A Simple, Realistic Stochastic Model of Gastric Emptying

A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth

Alcohol consumption is associated with a wide variety of preventable health complications and is a major risk factor for all-cause mortality in the age group 15-47 years. To reduce dangerous drinking behavior, eHealth applications have shown promise. A particularly interesting potential lies in the combination of eHealth apps with mathematical models. However, existing mathematical models do not consider real-life situations, such as combined intake of meals and beverages, and do not connect drinking to clinical markers, such as phosphatidylethanol (PEth). Herein, we present such a model which can simulate real-life situations and connect drinking to long-term markers. The new model can accurately describe both estimation data according to a χ2 -test (187.0 < Tχ2 = 226.4) and independent validation data (70.8 < Tχ2 = 93.5). The model can also be personalized using anthropometric data from a specific individual and can thus be used as a physiologically-based digital twin. This twin is also able to connect short-term consumption of alcohol to the long-term dynamics of PEth levels in the blood, a clinical biomarker of alcohol consumption. Here we illustrate how connecting short-term consumption to long-term markers allows for a new way to determine patient alcohol consumption from measured PEth levels. An additional use case of the twin could include the combined evaluation of patient-reported AUDIT forms and measured PEth levels. Finally, we integrated the new model into an eHealth application, which could help guide individual users or clinicians to help reduce dangerous drinking.

Physiological Dynamics in the Upper Gastrointestinal Tract and the Development of Gastrointestinal Absorption Models for the Immediate-Release Oral Dosage Forms in Healthy Adult Human

This review is a revisit of various oral drug absorption models developed in the past decades, focusing on how to incorporate the physiological dynamics in the upper gastrointestinal (GI) tract. For immediate-release oral drugs, GI absorption is a critical input of drug exposure and subsequent human body response, yet difficult to model largely due to the complex GI environment. One of the biggest hurdles lies at capturing the high within-subject variability (WSV) of bioavailability measures, which can be mechanistically explained by the GI physiological dynamics. A thorough summary of how GI dynamics is handled in the absorption models would promote the development of mechanism-based oral drug absorption models, aid in the design of clinical studies regarding dosing regimens and bioequivalence studies based on WSV, and advance the decision-making on formulation selection.

Stochastic Differential Equation-based Mixed Effects Model of the Fluid Volume in the Fasted Stomach in Healthy Adult Human

The rate and extent of drug dissolution and absorption from a solid oral dosage form depend largely on the fluid volume along the gastrointestinal tract. Hence, a model built upon the gastric fluid volume profiles can help to predict drug dissolution and subsequent absorption. To capture the great inter- and intra-individual variability (IAV) of the gastric fluid volume in fasted human, a stochastic differential equation (SDE)-based mixed effects model was developed and compared with the ordinary differential equation (ODE)-based model. Twelve fasted healthy adult subjects were enrolled and had their gastric fluid volume measured before and after consumption of 240 mL of water at pre-determined intervals for up to 2 hours post ingestion. The SDE- and ODE-based mixed effects models were implemented and compared using extended Kalman filter algorithm via NONMEM. The SDE approach greatly improved the goodness of fit compared with the ODE counterpart. The proportional and additive measurement error of the final SDE model decreased from 14.4 to 4.10% and from 17.6 to 4.74 mL, respectively. The SDE-based mixed effects model successfully characterized the gastric volume profiles in the fasted healthy subjects, and provided a robust approximation of the physiological parameters in the very dynamic system. The remarkable IAV could be further separated into system dynamics terms and measurement error terms in the SDE model instead of only empirically attributing IAV to measurement errors in the traditional ODE method. The system dynamics were best captured by the random fluctuations of gastric emptying coefficient Kge.

Cross Effects of Diets and Rearing Temperatures on Gastrointestinal Evacuation and Growth Performance in Adult Sabah Groupers (Epinephelus fuscoguttatus × E. lanceolatus)

This study explores the gastrointestinal evacuation time (GET) and gastrointestinal evacuation rate (GER) of the popular Sabah grouper (Epinephelus fuscoguttatus × E. lanceolatus) adults using two established methods (X-radiography and serial slaughter) and square root modeling using different temperatures: 28 °C, 30 °C, 32 °C, and 34 °C and different diets: pellet (ash: 11.4 ± 0.08; moisture: 29.0 ± 0.01; protein 37.5 ± 0.80; lipid 15.0 ± 0.13) and trash fish: Sardinella sp. (ash: 2.3 ± 0.15; moisture: 78.5 ± 0.33; protein 55.4 ± 0.62; lipid 7.3 ± 0.25) and the impact on growth indices. The results indicate that the GET shortened as temperature increased from 28 °C to 30 °C; however, it was prolonged when it surged to 32 °C and 34 °C. The groupers fed with trash fish at a temperature of 30 °C had the shortest GER (0.41 ± 0.10 g hr^-1) whereas groupers fed with pellet at 34 °C had the longest GER (0.95 ± 0.02 g hr^-1). Likewise, the highest SGR (16.25 ± 2.11% day^-1) was observed at 30 °C for groupers fed with a trash fish diet. The condition (K) value was lowest at 34 °C for groupers fed with a pellet diet (1.01 ± 0.04) and highest at 30 °C for groupers fed with trash fish (1.45 ± 0.04). Our results suggest that temperature and diet influence growth indices and GE of adult Sabah groupers. Incorporation of this information will allow better management of this commercially important grouper species when reared in a controlled aquaculture environment.

Lilly Absorption Modeling Platform: A Tool for Early Absorption Assessment

Oral drug absorption modeling has developed at a rapid pace in the 40 years or so since the first ideas for mathematical approaches to oral absorption were introduced. The success of compartmental approaches accelerated the uptake of absorption modeling, and over the last 20 years, work on absorption modeling has shifted almost exclusively to the compartmental framework. This report describes a new noncompartmental absorption modeling framework, the Lilly Absorption Modeling Platform (LAMP). LAMP connects a well-mixed stomach to a continuous tube model of the small intestine with plug flow. Within the continuous tube framework, the model includes intestinal mixing and a novel highly tunable precipitation model that can describe a combination of rapid nucleation and slow growth. The framework is designed to balance speed, consistency, and ease of use with a minimum of model complexity to capture the essential features of gastrointestinal (GI) physiology and critical elements of the oral absorption process. The model was validated based on predictions of the fraction absorbed and the maximum absorbable dose for a set of Eli Lilly and Company clinical compounds.

In-vitro digestion models: a critical review for human and fish and a protocol for in-vitro digestion in fish

Digestive systems in human, animals, and fish are biological reactors and membranes to digest food and extract nutrients. Therefore, static and dynamic models of in-vitro digestion systems are developed to study e.g. novel food and feed before in-vivo studies. Such models are well developed for human, but not to the same extent for animals and fish. On the other hand, recent advances in aquaculture nutrition have created several potential fish meal replacements, and the assessment of their nutrient digestibility is critical in the application as a fish meal replacement. Using an in-vitro method, the assessment of an ingredient digestibility could be faster and less expensive compared to using an in-vivo experiment. An in-vitro method has been widely used to assess food nutrient digestibility for humans; however, its application for fish is still in the early stages. Both the human and fish as monogastric vertebrates share similar gastrointestinal systems; thus, the concept from the application for humans could be applied for fish. This review aims to improve the in-vitro digestion protocol for fish by adapting the concept from then study for humans, summarizing the current available in-vitro digestion model developed for human and fish in-vitro digestion study, identifying challenges specifically for fish required to be tackled and suggesting an engineering approach to adapt the human in-vitro gastrointestinal model to fish. Protocols to conduct in-vitro digestion study for fish are then proposed.

PARAMETER ESTIMATION OF A SIMPLE, REALISTIC STOCHASTIC MODEL OF GASTRIC EMPTYING OF PELLETS UNDER FASTING CONDITIONS

This study is aimed to develop a parameter estimation procedure for a stochastic model of gastric emptying of pellets under fasting conditions of healthy subjects that represent the irregular decrements of gastric contents after administration of pellets. An algorithm for the identification of experimental subjects into subgroups based on their gastric emptying rates has been proposed. The parameter estimation procedure was performed with observational data of gastric emptying profiles of 19 subjects from the existing literature. The identification algorithm was validated through comparison against the original results, showing that seven subjects indicated slow gastric emptying and 12 subjects indicated fast emptying. After excluding one subject with gastric stasis, the optimal results obtained from this study classified subjects into three subgroups: two subjects with slow, five subjects with intermediate and 11 subjects with fast gastric emptying. The proposed parameter estimation procedure of the stochastic model is relatively easy to implement and can be used to analyze real patients’ data. The algorithm for identification of the gastric emptying dynamics in experimental subjects could provide useful information for further investigations of long-term energy balance forecasting.

Spirulina breath test indicates differences in gastric emptying based on age, gender, and BMI

BACKGROUND

Measurements of gastric emptying (GE) by scintigraphy in the pediatric population are based on adult standards. Due to radiation exposure, scintigraphy cannot be performed on healthy children to establish norms of GE in the pediatric population. Stable isotope breath tests (GEBTs) pose no such health risk to children. This study sought to determine the feasibility of a GEBT in children and to investigate whether GE may differ by age, gender, or body mass index (BMI).

METHODS

Fifty healthy children 6 to 18 years underwent a ¹³ C-Spirulina platensis GEBT. Breath samples were obtained at baseline, every 15 min for 1 h, and at 30-min intervals for 3 h thereafter. Seventeen similarly aged patients with dyspeptic symptoms concurrently underwent scintigraphy and the GEBT.

KEY RESULTS

Forty-six healthy subjects were included in the final analysis. Females had an overall slower rate of GE than did males. At nearly all timepoints, children with a BMI >85^th percentile had slower GE than normally weighted children. The GE rate of children aged 6-9 reached a maximum later than did the rate of older children. Thirteen patients undergoing scintigraphy were included in the comparative analysis. The agreement between scintigraphic and GEBT half-times as measured by the concordance correlation coefficient was 0.383 (95% CI: 0.02-0.65).

CONCLUSIONS AND INFERENCES

GEBT was easily accomplished in healthy children. Differences of GE rates by age, gender, and BMI support the need for establishing pediatric standards of GE. One way to establish such standards may be through the use of a GEBT.

Bayesian analysis of Glucose dynamics during the Oral Glucose Tolerance Test (OGTT)

This paper proposes a model that considers the action and timing of insulin and glucagon in glucose homeostasis after an oral stimulus. We use the Bayesian paradigm to infer kinetic rates, namely insulin and glucagon secretion, gastrointestinal emptying, and basal glucose concentration in blood. We identify two insulin scores related to glucose concentration in both blood and the gastrointestinal tract. The scores allow us to suggest a classification for individuals with impaired insulin sensitivity.

Strategies to Refine Gastric Stimulation and Pacing Protocols: Experimental and Modeling Approaches

Gastric pacing and stimulation strategies were first proposed in the 1960s to treat motility disorders. However, there has been relatively limited clinical translation of these techniques. Experimental investigations have been critical in advancing our understanding of the control mechanisms that innervate gut function. In this review, we will discuss the use of pacing to modulate the rhythmic slow wave conduction patterns generated by interstitial cells of Cajal in the gastric musculature. In addition, the use of gastric high-frequency stimulation methods that target nerves in the stomach to either inhibit or enhance stomach function will be discussed. Pacing and stimulation protocols to modulate gastric activity, effective parameters and limitations in the existing studies are summarized. Mathematical models are useful to understand complex and dynamic systems. A review of existing mathematical models and techniques that aim to help refine pacing and stimulation protocols are provided. Finally, some future directions and challenges that should be investigated are discussed.

Model-based data analysis of individual human postprandial plasma bile acid responses indicates a major role for the gallbladder and intestine

BACKGROUND

Bile acids are multifaceted metabolic compounds that signal to cholesterol, glucose, and lipid homeostasis via receptors like the Farnesoid X Receptor (FXR) and transmembrane Takeda G protein-coupled receptor 5 (TGR5). The postprandial increase in plasma bile acid concentrations is therefore a potential metabolic signal. However, this postprandial response has a high interindividual variability. Such variability may affect bile acid receptor activation.

METHODS

In this study, we analyzed the inter- and intraindividual variability of fasting and postprandial bile acid concentrations during three identical meals on separate days in eight healthy lean male subjects using a statistical and mathematical approach.

MAIN FINDINGS

The postprandial bile acid responses exhibited large interindividual and intraindividual variability. The individual mathematical models, which represent the enterohepatic circulation of bile acids in each subject, suggest that interindividual variability results from quantitative and qualitative differences of distal active uptake, colon transit, and microbial bile acid transformation. Conversely, intraindividual variations in gallbladder kinetics can explain intraindividual differences in the postprandial responses.

CONCLUSIONS

We conclude that there is considerable inter- and intraindividual variation in postprandial plasma bile acid levels. The presented personalized approach is a promising tool to identify unique characteristics of underlying physiological processes and can be applied to investigate bile acid metabolism in pathophysiological conditions.

A mathematical model of food intake

The metabolic, hormonal and psychological determinants of the feeding behavior in humans are numerous and complex. A plausible model of the initiation, continuation and cessation of meals taking into account the most relevant such determinants would be very useful in simulating food intake over hours to days, thus providing input into existing models of nutrient absorption and metabolism. In the present work, a meal model is proposed, incorporating stomach distension, glycemic variations, ghrelin dynamics, cultural habits and influences on the initiation and continuation of meals, reflecting a combination of hedonic and appetite components. Given a set of parameter values (portraying a single subject), the timing and size of meals are stochastic. The model parameters are calibrated so as to reflect established medical knowledge on data of food intake from the National Health and Nutrition Examination Survey (NHANES) database during years 2015 and 2016.

A quantitative model for metabolic intervention using gut microbes

As medicine shifts toward precision-based and personalized therapeutics, utilizing more complex biomolecules to treat increasingly difficult and rare conditions, microorganisms provide an avenue for realizing the production and processing necessary for novel drug pipelines. More so, probiotic microbes can be co-opted to deliver therapeutics by oral administration as living drugs, able to survive and safely transit the digestive tract. As living therapeutics are in their nascency, traditional pharmacokinetic-pharmacodynamic (PK-PD) models for evaluating drug candidates are not appropriate for this novel platform. Using a living therapeutic in late-stage clinical development for phenylketonuria (PKU) as a case study, we adapt traditional oral drug delivery models to properly evaluate and inform the engineering of living therapeutics. We develop the adapted for living therapeutics compartmental absorption and transit (ALT-CAT) model to provide metrics for drug efficacy across nine age groups of PKU patients and evaluate model parameters that are influenced by patient physiology, microbe selection and therapeutic production, and dosing formulations. In particular, the ALT-CAT model describes the mathematical framework to model the behavior of orally delivered engineered bacteria that act as living therapeutics by adapting similar methods that have been developed and widely-used for small molecular drug delivery and absorption.

A novel fast-slow model of diabetes progression: Insights into mechanisms of response to the interventions in the Diabetes Prevention Program

Several models for the long-term development of T2DM already exist, focusing on the dynamics of the interaction between glycemia, insulinemia and β-cell mass. Current models consider representative (fasting or daily average) glycemia and insulinemia as characterizing the compensation state of the subject at some instant in slow time. This implies that only these representative levels can be followed through time and that the role of fast glycemic oscillations is neglected. An improved model (DPM15) for the long-term progression of T2DM is proposed, introducing separate peripheral and hepatic (liver and kidney) insulin actions. The DPM15 model no longer uses near-equilibrium approximation to separate fast and slow time scales, but rather describes, at each step in slow time, a complete day in the life of the virtual subject in fast time. The model can thus represent both fasting and postprandial glycemic levels and describe the effect of interventions acting on insulin-enhanced tissue glucose disposal or on insulin-inhibited hepatic glucose output, as well as on insulin secretion and β-cell replicating ability. The model can simulate long-term variations of commonly used clinical indices (HOMA-B, HOMA-IR, insulinogenic index) as well as of Oral Glucose Tolerance or Euglycemic Hyperinsulinemic Clamp test results. The model has been calibrated against observational data from the Diabetes Prevention Program study: it shows good adaptation to observations as a function of very plausible values of the parameters describing the effect of such interventions as Placebo, Intensive LifeStyle and Metformin administration.

Predictive PBPK modeling as a tool in the formulation of the drug candidate TMP-001

Since many drugs in the therapy scheme of multiple sclerosis (MS) are applied parenterally with significant side effects, oral treatment is the most accepted therapy option for chronic diseases like MS. The drug candidate TMP-001, which has disease-modifying properties, can be applied orally. Beside other symptoms, swallowing disorders have a major impact not only on the health status and quality of life of MS patients, but also impede reliable drug therapy. Consequently, the development of an easy-to-swallow liquid oral dosage form supported by a combined PBPK-IVIVC model was approached. In this context, the impact of formulation parameters was studied. Biorelevant in vitro drug release studies resulted in an almost complete release of 96.91% ± 1.00% in the intestine which was translated to rapidly increasing in silico plasma profiles. The predictions were compared to the outcome of a phase I clinical trial. A partial parameter sensitivity analysis of the in silico model deepened our understanding of the physiological processes underlying human pharmacokinetics.