Physiology-based IVIVE predictions of tramadol from in vitro metabolism data

To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (SimcypA (R)). Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLint(H)) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution. Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis. IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults

The utility of HepG2 cells to identify direct mitochondrial dysfunction in the absence of cell death.

Drug-induced mitochondrial dysfunction has been hypothesized to be an important determining factor in the onset of drug-induced liver injury. It is essential to develop robust screens with which to identify drug-induced mitochondrial toxicity and to dissect its role in hepatotoxicity. In this study we have characterised a mechanistically refined HepG2 model, using a panel of selected hepatotoxicants and non-hepatotoxicants. We have demonstrated that acute metabolic modification, via glucose-deprivation over a 4 h period immediately prior to compound addition, is sufficient to allow the identification of drugs which induce mitochondrial dysfunction, in the absence of cell death over a short exposure (2 – 8 h) using a plate-based screen to measure cellular ATP content and cytotoxicity. These effects were verified by measuring changes in cellular respiration, via oxygen consumption and extracellular acidification rates. Overall, these studies demonstrate the utility of HepG2 cells for the identification of mitochondrial toxins which act directly on the electron transport chain and that the dual assessment of ATP content alongside cytotoxicity provides an enhanced mechanistic understanding of the causes of toxicity

Short-term supplementation of celecoxib-shifted butyrate production on a simulated model of the gut microbial ecosystem and ameliorated in vitro inflammation

Celecoxib has been effective in the prevention and treatment of chronic inflammatory disorders through inhibition of altered cyclooxygenase-2 (COX-2) pathways. Despite the benefits, continuous administration may increase risk of cardiovascular events. Understanding microbiome-drug-host interactions is fundamental for improving drug disposition and safety responses of colon-targeted formulations, but little information is available on the bidirectional interaction between individual microbiomes and celecoxib. Here, we conducted in vitro batch incubations of human faecal microbiota to obtain a mechanistic proof-of-concept of the short-term impact of celecoxib on activity and composition of colon bacterial communities. Celecoxib-exposed microbiota shifted metabolic activity and community composition, whereas total transcriptionally active bacterial population was not significantly changed. Butyrate production decreased by 50% in a donor-dependent manner, suggesting that celecoxib impacts in vitro fermentation. Microbiota-derived acetate has been associated with inhibition of cancer markers and our results suggest uptake of acetate for bacterial functions when celecoxib was supplied, which potentially favoured bacterial competition for acetyl-CoA. We further assessed whether colon microbiota modulates anti-inflammatory efficacy of celecoxib using a simplified inflammation model, and a novel in vitro simulation of the enterohepatic metabolism. Celecoxib was responsible for only 5% of the variance in bacterial community composition but celecoxib-exposed microbiota preserved barrier function and decreased concentrations of IL-8 and CXCL16 in a donor-dependent manner in our two models simulating gut inflammatory milieu. Our results suggest that celecoxib-microbiome-host interactions may not only elicit adaptations in community composition but also in microbiota functionality, and these may need to be considered for guaranteeing efficient COX-2 inhibition

Acute Metabolic Switch Assay Using Glucose/Galactose Medium in HepaRG Cells to Detect Mitochondrial Toxicity.

Using galactose instead of glucose in the culture medium of hepatoma cell lines, such as HepG2 cells, has been utilized for a decade to unmask the mitochondrial liability of chemical compounds. A modified glucose-galactose assay on HepG2 cells, reducing the experimental period for screening of mitochondrial toxicity to 2 to 4 hr, has been previously reported. HepaRG cells are one of the few cell lines that retain some of the important characteristics of human hepatocytes, offering advantages of working with a cell line, therefore, are considered an alternative for HepG2 cells in drug toxicity screening. A method is described here using HepaRG cells in an acute metabolic switch assay utilizing specific glucose/galactose media, a combined ATP-protein-LDH assay measuring three endpoints from one 96-well plate, and a criteria to label a compound as a mitochondrial toxin. © 2019 by John Wiley & Sons, Inc

Evidence-based selection of training compounds for use in the mechanism-based integrated prediction of drug-induced liver injury in man

The current test systems employed by pharmaceutical industry are poorly predictive for drug-induced liver injury (DILI). The ‘MIP-DILI’ project addresses this situation by the development of innovative preclinical test systems which are both mechanism-based and of physiological, pharmacological and pathological relevance to DILI in humans. An iterative, tiered approach with respect to test compounds, test systems, bioanalysis and systems analysis is adopted to evaluate existing models and develop new models that can provide validated test systems with respect to the prediction of specific forms of DILI and further elucidation of mechanisms. An essential component of this effort is the choice of compound training set that will be used to inform refinement and/or development of new model systems that allow prediction based on knowledge of mechanisms, in a tiered fashion. In this review, we focus on the selection of MIP-DILI training compounds for mechanism-based evaluation of non-clinical prediction of DILI. The selected compounds address both hepatocellular and cholestatic DILI patterns in man, covering a broad range of pharmacologies and chemistries, and taking into account available data on potential DILI mechanisms (e.g. mitochondrial injury, reactive metabolites, biliary transport inhibition, and immune responses). Known mechanisms by which these compounds are believed to cause liver injury have been described, where many if not all drugs in this review appear to exhibit multiple toxicological mechanisms. Thus, the training compounds selection offered a valuable tool to profile DILI mechanisms and to interrogate existing and novel in vitro systems for the prediction of human DILI

In Vitro Model for Hepatotoxicity Studies Based on Primary Human Hepatocyte Cultivation in a Perfused 3D Bioreactor System

Accurate prediction of the potential hepatotoxic nature of new pharmaceuticals remains highly challenging. Therefore, novel in vitro models with improved external validity are needed to investigate hepatic metabolism and timely identify any toxicity of drugs in humans. In this study, we examined the effects of diclofenac, as a model substance with a known risk of hepatotoxicity in vivo, in a dynamic multi-compartment bioreactor using primary human liver cells. Biotransformation pathways of the drug and possible effects on metabolic activities, morphology and cell transcriptome were evaluated. Formation rates of diclofenac metabolites were relatively stable over the application period of seven days in bioreactors exposed to 300 µM diclofenac (300 µM bioreactors (300 µM BR)), while in bioreactors exposed to 1000 µM diclofenac (1000 µM BR) metabolite concentrations declined drastically. The biochemical data showed a significant decrease in lactate production and for the higher dose a significant increase in ammonia secretion, indicating a dose-dependent effect of diclofenac application. The microarray analyses performed revealed a stable hepatic phenotype of the cells over time and the observed transcriptional changes were in line with functional readouts of the system. In conclusion, the data highlight the suitability of the bioreactor technology for studying the hepatotoxicity of drugs in vitro