computer aided drug delivery system

1. “MODEL CONSTRUCTION IN
GASTROINTESTINAL SIMULATION.”
Presented by:
Karthik swamy B.M
(Department of
pharmaceutics)
Under the guidance of
Dr.Y.Anand kumar

2. In silico
• In silico (literally alluding the mass use of
silicon for semiconductor computer chips) is an
expression used to performed on computer or via
computer simulation
• In silico tools capable of identifying critical
factors (i.e. drug physicochemical properties,
dosage form factors) influencing drug in vivo
performance, and predicting drug absorption
based on the selected data set (s) of input factors.

3. MODELS
• Compartmental Absorption and Transit
(CAT)
• Advanced Dissolution, Absorption and
Metabolism (ADAM) model;
• Grass model.
• GI-Transit-Absorption (GITA) model.
• CAT model; Advanced CAT (ACAT)
model.

4. Some commercial software packages
for scientific basis
• GastroPlus™,
• INTELLIPHARM® PKCR,
• SimCYP
• PK-Sim®
• IDEA™
• Cloe® PK
• Cloe® HIA.

5. Gastro intestinal absorption simulation
Simulation software packages, such as
gastro plus™, are advanced technology
computer programs designed to predict PK,
and optionally, pharmacodynamic effects of
drugs in humans and certain animals. The
underlying model in gastro plus™ is the ACAT
model, an improved version of the original
CAT model.

6. The ACAT model of the human GI tract consists of
nine compartments linked in series, each of them
representing a different segment of the GI tract
(stomach, duodenum, two jejunum compartments,
three ileum compartments, caecum, and ascending
colon).
These compartments are further subdivided to
comprise the drug that is unreleased, undissolved,
dissolved, and absorbed (entered into the enterocytes).
Movement of the drug between each sub-compartment
is described by a series of differential equations

7. The rate change of dissolved drug
concentration in each GI compartment
depends on ten processes.
• Transit of drug into the compartment.
• Transit of drug out of the compartment.
• Release of drug from the formulation into the
compartment.
• Dissolution of drug particles.
• Precipitation of drug.

8. • Lumenal degradation of drug.
• Absorption of drug into the enterocytes.
• Exsorption of drug from the enterocytes
back into the lumen.
• Absorption of drug into portal vein via
paracellular pathway.
• Exsorption of drug from portal vein via
paracellular pathway.

10. GI simulation: general modeling and
simulation strategy

11. GI simulation Model construction
• Modeling and simulation start from data
collection. Mechanistic absorption models
require a number of input parameters, which
can either be experimentally determined or in
silico predicted. The common approach is to
use literature reported values as initial inputs.
• There is a number of examples in the literature
describing the use of GastroPlus™ to predict
the drug PK profile after oral administration.

12. GI simulation of Nimesulide oral
absorption
Parameters Model-1 Model-2
Molecular weight 308.31 308.31
LogD(pH7.4) 1.8 1.48
pKa 6.4 6.4
Human jejuna permeability 2.225x10 2.002x10
Dose(mg) 100 100
Dose volume(ml) 200 200
Solubility at pH 4.5(mg/ml) 0.007 0.030
Mean precipitation time(s) 900 900
Diffusion coefficient(cm/s) 0.757x10 0.757x10
Drug particle density(g/ml) 1.2 1.2
Effective particle radius(µm) 5 25
Body weight 88 88
First pass extraction (FPE)in liver(%) 0.1 0.1
Blood /plasma conc.ration 0.668 1
Unbound percent plasma (%) 4.513 3
Cl(L/h/kg) 0.039 0.028
Vc(L/kf) 0.226 0.14
Elimination half-life ta/a(h) 15 15
Dosage form IR tablet IR suspension/IR tablet

13. ASF values employed
Parameters Model-1 Model-2
Stomach 0 0
Dueodenum 1000 2.687
Jejunum 1 500 2.668
Jejunum 2 2.600 2.633
Ileum 1 0.500 2.588
Ileum 2 0.500 2.551
Caecum 6.098 1.328
Asc colon 12.240 1.995

14. Comparison of PK parameters between
Model 1 and Model 2 predicted and in vivo
observed data
Parameters Model-1 Model-2
Observed Simulated % PE Simulated %PE
Cmax(µg/ml) 3.19 3.21 -0.63 3.39 -6.16
Tmax(h) 4.00 3.15 21.25 3.40 15.00
AUC 0-∞(µg h/ml) 25.78 25.96 -0.70 25.69 0.35
AUC 0-t(µg h/ml) 30.96 29.10 -6.01 27.92 9.82
%PE-Percent prediction error

15. • Model 1 outcomes indicated involvement of
influx transporters in nimesulide absorption,
while according to the Model 2 outcomes, the
pH-surfactant induced increase in drug solubility
was a predominant factor leading to relatively
rapid absorption in the proximal intestine.
• It should be noted that the model 2 assumption
was supported by the concept of
biopharmaceutics. Drug disposition classification
system (BDCCS), according to which BCS class
II drugs are not expected to be substrates for
influx transporters.

16. • In addition, parameters for which accurate data
were not available (i.e. In vivo solubility and
human jejunal permeability) were optimized in
model 2.
• Also, model 2 was developed using the set of in
vivo data for two dosage forms (oral suspension
and ir tablet), and revealed incomplete drug
absorption from the ir tablet (∼70% of the
administered dose, as compared to almost 100%
drug absorbed estimated for the same set of in
vivo data when model 1 was applied).

17. • This finding indicated that nimesulide dissolution
from IR tablets is expected to be the limiting
factor for drug absorption.
• Overall, the described independent procedures to
build a nimesulide specific absorption model
illustrated the importance of understanding
complex interplay between drug physicochemical
and pk properties, formulation factors, and
human physiology characteristics, in order to
predict drug pk profile in vivo.

18. • Interpretation of the obtained data indicated that
the approach applied in model 2 might be
considered as more realistic, signifying that the
related absorption model more likely reflects
nimesulide in vivo absorption.
• It was also stressed that, in order to obtain
meaningful in silico modeling, the necessary
input data have to be carefully selected and/or
experimentally verified.

19. THANK YOU