Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network

Bellmann, Susann; Krishnan, Shaji; Graaf, A. De; Ligt, Rianne A. de; Pasman, Wilrike J.; Minekus, Mans; Havenaar, R.

doi:10.1016/j.foodres.2019.03.051

Cited by 19 publications

(11 citation statements)

References 40 publications

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“…This mixed type approach has also been used to predict appetite responses to foods based on gastric rheology combined with amino acid and glucose absorption. 199 The researchers used an artificial neural network approach with a number of training sets to build the predictive capacity and link the in vitro measures to human participant visual analogue scale scores for fullness and hunger. Although this area of modelling is still in its infancy, it is clear that developments in CFD and artificial intelligence approaches have the potential to make in silico models powerful predictive tools with the ability to predict physiological responses to foods.…”

Section: In Silico Models Of Digestionmentioning

confidence: 99%

Simulating human digestion: developing our knowledge to create healthier and more sustainable foods

2020

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Section: In Silico Models Of Digestionmentioning

confidence: 99%

Simulating human digestion: developing our knowledge to create healthier and more sustainable foods

2020

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“…The TIM system developed at TNO Nutrition and Food Research (Zeist, the Netherlands) induced contractions by alternating water pressure on flexible silica walls. Several models of the TIM system are available for different application purposes, that is, TIM-1 for the upper GI tract (Minekus et al, 1995), TinyTIM for high throughput trials with a simplified configuration of the upper GI tract (Verwei et al, 2016), TIM-2 for the colon, and TIMagc for the stomach only (Bellmann et al, 2016(Bellmann et al, , 2019. Additionally, the TIM system can be adjusted to simulate different life stages (such as infant, adult, and elderly) and various physiological or pathological conditions (such as gastric hyperacidity or pancreatic failure) (Venema et al, 2019).…”

Section: Hydraulic Systemmentioning

confidence: 99%

Simulating human gastrointestinal motility in dynamic in vitro models

Kong

2022

Comp Rev Food Sci Food Safe

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The application of dynamic in vitro gastrointestinal (GI) models has grown in popularity to understand the impact of food structure and composition on human health. Given that GI motility is integral to digestion and absorption, a predictive in vitro model should faithfully replicate the motility patterns and motor functions in vivo. In this review, typical characteristics of gastric and small intestinal motility in humans as well as the biomechanical and hydrodynamic events pertinent to gut motility are summarized. The simulation of GI motility in the presently existing dynamic in vitro models is discussed from an engineering perspective and categorized into hydraulic, piston/probe‐driven, roller‐driven, pneumatic, and other systems. Each system and its representative models are evaluated in terms of their motility patterns, the key hydrodynamic characteristics concerning gut motility, their performance in simulating the key physiological events, and their ability to establish in vitro–in vivo correlations. Practical Application: The review paper provided useful information in the design of dynamic GI models and the simulation of human gastric and small intestinal motility which are important for understanding food and health.

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“…71 Later studies showed that it is possible to develop specific in silico modeling with TIM-1 or tiny-TIM digestion and bioaccessibility data as input for prediction of the glycemic response and appetite rating. 73,74 For the development and calibration of these in silico models the in vivo data of a limited number of products were used. After calibration the TIM data of the different food products were used as input.…”

Section: Tim Systems In Combination With In Silico Modelingmentioning

confidence: 99%

“…73 The prediction for human satiation and satiety after meal intake was good, but most likely can be improved by using more TIM digestion parameters. 74 The first pharma TIM-1-in silico study has been published by Naylor et al 75 The TIM-1 bioaccessibility versus time data for paroxitine-HCl were used as input in GastroPlus. The predicted plasma concentration curves were similar to the clinical data.…”

Section: Tim Systems In Combination With In Silico Modelingmentioning

confidence: 99%

Results from a Validated in vitro Gastrointestinal Model (TIM) used as input Data for in silico Modeling Give Highly Predictive Information for the Human Situation

Havenaar¹,

Bellmann

2022

MRAJ

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The aim of this review paper is to evaluate the predictive quality of a combination of in vitro dynamic gastrointestinal models, mucosal transit models and in silico kinetic modeling. The TNO gastro-Intestinal Model (TIM) is a computer-controlled system, mimicking essential gastrointestinal parameters of the stomach, small intestine and large intestine. The systems have dialysis or filtration units connected to the intestinal compartments. TIM settings are adapted to the condition that has to be simulated, such as fasted and fed state, age, and co-medication. In this way the transit and digestibility of food, release, dissolution, and bioaccessibility of nutrients, drugs, and metabolites can be studied. The TIM Systems have been validated in comparison to human studies for various food products and oral drugs, published in peer-reviewed journals. The results show the potential availability for absorption, called 'bioaccessibility'. Combining TIM with mucosal transit assays, it is possible to also analyze the intestinal absorption. But for predicting bioavailability and plasma concentrations in time it needs additional kinetic data, such as distribution, metabolism, and excretion. TIM bioaccessibility data and (published) kinetic data can be used as input in commercial in silico models or specifically developed in silico modeling. Validation studies show a high predictive quality for human nutrient and drug bioavailability and plasma concentrations. Maybe not (yet) in all cases the predictions will cover for 100% the human data, so there is room for improvement. However, the reviewed studies clearly show the strength of combining a validated gastrointestinal model with physiological kinetic data in in silico modeling. It certainly will replace animal experiments and will strongly increase the success rate of follow-up human studies, saving time and costs.

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Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network

Cited by 19 publications

References 40 publications

Simulating human digestion: developing our knowledge to create healthier and more sustainable foods

Simulating human digestion: developing our knowledge to create healthier and more sustainable foods

Simulating human gastrointestinal motility in dynamic in vitro models

Results from a Validated in vitro Gastrointestinal Model (TIM) used as input Data for in silico Modeling Give Highly Predictive Information for the Human Situation

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