PREDICTING HUMAN PHARMACOKINETICS BY
USING EX VIVO MODELS AND PBPK MODELING;
DEMONSTRATOR STUDY USING ROSUVASTATIN
AND DIGOXIN

Lianne Stevens1,2
Joost Westerhout2
Jeroen Dubbeld1
Joanne Donkers2
Catherijne Knibbe3
Ian Alwayn1
Evita van de Steeg2

P168

1 LUMC, Transplantation Surgery, the Netherlands
2 TNO, Human Biology, Healthy Living, The Netherlands
3 LACDR, Division of Systems Biomedicine and Pharmacology,

The Netherlands

RESULTS
1) Intestinal regional transport

INTRODUCTION
The prediction of hepatic clearance and biliary excretion is of highimportance to assess the pharmacokinetics of drugs. Ex vivo wholeorgan models, are a promising tool compared to in vitro models,thereby paving the way to apply physiologically-based
pharmacokinetic (PBPK) modeling in a more reliable and accurate
way.

Digoxin:

Basolateralsample•limited absorption (average Papp0.57, due to PgP affinity)•Showing higher Papp values in dedistal parts of GI tract (Papp 0.87)

Rosuvastatin:• Similar results were found forrosuvastatin (BCRP substrate), withaverage Papp value of 0.29 and 0.31
for jejunum and ileum and 0.4 for
distal GI tract

AIMTo demonstrate and incorporate ADME data of 2 model drugs(rosuvastatin and digoxin) derived from intestinal segment studies
and whole organ perfused liver and kidney into a generic PBPK
model to predict the drug PK profile in humans.

Figure 2. Papp values in jejunum, ileum and colon of (A) Digoxinand (B) rosuvastatin. Data represents mean ±SD (n=3)2) Hepatic, biliary and renal clearance

METHODS

Perfusate
Digoxin:•Hepatic extraction 0.3

Rosuvastatin:•Hepatic extraction 0.81

• Major route ofelimination via bile forboth compounds

Bile Urine• Minor urinary excretion

Two ex vivo models were developed using porcine organs to study
ADME processes of rosuvastatin and digoxin. The generated data
was subsequently incorporated in a generic PBPK model:

Figure 3. Pharmacokinetic profiles of ex vivo liver and kidney perfusion model(A) Perfusate clearance of digoxin and (B) rosuvastatin. Biliary and urinary
fractions were measured for (C) digoxin and (D) rosuvastatin. Data representsmean ±SD (n=1/n=2)

3) PBPK modelling

1) Intestinal regional transport
Intestinal transport of rosuvastatin and digoxin was determinedusing the InTESTine system• Porcine jejunum, ileum & colon tissue• Assessment of apical to basolateral transport
2) Liver & kidney perfusion
Combined liver kidney perfusion was performed to study biliaryend renal clearance• Cannulation liver: hepatic artery & portal vein
• Cannulation kidney: renal artery• Slow bolus dosing via portal vein
• Perfusate, bile and urine samples taken in time
3) PBPK modelling
A generic PBPK model was subsequently developed with theinput of drug specific properties and system specific properties
Ex vivo models input:• InTESTine: regional Papp data
• Liver & kidney perfusion derived data

Figure 4. Simulated plasma profile of (A) digoxin and (B) rosuvastatin compared to clinical data
Table 2. The simulated and clinical values for bioavailability, renal andfecal excretion for digoxin and rosuvastatin

Bioavailability

Renal

Fecal

Simulated

72%

64%

36%

Clinical70-80%

primary-Simulated

Absolute: 45%
Relative: 47%

44%

56%

ClinicalAbsolute: 20%
Relative: 50%

10%

90%

DrugTable 3. The simulated vs. clinical pharmacokinetic
parameters for single PO dose of 0.5 mg digoxin or 10 mg
rosuvastatin

DigoxinRosuvastatin

Ex vivo data was incorporated into a generic PBPK model and simulations resulted in relatively accurate
predictions of the plasma concentration (Area Under the Curve (AUC)), plasma peak concentration (Cmax), hepaticclearance and bioavailability when compared to human clinical studies

CONCLUSIONSThe combination of ex vivo gut, liver and kidney models with a generic PBPK model is a unique and powerfulcombination to predict ADME profile of (new) drugs
Figure 1. Graphical representation of combined ex vivo liver andkidney perfusion; generating perfusate, bile and urine fractions.

• possibility to calculate the fraction that undergoes enterohepatic circulation.
• Future research is aimed at studying drug-drug interactions an the effects of disease processes.