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GI transfer
May 13 2014
Integration of the gastrointestinal transit
into different in vitro models
Evaluation of the gastrointestinal transit
by using a non-absorbable marker
GI
Stomach
Time
Drug
concentration
Drug
concentration
Transfer
Small Intestin
Time
Integration of the gastrointestinal transit
into different in vitro models
• Non-absorbable marker:
– Paromomycin Sulfate: Gabbroral®: Antibiotic
• Site of action: infections of the GI tract
Not transported to the blood compartment (confirmed by
Caco 2 experiment)
Caco-2
Candidate compound to evaluate the GI transit
200
µM
150
100
50
0
Analysis: HPLC-FLUO
– Derivatisation by Fluorenylmethyloxycarbonyl
chloride (FMOC-Cl) to make it possible to detect
Method validation
Compound
Mobile
Phase
Paromomycin
Sulfate
Detection
Acn:H2O
(87:13)
FLUO
Wavelength
(Ex/Em)
260/315
INTRADAY
1400
Flow Rate
(mL/min)
1
1200
1000
1000
µM
1300µM
500µM
600
800
1300µM
µM
800
7,5
INTERDAY
1400
1200
Retention Time
(minutes)
500µM
600
50µM
50µM
400
400
200
200
0
0
FaHIF
FeHIF
FaHGF
FaHIF
FeHIF
FaHGF
Setup Clinical Trial
– 5 healthy volunteers:
• Drinking 250mL of water, pre-dissolved
with one tablet of Gabbroral®
•A
Aspirating
i ti stomach
t
h&d
duodenal
d
l fl
fluids
id
Setup Clinical Trial
– 4 different conditions:
1. Fasted State
2. Fed State
3. Fed State + Domperidon (Motilium®)
(transit stimulating effect)
4. Fed State + Loperamide HCl (Imodium®)
(transit inhibiting effect)
Clinical Trial
10
pH
• Results:
5
0
– Fasted State:
0
100
200
300
Time (min)
Stomach Fasted State
900
1400
800
1200
paromomycin (µM)
paromomycin (µM)
Duodenum Fasted State
700
600
500
400
300
200
100
0
0.5
800
600
400
200
mean±SEM
mean±SEM
0
1000
0
1
Time (h)
Stomach Fasted State
1.5
2
0
0.5
1
Time (h)
Duodenum Fasted State
1.5
2
Clinical Trial
pH
– Fed State:
8
6
4
2
0
0
100
200
300
Time (min)
Stomach Fed State
400
800
Paromomycin (µM)
Paromomycin (µM)
1000
600
400
200
Duodenum Fed State
200
mean±SEM
mean±SEM
0
0
0
0.5
1
1.5
2
Time (h)
Stomach Fed State
2.5
3
3.5
4
0
0.5
1
1.5
2
2.5
Time (h)
Duodenum Fed State
3
3.5
4
Fed State + Domperidon
pH
10
5
0
0
100
200
Time (min)
Stomach Fed State+Motilium
Duodenum Fed State+Motilium
Paromomycin Cmax
Duodenum (µM)
700
Volunteer 2
600
500
Volunteer 4
Volunteer 3
Volunteer 5
400
300
Volunteer 1
200
100
0
FED STATE
FED STATE + DOMPERIDONE
300
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
1
Psachoulias et al.
2012
2
3
Tiny TIM and TIM-1
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
1
Psachoulias et al.
2012
2
3
Tiny TIM and TIM-1
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
Psachoulias et al. 2012:
Simulated duodenal concentration
concentration-time
time
profiles of paromomycin, using the
three-compartmental model in both the
original mode (Psachoulias et al. 2012)
(■) and the modified mode (Symillides
et al. 2013) (---). Reference data is given
by the mean (± SEM) in vivo duodenal
concentration-time profile (▲).
1400
1200
Paromomycin (µM)
1
1000
800
600
400
200
0
0
0.5
1
Time (h)
1.5
2
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
1
2
3
Psachoulias et al.
2012
Tiny TIM and TIM-1
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
2
TNO Intestinal Model (TIM-1):
TIM-1 fasted state experiment 1 & 2:
Mean concentration-time
concentration time profiles and
pH profiles of the stomach (▲) and
duodenum (●) compartment of TIM-1
compared with the mean concentrationtime profile of the in vivo duodenum (■)
(n=3; mean ± SEM). The arrow indicates
the difference between the gastric
emptying time for the TIM-1 (0.55 hour)
and the in vivo data (0.125 hour).
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
1
2
3
Psachoulias et al.
2012
Tiny TIM and TIM-1
Integration of the gastrointestinal transit
into different in vitro models
• Implementation to in vitro/ in silico:
Simcyp® Simulation model:
Simulations of duodenal
paromomycin
i concentrations
t ti
using Simcyp® (varying gastric
emptying time (GET), from 0.4 h
to 0.101 h) in a “virtual
population”.
Mean duodenal concentrationtime profile in the fasted state in
humans is also shown (mean ±
SEM) (■).
1400
Paromomycin (µM))
3
Mean HV
1200
1000
GET 0.4 h
800
600
GET 0.125 h
400
200
0
0
0.5
1
Time (h)
1.5
2
Conclusions
In Vivo:
o
For drugs in solution, a fast transfer from stomach to small intestine (observed mean
GET 0.125 h) results in a dilution of less than 1:2 in fasting conditions.
o
Delayed gastric emptying time in the fed state (observed mean GET 0.8 h) is not
influenced by the administration of domperidone or loperamide, a transit-stimulating
and
d iinhibiting
hibiti agent,
t respectively.
ti l
In Vitro & In Silico:
o
Using the human data as reference, it was demonstrated that current in vitro and in
silico tools tend to overestimate the gastric emptying time for drugs in solution.
o
Nevertheless, adaptation of model parameters allows for a better simulation of the in
vivo situation.
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