Resources

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Burnett G R et al. (2002). Interaction between protein allergens and model gastric emulsions. Biochem Soc Trans; 30(Pt 6): 916-918. https://doi.org/10.1042/bst0300916 

Marciani LG et al. (2001). Effect of meal viscosity and nutrients on satiety, intragastric dilution, and emptying assessed by MRI. American Journal of Physiology-Gastrointestinal and Liver Physiology, 280(6), G1227–G1233. https://doi.org/10.1152/ajpgi.2001.280.6.g1227

Wickham M J S et al. (2012). The Design, Operation, and Application of a Dynamic Gastric Model. Dissolution Technologies; 19(3): 15-22. https://doi.org/10.14227/DT190312P15

Butler J et al. (2019). In vitro models for the prediction of in vivo performance of oral dosage forms: Recent progress from partnership through the IMI OrBiTo collaboration. Eur J Pharm Biopharm; 136: 70-83. https://doi.org/10.1016/j.ejpb.2018.12.010 

Chessa S et al. (2014). Application of the Dynamic Gastric Model to evaluate the effect of food on the drug release characteristics of a hydrophilic matrix formulation. Int J Pharm; 466(1-2): 359-367. https://doi.org/10.1016/j.ijpharm.2014.03.031

This study assessed the suitability of the Dynamic Gastric Model for studying food effect on a hydrophilic matrix formulation in comparison with the conventional USP dissolution methodology. Dissolution data measured with the compendial methods indicated the HCTZ tablet was not sensitive to food-effect, whereas the Dynamic Gastric Model detected changes in physical properties and drug release performance. 

Mercuri A et al. (2011). The effect of composition and gastric conditions on the self-emulsification process of ibuprofen-loaded self-emulsifying drug delivery systems: a microscopic and dynamic gastric model study. Pharm Res; 28(7): 1540-1551. https://doi.org/10.1007/s11095-011-0387-8

This study investigated the link between formulation of self-emulsifying drug delivery systems (SEDDS) and the emulsification process in the human stomach using the Dynamic Gastric Model and the USP Dissolution Apparatus II. Samples from the Dynamic Gastric Model showed particle size remained broadly similar for both the drug and placebo. Results from the USP show a larger droplet size compared to the Dynamic Gastric Model, suggesting the mechanical agitation is important in determining size. 

Mercuri A et al. (2009). Assessing drug release and dissolution in the stomach by means of Dynamic Gastric Model: a biorelevant approach. J Pharm Pharmacol; 61 Supplement 1: A-5 

Mercuri A et al. (2008). Dynamic gastric model (DGM): a novel in vitro apparatus to assess the impact of gastric digestion on the droplet size of self-emulsifying drug-delivery systems. J Pharm Pharmacol; 60 Supplement 1: A-2 

Vardakou M et al. (2011). Achieving antral grinding forces in biorelevant in vitro models: comparing the USP dissolution apparatus II and the dynamic gastric model with human in vivo data. AAPS PharmSciTech; 12(2): 620-626. https://doi.org/10.1208/s12249-011-9616-z

This study assessed grinding forces of the Dynamic Gastric Model and Dissolution Apparatus USP-II with the breakdown of agar gel beads. Result suggested the Dynamic Gastric Model can simulate the gastric forces, while the Dissolution Apparatus USP-II failed to produce breaking forces.

Vardakou M et al. (2011). Predicting the human in vivo performance of different oral capsule shell types using a novel in vitro dynamic gastric model. Int J Pharm; 419(1-2): 192-199. https://doi.org/10.1016/j.ijpharm.2011.07.046

This study compared the use of the Dynamic Gastric Model with the USP dissolution apparatus to compare different capsule formulations of paracetamol. Results were then compared with in vivo gamma scintigraphy human data and gastric emptying profiles. Rupture times of all capsules and gastric emptying profiles measured by the Dynamic Gastric Model in fasted state aligned with in vivo gamma scintigraphy and plasma profiling.

Ballance S et al. (2013). Evaluation of gastric processing and duodenal digestion of starch in six cereal meals on the associated glycaemic response using an adult fasted dynamic gastric model. Eur J Nutr; 52(2): 799-812. https://doi.org/10.1007/s00394-012-0386-5 

This study investigated cereal starch digestion and glycaemic response using the Dynamic gastric Model. A range of grains were processed and fed into the Dynamic Gastric Model with water. Results found no significant difference in glycaemic index values from this in vitro model compared to in vivo data. 

Edwards C H et al. (2021). Structure-function studies of chickpea and durum wheat uncover mechanisms by which cell wall properties influence starch bioaccessibility. Nat Food; 2: 118-126. https://doi.org/10.1038/s43016-021-00230-y 

Grassby T et al. (2017). In vitro and in vivo modeling of lipid bioaccessibility and digestion from almond muffins: The importance of the cell-wall barrier mechanism. Journal of Functional Foods; 37: 263–271. https://doi.org/10.1016/j.jff.2017.07.046 

Lo Curto A et al. (2011). Survival of probiotic lactobacilli in the upper gastrointestinal tract using an in vitro gastric model of digestion. Food Microbiology; 28(7): 1359-1366. https://doi.org/10.1016/j.fm.2011.06.007 

This study investigated the survival of probiotic Lactobacillus strains in the upper gastrointestinal tract, using the Dynamic Gastric Model. The model was fed the bacteria resuspended in water or milk. Results showed survival of the probiotic strains after in vitro digestion, with a higher survival in milk compared to water. 

Mandalari G et al. (2018). Understanding the Effect of Particle Size and Processing on Almond Lipid Bioaccessibility through Microstructural Analysis: From Mastication to Faecal Collection. Nutrients; 10(2): 213. https://doi.org/10.3390/nu10020213 

Mandalari G et al. (2018 Epub 2016). Durum wheat particle size affects starch and protein digestion in vitro. Eur J Nutr; 57(1): 319-325. https://doi.org/10.1007/s00394-016-1321-y 

Mandalari G et al. (2016). The effect of sun-dried raisins (Vitis vinifera L.) on the in vitro composition of the gut microbiota. Food & Function; 7: 4048-4060. https://doi.org/10.1039/c6fo01137c 

Mandalari G et al. (2013). Bioaccessibility of pistachio polyphenols, xanthophylls, and tocopherols during simulated human digestion. Nutrition; 29(1): 338-44. https://doi.org/10.1016/j.nut.2012.08.004 

This study investigated polyphenol, xanthophylls (lutein), and tocopherols from various preparations of pistachios during digestion with the Dynamic Gastric Model. Raw pistachios and roasted, salted pistachios were masticated and fed into the Dynamic Gastric Model for digestion. Samples were then processed with duodenal digestion and followed by analysis. Results showed the bioactives become accessible in the stomach, increasing the potential for absorption in the intestines.  

Mandalari G et al. (2008). Potential prebiotic properties of almond (Amygdalus communis L.) seeds. Appl Environ Microbiol; 74(14): 4264-4270. https://doi.org/10.1128/AEM.00739-08 

Marciani L et al. (2007). Enhancement of intragastric acid stability of a fat emulsion meal delays gastric emptying and increases cholecystokinin release and gallbladder contraction. Am J Physiol Gastrointest Liver Physiol; 292(6): G1607-1613. https://doi.org/10.1152/ajpgi.00452.2006 

Mills CE et al. (2021). Palmitic acid-rich oils with and without interesterification lower postprandial lipemia and increase atherogenic lipoproteins compared with a MUFA-rich oil: A randomized controlled trial. Am J Clin Nutr; 113(5):1221-1231. https://doi.org/10.1093/ajcn/nqaa413 

Pitino L et al. (2011). Survival of Lactobacillus rhamnosus strains inoculated in cheese matrix during simulated human digestion. Food Microbiol; 28(7): 1359-66. https://doi.org/10.1016/j.fm.2012.02.013

This study used the Dynamic Gastric Model to investigate the survival of probiotic bacteria, previously isolated from Pecorino cheese, in the gastrointestinal tract. Strains of Lactobacillus were fed to the Dynamic Gastric Model within a model cheese, and monitored for survival. The Lactobacillus strains showed good survival after gastric digestions, with cheese working as an effective delivery system. 

Pitino I et al. (2010). Survival of Lactobacillus rhamnosus strains in the upper gastrointestinal tract. Food Microbiol; 27(8): 1121-1127. https://doi.org/10.1016/j.fm.2010.07.019

Rodes L et al. (2014). Enrichment of Bifidobacterium longum subsp. infantis ATCC 15697 within the human gut microbiota using alginate-poly-l-lysine-alginate microencapsulation oral delivery system: an in vitro analysis using a computer-controlled dynamic human gastrointestinal model. J Microencapsul; 31(3): 230-238. https://doi.org/10.3109/02652048.2013.834990 

Salt LJ et al. (2023). Mechanisms of interesterified fat digestibility in a muffin matrix using a dynamic gastric model. Food & Function, 14(22), 10232–10239. https://doi.org/10.1039/d3fo02963h

Thuenemann EC et al. (2015). Dynamic Gastric Model (DGM). In: Verhoeckx K et al (eds). The Impact of Food Bioactives on Health: in vitro and ex vivo models [Internet]. Cham (CH): Springer; 2015. Chapter 6. https://doi.org/10.1007/978-3-319-16104-4_6 

Zhang Q et al. (2014). Differential digestion of human milk proteins in a simulated stomach model. J Proteome Res; 13(2): 1055-1064. https://doi.org/10.1021/pr401051u