoc. AscCol. DecCol.
Caco-2
Esoph.
Duod. Ileum
Cecum TraCol. Rectum
RT-PCR
Peptide Transporter-1
Southern
Peptide Transporter-3
Peptide Histidine
Transporter 1
Human Peptide
Tranporter – 1
β-actin
Herrera-Ruiz AAPS Pharmsci 2001; 3 (1) article 9
(http://www.aapspharmaceutica.org)
PBPK Workshop
April 6-10, 2009
Influx Transporter Distribution in Rat Gut
Rat
Stom.
Jejunum
Duod.
Ileoc.
Ileum
Colon
Cecum
RT-PCR
Peptide Transporter-1
Peptide Transporter-3
Peptide Histidine
Transporter 1
Human Peptide
Tranporter – 1
β-actin
Herrera-Ruiz AAPS Pharmsci 2001; 3 (1) article 9
(http://www.aapspharmaceutica.org)
PBPK Workshop
April 6-10, 2009
Southern
Pgp Expression in Human Small Intestine
Mouly, S., Paine, M.F. PharmRes-20(10):1595-1598 (2003)
PBPK Workshop
April 6-10, 2009
Simulated Valacyclovir
GastroPlus results with gut transporters were first reported in
Feb. 2003 at AAPS Drug Transport Workshop, Peachtree City, GA
PBPK Workshop
April 6-10, 2009
Simulated Gabapentin
PBPK Simulation of 400 mg Solution Dose
Using LAT2 Gut Distribution
Vss from in silico Kps (Rodgers & Rowland)
CL was from fup * GFR for 41 yo Female
Optimized LAT2 Km and Vmax across
PO doses from 400 to 1600 mg
Km = 5.8 mM Vmax = 5.1 µg/s
PBPK Workshop
April 6-10, 2009
Clinical data from: Gildal BE, Epilepsy Res. 40:123 (2000)
Non-linear Dose Dependence of Gabapentin
PBPK Workshop
April 6-10, 2009
400 mg Fb = 55%
800 mg Fb = 46%
1200 mg Fb = 41%
1600 mg Fb = 36%
First Pass Metabolism
• Gut wall first pass metabolism can
be significant, especially for
CYP3A4 and CYP2D6 substrates
CYP3A4
• Hepatic first pass is a function of
the unbound concentration
presented to the liver and the
hepatic blood flow rate
• Changing absorption location and
rate (e.g., by changing formulation)
can change both gut wall
metabolism and hepatic first pass
metabolism
PBPK Workshop
April 6-10, 2009
J
lumen
enterocyte
Drug
Metabolite
Hepatic Metabolism
Liver Metabolism Rate = CLh * Cliver
CLh = Eh * Qh * RB
Eh = CLinth* fu,plasma / [CLinth* fu,plasma + Qh * RB ]
where CLinth = Σ Vmax(j) *Cu,hepat / (Km(j)+ Cu,hepat)
Eh = total hepatic extraction
Qh = hepatic blood flow rate
RB = blood-to-plasma concentration ratio
CLinth = total hepatic intrinsic clearance
Vmax(j) = maximum metabolic rate for enzyme j
Km(j) = Michaelis-Menten constant for enzyme j
Cu,hepat = unbound concentration in hepatocytes
PBPK Workshop
April 6-10, 2009
Gut Metabolism Scale Factors
Paine MF and Thummel KE, JPET, 1997; 283(3): p. 1552-62.
3A4 (nmol) = 9.7
Liver CYP3A = 5489 nmol
Liver Wt. = 1800 g
MicProt = 38 mg / g liver
CYP3A4 = 69.7 pmol / mgP
PBPK Workshop
April 6-10, 2009
38.4
22.4
Gut Metabolism
GMR(i) = GEDF(j,i)*Vmax(j)* Cu,ent(i)/(Km(j)+ Cu,ent(i))
GMR(i) = gut metabolism rate in compartment i
GEDF(j,i) = gut enzyme distribution factor for enzyme j in
enterocyte compartment i relative to amount in whole liver
Vmax(j) = maximum metabolic rate for enzyme j in whole liver
Km(j) = Michaelis-Menten constant for enzyme j
Cu,ent(i) = unbound drug concentration in enterocyte
compartment i
PBPK Workshop
April 6-10, 2009
Physiologically based pharmacokinetics
(PBPK)
Each compartment represents a tissue, with a
specific volume, blood perfusion rate, and
partition coefficient Kp(i) for each tissue,
where i denotes the tissue.
Three types of compartment:
Blood
Perfusion-limited tissue
Permeability-limited tissue
Tissues can have enzymes and transporters.
Tissues can have intrinsic clearance.
For perfusion-limited tissues, the concentration of
drug in the tissue is Kp(i) * unbound
concentration in plasma at all times
For permeability-limited tissues, Kp(i) serves as
the limiting value, but the actual tissue
concentration is determined by the
permeability and surface area exposed to the
plasma, so time is needed to reach the
concentration ratio defined by Kp(i).
PBPK Workshop
April 6-10, 2009
What’s Involved in PBPK
• Models of individual tissues
– Flows, Volumes
• Global model
– connections between tissues
• Mechanisms
– Clearance
– Metabolism
– Transport
– Binding
PBPK Workshop
April 6-10, 2009
Perfusion or Permeability Limited?
PERFUSION-LIMITED: If permeability is high, then the
amount of drug that partitions into the tissue will be limited by
the blood flow rate (perfusion rate) through the tissue. A
partition coefficient, Kp, is used to calculate the concentration
of drug in the tissue at each time step. Partitioning is assumed
to be instantaneous. If there are no measured values, partition
coefficients can be estimated from physicochemical properties
(logP, fup,fut).
PERMEABILITY-LIMITED: If permeability is low, the
amount of drug that partitions into the tissue will be limited by
the permeability and the surface area available for permeation.
A (permeability*surface) area product is used to calculate the
rate of drug transfer into or out of the tissue. At early times, the
tissue concentration will be less than the product of the
partition coefficient, Kp, and the unbound concentration in the
blood. The partition coefficient, Kp, serves to limit the extent
of partitioning, while permeability limits the rate.
PBPK Workshop
April 6-10, 2009
Perfusion limited
Kp
Q
P*A
Q
Permeability limited
Liver Tissue
BSEP
MRP2
MDR3
bile
MDR1
hepatocyte
Can be specified as:
•
Biliary Clearance Fraction
(fraction of liver clearance due to
biliary excretion)
•
An active efflux of drug across
canalicular membrane
•
A passive diffusion of drug across
canalicular membrane
hepatocyte
dM b  Activity × Vmax × C drug × Fut 
=
+ (PStcAp × C drug × Fut ) + (M clear × Fbcl )


dt
C drug + K m


active efflux
PBPK Workshop
April 6-10, 2009
passive diffusion
Biliary
clearance
fraction
Kidney Tissue
Perfusion-Limited:
CLfilt estimates:
- Fup*GFR
- GFR
- Fraction of Kidney blood flow
- Other
PBPK Workshop
April 6-10, 2009
Permeability-Limited:
Mechanisms: Transport
• Transport across cellular membranes:
– Linear, PStc or Peff x SA
• Only unbound fraction in extracellular space can
permeate – concentration gradient determines rate
perm = PSTC (Cect,u − Cict,u )
Cect : Drug Concentration in extracellular space
Cict : Drug Concentration in intracellular space
PSTC : Permeability - Surface Area product
– Nonlinear: Vmax, Km
Fluxin =
PBPK Workshop
April 6-10, 2009
Activity ⋅Vmax ⋅ Cect,u
K m + Cect,u
;
Fluxout =
Activity ⋅Vmax ⋅ Cict,u
K m + Cict,u
Mechanisms: Clearance
• Ability of tissue to clear drug
– limited by mass-flow of drug to tissue
– only unbound drug can be cleared
• Linear clearance
– CLint = intrinsic clearance
• Nonlinear clearance
– Michaelis-Menten kinetics
i
 Activity ⋅ Vmax
= ∑
i
i =1 
K
m + C t ,u

nEnz
CLint, u




CLint, u : Unbound intrinsic clearance
Ct ,u : Unbound tissue drug concentrat ion
PBPK Workshop
April 6-10, 2009
Mechanisms: Clearance
• Relationship between CLint and CLp
– clearance limited by tissue perfusion
– true regardless of actual mechanism




CL
int,
u

CL p = Rbp ⋅ CLb = Rbp ⋅ Q
Rbp 

CL
Q
+
 int,u
fup 

CL p , CLb : plasma, blood clearance
Q : Tissue blood flow
Rbp : Blood/plasma concentration ratio
fup : fraction unbound in plasma
PBPK Workshop
April 6-10, 2009
Estimating PBPK Parameters
Tissue weights, tissue perfusion rates, tissue densities, and partition
coefficients for each tissue for the drug are required for PBPK.
The Population Estimates for Age-Related Physiology™ (PEAR
Physiology) module inside of PBPKPlus generates such values. It
is based on the NHANES database (2003-2004) for
American/Western physiologies, and a Japanese government
database for Japanese/Asian physiologies. You specify age, gender,
and venous hematocrit.
The PEAR Physiology module also generates tissue parameters for
rat, dog, and mouse, but age, and gender are fixed.
PBPK Workshop
April 6-10, 2009
American Physiologies - Average Body Weight
PBPK Workshop
April 6-10, 2009
American Physiologies - Average Body Height
PBPK Workshop
April 6-10, 2009
Japanese Physiologies - Average Body Weight
PBPK Workshop
April 6-10, 2009
Japanese Physiologies - Average Body Height
PBPK Workshop
April 6-10, 2009
PEAR-Physiology Method
• Input parameters for PEAR-Physiology are species, age,
gender, and venous hematocrit. The output is a complete set
of tissue physiology parameters.
• 1. Look up average weight, height, bioimpedance.
• 2. Calculate BMI and Fat Free Mass (FFM)
• 3. Set the constant perfusion rates per mL tissue
• 4. Calculate blood volumes
• 5. Calculate mean weight, volume, density, perfusion for each
tissue.
PBPK Workshop
April 6-10, 2009
PEAR-Physiology Method
PBPK Workshop
April 6-10, 2009
Mechanisms: Distribution
• Partitioning into tissues
– binding
– lipid partitioning
– transport
– other??
• Measurable quantity
– Kpapp = Ctu / Cpu at steady state
• non-eliminating tissue
PBPK Workshop
April 6-10, 2009
Combining In Silico Technologies
F
O
N
O
QSAR
Activity
S+log P
S+pKa
S+Sw at native pH
S+Peff
S+Vd
S+fup
Cl
Toxicities
. . . etc.
Structure-property predictions from ADMET Predictor™ provide estimates
for:
pKa, logP, solubility, permeability, plasma protein binding, etc.
Kp’s estimated from logP or logD and tissue properties
Clearance is the big unknown – not yet reliably predicted from structure for
diverse molecular structure (you still need to measure this in vitro)
PBPK Workshop
April 6-10, 2009
Predicting Kp’s
PBPK Workshop
April 6-10, 2009
Predicting Kp’s
Poulin & Thiel method (Homogeneous):
[
K ⋅ (V
Kp =
[K ⋅ (V
nlt
nlp
] [
)]+ [(V
] ⋅ fu
)] fu
+ 0.3V pht ) + (Vwt + 0.7V pht )
p
+ 0.3V php
t
wp
+ 0.7V php
Poulin & Thiel method (Extracellular):
Kp =
Ve
(1 − hct )
Berezhkovskiy:
[
K ⋅ (V
Kp =
[K ⋅ (V
nlt
nlp
PBPK Workshop
April 6-10, 2009
⋅
fu p
fut
] [
)]+ [(V
]
)]
+ 0.3V pht ) + (Vwt / fut + 0.7V pht )
+ 0.3V php
wp
/ fu p + 0.7V php
Predicting Kp’s
Rodgers and Rowland method:
Kp = Kpu × fup
1.
Strong bases and zwitterions with at least one base pKa > 7 – takes into
consideration the unique interaction of bases with acidic phospolipids
Kpu = Vewt
2.
 (1 / X [ D ], IW )
  Ka[ AP ]T ((1 / X [ D ], IW ) − 1)   K ⋅ Vnlt + (0.3K + 0.7)V pht

+
+
Viwt  + 
 (1 / X


 
(1 / X [ D ], P )
(1 / X [ D ], P )
[ D ], P )

 
 




Acids, Neutrals, and weak bases – takes into account binding to lipoproteins
(neutral drugs) or tissue albumin (acids and weak bases – ionized fractions)
Kpu =
(1 / X [ D ], IW )Viwt
(1 / X [ D ], P )
+ Vewt

 K ⋅ Vnlt + (0.3K + 0.7)V pht   1
K ⋅Vnlp + (0.3K + 0.7)V php 




+
+
−1 −
× RAt 

  fup

(
1
/
X
)
(
1
/
X
)
[
D
],
P

[
D
],
P


 

X[D] – fraction of neutral drug species in intracellular water (IW, pH=7) and plasma (P, pH=7.4)
K – vegetable oil/water partition coefficient for adipose tissue and 1-octanol/water partition coefficient for remaining tissues
fup-fraction unbound of drug in plasma, Ka – association constant of base with acidic phospholipids, [AP]T – tissue concentration of
acidic phospholipids
RAt – tissue/plasma lipoprotein or albumin ratio
PBPK Workshop
April 6-10, 2009
Predicting Kp’s
Rodgers and Rowland – Single (S+ modification)
Simulations Plus (in collaboration with Roche) developed an alternative
approach to calculating Kps according to Rodgers and Rowland:
• Single equation is being used for all compounds
• The binding of drug to acidic phospholipids or plasma proteins is given by
actual ionization of each drug at physiological pH
single equation
two equations
3
1
2.5
0.8
Kp adipose
Kp muscle
single equation
2
1.5
1
0.6
0.4
0.5
0.2
0
0
4
6
8
pKa
PBPK Workshop
April 6-10, 2009
10
two equations
4
6
8
pKa
10
Predicting Kp’s
Rodgers and Rowland – Single (S+ modification)
Comparison of Vss calculated from Kps based on Original Two
and New Single Equation
( ErrTwo − ErrOne )
E=
( ErrTwo + ErrOne )
Pred Vss Normalized Error
1.5
1
0.5
0
0
2
4
6
8
-0.5
-1
-1.5
strongest base pKa
PBPK Workshop
April 6-10, 2009
10
12
Predicting Kp’s
Adjusted Fup
• Highly lipophilic drugs can exhibit significant binding to plasma lipids
• Binding to plasma lipids may not be captured by standard equilibrium dialysis
measurement of Fup
GastroPlus incorporates an equation for Adjustment of Fup based on following
assumptions:
1. logPo/w can be used as an estimate for the drug partitioning into plasma lipids
2. Experimental Fup is a measure of drug binding ONLY to plasma albumin
PBPK Workshop
April 6-10, 2009
Required Parameters
Biopharmaceutical properties (logP, pKa, Solubility, Permeability,
Fup, Rbp)
• prediction from structure (ADMET Predictor)
• in vitro experimental values
Clearance
• in vitro (microsomes, hepatocytes, rCYPs)
• Pre-clinical species
PBPK Workshop
April 6-10, 2009
Example:
Midazolam
Bornemann L.D. et al. Dose Dependent Pharmacokinetics of
Midazolam. Eur J Clin Pharmacol. 1985; 29:91-95.
Human PK prediction using no human data:
in silico and in vitro properties
in vitro clearance
PBPK Workshop
April 6-10, 2009
Midazolam - Inputs
F
LogP = 2.7
pKa = 6.0 (Base)
N
N
N
Solubility = 0.13 mg/mL @ pH = 5.33
Fup = 3.5%
Rbp = 0.55
Peff = 4.68×10-4 cm/s (ADMET Predictor)
3A4 Km = 3.7µM
3A4 Vmax = 850 nmol/min/mg MP
Physiology – Typical western 30yo male
PBPK Workshop
April 6-10, 2009
Cl
Midazolam – Model Setup
• Import structure
• Enter in vitro values for properties
• Create default PBPK model for adult physiology
• Calculate Kps
• Set up enzymes
the adult enzyme expression in liver included in the default
PBPK model
the distribution of 3A4 in gut included with default ACAT model
use built-in utility for conversion of in vitro Km and Vmax values
to in vivo values
PBPK Workshop
April 6-10, 2009
Midazolam – Results – No Fitted Parameters!
PBPK Workshop
April 6-10, 2009
Midazolam – Results – No Fitted Parameters!
Cmax
1 : 1.4
1 : 1.3
1 : 1.3
AUC
1 : 1.3
1 : 0.96
1 : 1.2
PBPK Workshop
April 6-10, 2009
Midazolam – Results – Pediatric
• Midazolam metabolized by 3A4
• Known age-dependent 3A4
expression
• Known age-dependent tissue sizes
and blood flows
Johnson, T.N., Br. J. Clin. Pharm. 51(5):451 (2001)
PBPK Workshop
April 6-10, 2009
Example:
Cilostazol
Bramer S.L. et al. Cilostazol Pharmacokinetics after Single and
Multiple Oral Doses in Healthy Males and Patients with
Intermittent Claudication Resulting from Peripheral Arterial
Disease. Clin Pharmacokinet 1999; 37(Suppl 2): 1-11.
PK prediction using:
in silico and in vitro properties
in vitro metabolism data
PBPK Workshop
April 6-10, 2009
Cilostazol - Inputs
N N
N
All properties from ADMETPredictor:
S+LogP = 2.9
S+pKa = 1.39 (Base); 11.26 (Acid)
O
S+Sw = 0.542 mg/mL @ S+pH = 6.88
S+Fup = 22.86% (adjusted Fup = 10.86%)
Rbp = 1 (default)
N
O
S+Peff = 1.09×10-4 cm/s
In vitro Km and Vmax for 3A4, 3A5, 2C19 and 2C8
Human Physiology – Typical western 30yo male
PBPK Workshop
April 6-10, 2009
N
Cilostazol – Model Setup
• Import structure
• Create default PBPK model for adult physiology
• Calculate Kps
• Set up enzymes
the adult enzyme expression in liver included in the default
PBPK model
the distribution of 3A4 in gut included with default ACAT model
use built-in utility for conversion of in vitro Km and Vmax values
to in vivo values
PBPK Workshop
April 6-10, 2009
Cilostazol - Results
1 : 0.43
1 : 0.45
PBPK Workshop
April 6-10, 2009
Default PBPK model
with calculated Kps
with all in silico
inputs
Cilostazol - Results
1 : 1.1
1 : 0.97
PBPK Workshop
April 6-10, 2009
Default PBPK model
with calculated Kps
using in vitro Fup
(3.3%) and Rbp
(0.6) values
Example:
Terbinafine
Hosseini-Yeganeh M., and McLachlan A. Physiologically Based
Pharmacokinetic Model for Terbinafine in Rats and Humans.
Antimicrob Agents Chemother 2002; 46(7): 2219-2228.
PK prediction using:
in silico properties
clearance scaled from Rat
PBPK Workshop
April 6-10, 2009
Terbinafine - Inputs
All properties from ADMETPredictor:
S+LogP = 5.94
S+pKa = 7.95 (Base)
S+Sw = 8.16 µg/mL @ S+pH = 8.66
S+Fup = 14.4% (adjusted Fup = 0.019%)
Rbp = 1 (default)
S+Peff = 12×10-4 cm/s
Rat Cp-time profile after IV administration
Human Physiology – Typical western 30yo male
PBPK Workshop
April 6-10, 2009
Terbinafine – Model Setup
• Import structure
• Create default PBPK model for adult
physiology
• Calculate Kps
• Estimate CL from rat IV Cp-time profile
• Scale rat CL to human
PBPK Workshop
April 6-10, 2009
Terbinafine – Rat Data
Dose = 1.5mg
IV bolus administration
NONCOMPARTMENTAL ANALYSIS OF
DATA:
AUC =
AUMC =
MRT =
CL =
K(z) =
CL/kg=
Vss =
Vss/kg=
3.6426
8.0494
2.2098
0.4118
11.7914
1.6472
0.91
3.6398
µg-h/mL
µg-h^2/mL
h
L/h
1/h
L/h/kg
L
L/kg
Scaling clearance to human using ¾ power
law:
Human CL = 32.7 L/h
PBPK Workshop
April 6-10, 2009
Terbinafine - Results
1 : 0.8
1 : 1.3
PBPK Workshop
April 6-10, 2009
Default PBPK
model with
calculated Kps
Terbinafine - Results
1 : 1.1
1 : 1.3
PBPK Workshop
April 6-10, 2009
Default PBPK
model with rat Kps
Published Studies
Jones H. et al. Clin Pharmacokinet 2006, 45(5):511-542
PBPK Workshop
April 6-10, 2009
Published Studies
Cole S. et al. Poster Presentation, ISSX Asian meeting 2008
PBPK Workshop
April 6-10, 2009
Summary
• PBPK approach provides superior results to simple allometric scaling
• For prediction of oral doses, the processes in the gastrointestinal tract are
important – a predictive model must include a good gut model
• GastroPlus
Provides physiological models for gut (ACAT) as well as other
tissues (PBPK)
Provides an easy way of creating the default physiological
models for routine predictions (different species, age dependent)
Provides flexible models – easy to adjust for special populations,
physiological or disease states for “expert” use
Allows incorporating all relevant transport and clearance
processes (with default settings for all processes for which
information is already available in literature)
PBPK Workshop
April 6-10, 2009