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APS_v3

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APS_v3

  1. 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. 2. What is a food scientist doing at a pharmaceutical meeting? 2Together to the next level
  3. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

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