Use of Physiologically Based Kinetic Modeling-Based Reverse Dosimetry to Predict In Vivo Nrf2 Activation by EGCG and Its Colonic Metabolites in Humans

Use of physiologically based kinetic modeling to predict neurotoxicity and genotoxicity of methylglyoxal in humans

This study aimed to evaluate human neurotoxicity and genotoxicity risks from dietary and endogenous methylglyoxal (MGO), utilizing physiologically based kinetic (PBK) modeling-facilitated reverse dosimetry as a new approach methodology (NAM) to extrapolate in vitro toxicity data to in vivo dose-response predictions. A human PBK model was defined based on a newly developed and evaluated mouse model enabling the translation of in vitro toxicity data for MGO from human stem cell-derived neurons and WM-266-4 melanoma cells into quantitative human in vivo toxicity data and subsequent risk assessment by the margin of exposure (MOE) approach. The results show that the MOEs resulting from daily dietary intake did not raise a concern for endpoints for neurotoxicity including mitochondrial function, cytotoxicity, and apoptosis, while those for DNA adduct formation could not exclude a concern over genotoxicity. Endogenous MGO formation, especially under diabetic conditions, resulted in MOEs that raised concern not only for genotoxicity but also for some of the neurotoxicity endpoints evaluated. Thus, the results also point to the importance of taking the endogenous levels into account in the risk assessment of MGO.

Physiologically based kinetic (PBK) modeling as a new approach methodology (NAM) for predicting systemic levels of gut microbial metabolites

There is a clear need to develop new approach methodologies (NAMs) that combine in vitro and in silico testing to reduce and replace animal use in chemical risk assessment. Physiologically based kinetic (PBK) models are gaining popularity as NAMs in toxico/pharmacokinetics, but their coverage of complex metabolic pathways occurring in the gut are incomplete. Chemical modification of xenobiotics by the gut microbiome plays a critical role in the host response, for example, by prolonging exposure to harmful metabolites, but there is not a comprehensive approach to quantify this impact on human health. There are examples of PBK models that have implemented gut microbial biotransformation of xenobiotics with the gut as a dedicated metabolic compartment. However, the integration of microbial metabolism and parameterization of PBK models is not standardized and has only been applied to a few chemical transformations. A challenge in this area is the measurement of microbial metabolic kinetics, for which different fermentation approaches are used. Without a standardized method to measure gut microbial metabolism ex vivo/in vitro, the kinetic constants obtained will lead to conflicting conclusions drawn from model predictions. Nevertheless, there are specific cases where PBK models accurately predict systemic concentrations of gut microbial metabolites, offering potential solutions to the challenges outlined above. This review focuses on models that integrate gut microbial bioconversions and use ex vivo/in vitro methods to quantify metabolic constants that accurately represent in vivo conditions.

Use of Physiologically Based Kinetic Modeling to Predict Deoxynivalenol Metabolism and Its Role in Intestinal Inflammation and Bile Acid Kinetics in Humans

Current points of departure used to derive health-based guidance values for deoxynivalenol (DON) are based on studies in laboratory animals. Here, an animal-free testing approach was adopted in which a reverse dosimetry physiologically based kinetic (PBK) modeling is used to predict in vivo dose response curves for DON's effects on intestinal pro-inflammatory cytokine secretion and intestinal bile acid reabsorption in humans from concentration-effect relationships for DON in vitro. The calculated doses for inducing a 5% added effect above the background level (ED5) of DON for increasing IL-1β secretion in intestinal tissue and for increasing the amounts in the colon lumen of glycochenodeoxycholic acid (GCDCA) were 246 and 36 μg/kg bw/day, respectively. These in vitro-in silico-derived ED5 values were compared to human dietary DON exposure levels, indicating that the risk of DON's effects on these end points occurring in various human populations cannot be excluded. This in vitro-in silico approach provides a novel testing strategy for hazard and risk assessment without using laboratory animals.