1. In-silico modelling of digestion
application examples in the food
industry and potential link to
pharmacokinetic modelling
George van Aken
Together to the next level
1

2. What is a food scientist doing at a
pharmaceutical meeting?
2Together to the next level

3. Purpose of this presentation
3Together to the next level
Simulation
model
developed for
FOOD
application
Possible
opportunity for
Pharmacological
application
My food
science
based story
Please give me YOUR feedback!!!

4. Interaction of food with the body
4Together to the next level
The food’s perspective:
The food is selected, masticated, digested,
absorbed and processed
The body’s perspective:
The body receives mechanical, nutrient
and pharmacological signals;
affected by
time of day, mood, stress, activity, …
The body adapts:
release of digestive fluids,
residence times,
absorptive capacity,
post-absorptive processing,
appetite

5. Potential Applications
Satiety
Hunger
Satisfaction
Obesity, Anorexia
Liking, Quick energy
Medical
conditions
What
does
food do
to the
body?
Glycemic
effect
Gut health
Intestinal microbiotics
Pathogen growth and survival
Bioavailability
of nutrients
and
pharmaceutic
als
Food allergies
and
intolerances
5Together to the next level
Insulin resistance
Sugar craving
Muscle protein accretion
Sugar types, starch types and modifications
Allergic to protein digestion fragments
(peanuts, nuts, egg),
Digestive insufficiency (threshold
levels dairy, chocolate, ingredients)
Muscle protein accretion
Glycation of poteins
Protection and targetted release,
Timed release
Gastric discomfort, bloating, impaired
digestion, gastrointestinal surgery,
hospital food, elderly, infant formula

6. Complexity handled by digestion physiology
modelling
• Tight functional coupling
between the digestive
organs
Goal: optimal absorption, blood sugar
homeostasis, and required food intake;
avoid spilling to the large intestine.
• Digestive processing varies
in response to the food
Mixing conditions, enzyme activities,
bile concentrations, gastric pH profile,
transit times, absorption rate.
6Together to the next level

7. In silico digestive physiology modelling
• Timing of meals and drinks
• Speed of consumption
• Proteins, sugar, fat, water, pH
• Other compounds together or
separate from meal
Input parameters:
diet timing and
properties
Output:
temporal
variations
• Gastric pressure
• Gastric pH
• Gastric emptying
• CCK, PYY, GLP-1, GIP
• Digestive enzyme activity
• Bile secretion
• Small intestinal pH
• Absorption
• GI transit
Hunger, fullness,
bloating, satiety,
reward
Timed release
Bioavailability
Physiology
literature
In vitro
measurements
Physiological variations
(infants, elderly, diseased)

8. Active in the current model: Bio-control of
• Gastric acidification
• Gastric emptying reacting on volume, solids, nutrients, osmolarity, duodenal pH
• Activities of digestive enzymes (lipases, proteases) in reaction to food.
• Absorption rates of fatty acids, aminoacids and small sugars per unit length of
small intestine, including competitive absorption
• Intestinal fluid release.
• Bile release
• Gut hormone release (CCK, PYY, GLP-1, GIP).
• Gastric pressure
• Small intestinal transit rate (Ileal brake)
• Fullness, hunger > desire to eat.
8Together to the next level

9. Mucus lining
(selective, diffusion)
Gastric
volume or
pressure
Fullness
In-silico digestion model
Together to the next level
Intake
(water,
protein,fat,
carbohydrate
as a function
of time)
Fundus
Corpus
Antrum Duodenum Jejunum 1
Jejunum 2
Jejunum 3 Ileum 1
Ileum 2
Ileum 5
Ileum 6 Colon
Ileum 3
Ileum 4
nutnut
nut
nut
nut
nut
nut
nut
nut
nut
pylorus
Nutrient
density in
chyme
Hunger
absorption
I-cells CCK
K-cells GIP
L-cells
PYY, GLP1
Bile,
Enzymes
Water flux
controlling
luminal/mucous
nutrient density
Michaelis-Menten kinetics:
absorption rate = 𝑉𝑚𝑎𝑥
𝑆
𝐾 𝑀+𝑆
,
S is a function of competition between
aminoacids, fatty acids and small sugars
Bile
absorbed
Degistive
fluids
• Similar compartimental setup as PKPD models
• Physiological regulation for fed state added
Total absorbable
nutrients in small
intestine

10. Mixed meals during 1 day
10Together to the next level
Volumes Solids in stomach
Pepsin activity
pH increases
towards colon
Variation in gastric pH is
meal-dependent
Fed state
and low
duodenal
pH inhibits
MMC
Much variation in composition and
timing between all compartments
Gastric emptying attempts to adjust
nutrient delivery to duodenum
Gastric fundus behaves as a
balloning reservoir
Solids are stored in the fundus and
transferred to the antrum for
processing and emptying
duodenum
Gastric tone determines gastric
fullness/bloating/discomfort
Digestive enzymes are released to
meet digestive needs

11. Application 1. Effect of gastric
processing on Fullness and Hunger
Phase separation in the stomach
11Together to the next level
5 % triolein, 1 % WPI,
1 % caseinate
Control meal:
Yoghurt with emulsified fat
Active meal:
Yoghurt with grated cheese
Similar nutrient composition
and energy content
In collaboration with IFR: Mackie, A.R., Rafiee, H., Malcolm, P., Salt, L., van Aken, G.A., Specific
structuring of food emulsions leads to increased satiation and hunger suppression. Am. J. Physiol.
Gastrointestinal and Liver physiology (2013), 304, G1038-G1043.
Phase separation in the stomach

12. Main assumptions for predicting Fullness
and Hunger
• Fullness building up during the meal relates to gastric
distension and pressure.
• leads to meal ending.
• Hunger suppression relates to the detection of calories by
the intestinal enereocytes.
• Hunger leads to a desire to eat.
• Low blood sugar.
• Feeling weak, urge to eat.
• Sugar craving, altered in the obese/diabetic states.
12Together to the next level

13. simulated
Experimental data versus simulation
simulated
-8,00
-6,00
-4,00
-2,00
0,00
2,00
4,00
6,00
8,00
-50,00 0,00 50,00 100,00 150,00 200,00 250,00
Time after meal (minutes)
Change in Hunger
Active
Control
simulated
-4,00
-2,00
0,00
2,00
4,00
6,00
8,00
10,00
-50,00 0,00 50,00 100,00 150,00 200,00 250,00
Time after meal (minutes)
Change in Fullness
Active
Control
simulated

14. Link to pharmacokinetic modelling
Compared to most pharmakinetic models, the FED STATE is
described in much more detail
Would the pharmaceutical sector favour from a
much better simulation of the FED STATE in
pharmaco kinetic modeling?
Think of:
• Residence time and pH in the stomach
• Variation in intestinal transit rate
• pH variation in small intestine
• Meal-dependent release of bile
• Compositional variation in small intestin (digestion/absorption of water,
fat, lipids, carbohydrates, proteins, peptides, digestive enzymes)
• Gastrintestinal discomfort (nausea, constipation) and weight gain from
using antidepressants
14Together to the next level

15. Application 2. Protein utilization for muscle
mass maintainance and accretion
15Together to the next level
IN-SILICO MODELING OF PROTEIN DIGESTION AND
AMINO ACID ABSORPTION
Eat2Move
sporters
elderly

16. Key aspects of muscle protein
maintainance and increase
16Together to the next level
Muscle protein increase = MPS ─ MPB
Insulin Essential amino
acids; particularly
LEUCINE
Excercise
Blood amino
acid
homeostasis
Glucose
neogenesis
Muscle protein
renewal
Relatively constant
mTORC-1
→
protein effectors
Insulin
resistance
Sarcopenia
Old age,
Obese

17. Synergism of protein ingestion and
excercise
17Together to the next level
Tyler A Churchward-Venne,Nicholas A Burd, and Stuart M
Phillips, Nutr Metab (Lond). 2012; 9: 40
exercise
Excercise
increases MPS
Synergystic
effect of protein
and excercise

18. Appearance of Leucine in the blood plasma.
18Together to the next level
Experimental work in publications
by Dangin 2001, 2002 and 2003
Appearance of exogenous Leucine
P L
L
L
L
P
L
L
whey
casein
Whey,
casein
Slow protein
(Casein)
Fast protein
(whey)
Skeletal muscle growth is
stimulated by high peak-levels
of Leucine

19. In development: glucose homeostasis
• To predict the glyceamic effect for foods and meals. Aim to prevent
peaks in blood glucose levels, which increases the risk of
development Diabetes 2 and Metabolic syndrome)
• Highly relevant for Muscle mass maintainance and accretion,
Metabolic syndrome, sugar craving, …
• Modelled Insulin and Glucagone release and activity to regulate
homeostasis of blood glucose, amino-acid and fat metabolism
19Together to the next level
3 levels:
1.Subcellular β-cells (so far insuline only)
2.Pancreas and body
3.Include digestive system

20. Level 1: subcellular
Glucose-stimulated Insulin release by pancreatic β-cells
20Together to the next level
-cell
class
G*
Based on: Pedersen et al, Phil. Trans. R. Soc. A (2008)
Storage pool
Intermediate pool Rapidly releasing
pool “docked”
Granule formation
β-cells for
which
G* > G
Transportto
cell wall
Anchoring to
cell wall
β-cells for
which
G* < G Storage pool
Intermediate pool Rapidly releasing
pool “docked”
Fused
Bounced
Released
Granule formation
Transport to
cell wall
Anchoring to
cell wall
Rupture
 Spectrum of thresshold values G* for glucose concentrations in the pool β-cells

21. Level 1: simulation result
• Insulin release after a step-wise increase in blood sugar
concentration from 0 to 500 mg/dl (= 0 to 27.8 mmol/l)
21Together to the next level
Insulin:
1 µg = 25.8 mU
Biphasic insulin release

22. Level 2: Regulation of blood serum glucose
Balance of entry and utilization of glucose
22Together to the next level
Adapted from Toliċ at al. J. Theor. Biol. (2000)
Serum glucose
Serum Insulin
intravenous
brain Muscle
and
adipose
liver
neogenesis
Interstitial fluids
+
Insulin decay
̶̶
+
Level 1
β-cell

23. Level 2: Simulation result
intravenous bolus of 20 g glucose
• First phase insulin release almost invisible
• Single peek in blood sugar level
23Together to the next level
5.56 mmol/l
16.7 mmol/l
insulin glucose

24. Mucus lining
(selective, diffusion)
Gastric
volume or
pressure
Fullness
Level 3:
couple to digestion model: use nutrient absorption and
incretin hormone release to calculate blood sugar response
Together to the next level
Intake
(water,
protein,fat,
carbohydrate
as a function
of time)
Fundus
Corpus
Antrum Duodenum Jejunum 1
Jejunum 2
Jejunum 3 Ileum 1
Ileum 2
Ileum 5
Ileum 6 Colon
Ileum 3
Ileum 4
nutnut
nut
nut
nut
nut
nut
nut
nut
A
nut
pylorus
Nutrient
density in
chyme
Hunger
absorption
I-cells CCK
K-cells GIP
L-cells
PYY, GLP1
Total absorbable
nutrients
Bile,
Enzymes
Water flux
controlling
luminal
nutrient
density
Michaelis-Menten kinetics:
absorption rate = 𝑉𝑚𝑎𝑥
𝑆
𝐾 𝑀+𝑆
,
S is a function of competition between
aminoacids, fatty acids and small sugars
Bile
absorbed
Degistive
fluids
Stimulated insulin secretion
Reduced glucagon secretion
• Avoid high blood sugar levels
• Promote usage or storage of nutrients
Glucose,
Free fatty
acids,
Branched
chain
aminoacids
Level 2 + Level 1 model
Amplify the
stimulated
Insulin secretion

25. Level 3: simulation result
2 food bolusses of 20 g glucose
in 400 and 0 ml water, respectively
25Together to the next level
Incretin effect from GIP and
GLP-1 turned off
5.56 mmol/l
11.11 mmol/l
5.56 mmol/l
11.11 mmol/l
Incretin effect from GIP and
GLP-1 turned on
normal
5.56 mmol/l
11.11 mmol/l
Incretin effect from GIP and
GLP-1 turned on
DIABETIC (reduced glucose sensitivity)
diabetic
Extended
high blood
glucose
HYPO
(glucogon effect
not yet included)

26. Link to pharmacokinetic modelling
Insulin and glucose blood levels are of pharmaceutical
relevance and depend on the fed state.
Many diseases (diabetes, metabolic syndrom,
atherosclerosis, gout) relate to nutrient status, inflammatory
status (unfolded proteins in endoplasmatic reticulum, …).
Would the pharmaceutical sector favour from a
much better simulation of the FED STATE
coupled to sysemic and cell biological modelling?
Think of:
• Using a more detailed cellular model of Insulin/Glucagon release
• Adaptations to diseased situations
26Together to the next level

27. Future Development and
Applications
27Together to the next level
Introduce and further
develop this aproach
for PKPD modelling?
Connection to other
Pharmaceutical
developments?
Connect with system
biological models
using SBML?

28. 28Together to the next level
Together to the next level
Creating the future together
www.nizo.com
george.vanaken@nizo.com
www.insightfoodinside.com
info@insightfoodinside.com