Physiologically-based pharmacokinetic modelling to predict intragastric rifabutin concentrations in the treatment of Helicobacter pylori infection.

BACKGROUND: Sustained intragastric antibiotic exposure is important for Helicobacter pylori eradication, yet little is known about gastric pharmacology of commonly used H. pylori regimens. For rifabutin, differing intragastric concentrations based on dosing regimen may account for differences in reported eradication rates. AIM: To compare intragastric rifabutin concentrations between low-dose rifabutin (50 mg three time daily; as in RHB-105) and generically dosed rifabutin 150 mg once daily, 150 mg twice daily, and 300 mg once daily using a validated Physiologically-based pharmacokinetic (PBPK) model. METHODS: We obtained plasma pharmacokinetic data from the RHB-105 clinical development programs and used it to develop and validate a whole-body PBPK model using PK-SIM software. We modified the existing rifabutin model to include the impact of omeprazole on gastric pH and emptying time. Modelled intragastric rifabutin exposure was expressed as the time that each regimen maintained its concentration ≥MIC90 . RESULTS: Rifabutin 50 mg three times daily achieved significantly longer times with intragastric concentration above MIC90 (22.3 ± 1.1 h) than 150 mg once daily (8.3 ± 1.7 h), 150 mg twice daily (16.3 ± 2.3 h), or 300 mg once daily (8.5 ± 1.9 h) while providing the lowest mean maximal plasma concentration and mean area under the plasma concentration-time curve of all regimens studied. CONCLUSIONS: PBPK modelling showed rifabutin 50 mg three times daily had higher intragastric exposure times than 150 mg once daily or twice daily, or 300 mg once daily. This low-dose rifabutin regimen provides the highest potential for H. pylori eradication while minimising systemic rifabutin exposure.

Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation.

High-throughput (HT) in vitro to in vivo extrapolation (IVIVE) is an integral component in new approach method (NAM)-based risk assessment paradigms, for rapidly translating in vitro toxicity assay results into the context of in vivo exposure. When coupled with rapid exposure predictions, HT-IVIVE supports the use of HT in vitro assays for risk-based chemical prioritization. However, the reliability of prioritization based on HT bioactivity data and HT-IVIVE can be limited as the domain of applicability of current HT-IVIVE is generally restricted to intrinsic clearance measured primarily in pharmaceutical compounds. Further, current approaches only consider parent chemical toxicity. These limitations occur because current state-of-the-art HT prediction tools for clearance and metabolite kinetics do not provide reliable data to support HT-IVIVE. This paper discusses current challenges in implementation of IVIVE for prioritization and risk assessment and recommends a path forward for addressing the most pressing needs and expanding the utility of IVIVE.

RNA-sequencing (transcriptomic) data collected in liver and lung of male and female B6C3F1 mice exposed to various dose levels of 4-methylimidazole for 2, 5, or 28 days.

The National Toxicology Program (NTP) reported that chronic exposure to varying dietary concentrations of 4-methylimidazole (4-MeI) increased lung tumors in female and male mice [1]. In this study, mice (male and female B6C3F1 mice) were either administered 4-MeI by oral gavage (0, 50, 100, 200, or 300 mg/kg/day) for 2 days or exposed for 5 and 28 days to 4-MeI in the diet (0, 150, 300, 1250, or 2500 ppm) and whole transcriptome (RNA-Sequencing) data from 4-MeI-exposed B6C3F1 mice to determine whether changes occurred in the target (lung) and nontarget (liver) tissues. This analysis was conducted to provide information with which to evaluate biological processes affected by exposure to 4-MeI, with a focus on identifying key events that could be used to propose a plausible mode of action (MoA) for mouse lung tumors [2].

Physiologically Based Pharmacokinetic Modeling in Risk Assessment: Case Study With Pyrethroids.

The assessment of potentially sensitive populations is an important application of risk assessment. To address the concern for age-related sensitivity to pyrethroid insecticides, life-stage physiologically based pharmacokinetic (PBPK) modeling supported by in vitro to in vivo extrapolation was conducted to predict age-dependent changes in target tissue exposure to 8 pyrethroids. The purpose of this age-dependent dosimetry was to calculate a Data-derived Extrapolation Factor (DDEF) to address age-related pharmacokinetic differences for pyrethroids in humans. We developed a generic human PBPK model for pyrethroids based on our previously published rat model that was developed with in vivo rat data. The results demonstrated that the age-related differences in internal exposure to pyrethroids in the brain are largely determined by the differences in metabolic capacity and in physiology for pyrethroids between children and adults. The most important conclusion from our research is that, given an identical external exposure, the internal (target tissue) concentration is equal or lower in children than in adults in response to the same level of exposure to a pyrethroid. Our results show that, based on the use of the life-stage PBPK models with 8 pyrethroids, DDEF values are essentially close to 1, resulting in a DDEF for age-related pharmacokinetic differences of 1. For risk assessment purposes, this indicates that no additional adjustment factor is necessary to account for age-related pharmacokinetic differences for these pyrethroids.

Identifying qualitative differences in PPARα signaling networks in human and rat hepatocytes and their significance for next generation chemical risk assessment methods.

In this paper, we evaluate the PPARα signaling network in rats, examining transcriptional responses in primary hepatocytes exposed to a PPARα specific ligand, GW7647. These transcriptomic studies were complemented with ChIP-seq studies of PPARα binding and transcription binding motif identification for PPARα responsive genes. We also conducted a limited study of GW7647 dosing the in intact rat to examine differences in transcriptional responses for primary hepatocytes in vitro and in the intact liver. The rat network has a much larger number of down-regulated genes and pathways than we had found in the human and the PPARα binding motifs in rat differed for upregulated and down regulated genes. Based on these results and comparison with our previous work with the human PPARα signaling network, we identified qualitative differences in the transcriptional networks controlled by PPARα activation in the two species that provide an explanation of the interspecies differences in the responses of humans and rodents to GW7647 and likely to other PPARα agonists. These studies also allow some observations on the manner in which in vitro, fit-for-purpose assays in human hepatocytes could form the basis for risk assessment without recourse to in-life studies in rodents or other test species.

Development and Application of a Life-Stage Physiologically Based Pharmacokinetic (PBPK) Model to the Assessment of Internal Dose of Pyrethroids in Humans.

To address concerns around age-related sensitivity to pyrethroids, a life-stage physiologically based pharmacokinetic (PBPK) model, supported by in vitro to in vivo extrapolation (IVIVE) was developed. The model was used to predict age-dependent changes in target tissue exposure of 8 pyrethroids; deltamethrin (DLM), cis-permethrin (CPM), trans-permethrin, esfenvalerate, cyphenothrin, cyhalothrin, cyfluthrin, and bifenthrin. A single model structure was used based on previous work in the rat. Intrinsic clearance (CLint) of each individual cytochrome P450 or carboxylesterase (CES) enzyme that are active for a given pyrethroid were measured in vitro, then biologically scaled to obtain in vivo age-specific total hepatic CLint. These IVIVE results indicate that, except for bifenthrin, CES enzymes are largely responsible for human hepatic metabolism (>50% contribution). Given the high efficiency and rapid maturation of CESs, clearance of the pyrethroids is very efficient across ages, leading to a blood flow-limited metabolism. Together with age-specific physiological parameters, in particular liver blood flow, the efficient metabolic clearance of pyrethroids across ages results in comparable to or even lower internal exposure in the target tissue (brain) in children than that in adults in response to the same level of exposure to a given pyrethroid (Cmax ratio in brain between 1- and 25-year old = 0.69, 0.93, and 0.94 for DLM, bifenthrin, and CPM, respectively). Our study demonstrated that a life-stage PBPK modeling approach, coupled with IVIVE, provides a robust framework for evaluating age-related differences in pharmacokinetics and internal target tissue exposure in humans for the pyrethroid class of chemicals.

Developing context appropriate toxicity testing approaches using new alternative methods (NAMs).

In the past 10 years, the public, private, and non-profit sectors have found agreement that hazard identification and risk assessment should capitalize on the explosion of knowledge in the biological sciences, moving away from in life animal testing toward more human-relevant in vitro and in silico methods, collectively referred to as new approach methodologies (NAMs). The goals for implementation of NAMs are to efficiently identify possible chemical hazards and to gather dose-response data to inform more human-relevant safety assessment. While work proceeds to develop NAMs, there has been less emphasis on creating decision criteria or showing how risk context should guide selection and use of NAMs. Here, we outline application scenarios for NAMs in different risk contexts and place different NAMs and conventional testing approaches into four broad levels. Level 1 relies solely on computational screening; Level 2 consists of high throughput in vitro screening with human cells intended to provide broad coverage of possible responses; Level 3 focuses on fit-for-purpose assays selected based on presumptive modes of action (MOA) and designed to provide more quantitative estimates of relevant dose responses; Level 4 has a variety of more complex multi-dimensional or multi-cellular assays and might include targeted in vivo studies to further define MOA. Each level also includes decision-appropriate exposure assessment tools. Our aims here are to (1) foster discussion about context-dependent applications of NAMs in relation to risk assessment needs and (2) describe a functional roadmap to identify where NAMs are expected to be adequate for chemical safety decision-making.

Addressing systematic inconsistencies between in vitro and in vivo transcriptomic mode of action signatures.

Because of their broad biological coverage and increasing affordability transcriptomic technologies have increased our ability to evaluate cellular response to chemical stressors, providing a potential means of evaluating chemical response while decreasing dependence on apical endpoints derived from traditional long-term animal studies. It has recently been suggested that dose-response modeling of transcriptomic data may be incorporated into risk assessment frameworks as a means of approximating chemical hazard. However, identification of mode of action from transcriptomics lacks a similar systematic framework. To this end, we developed a web-based interactive browser-MoAviz-that allows visualization of perturbed pathways. We populated this browser with expression data from a large public toxicogenomic database (TG-GATEs). We evaluated the extent to which gene expression changes from in-life exposures could be associated with mode of action by developing a novel similarity index-the Modified Jaccard Index (MJI)-that provides a quantitative description of genomic pathway similarity (rather than gene level comparison). While typical compound-compound similarity is low (median MJI = 0.026), clustering of the TG-GATES compounds identifies groups of similar chemistries. Some clusters aggregated compounds with known similar modes of action, including PPARa agonists (median MJI = 0.315) and NSAIDs (median MJI = 0.322). Analysis of paired in vitro (hepatocyte)-in vivo (liver) experiments revealed systematic patterns in the responses of model systems to chemical stress. Accounting for these model-specific, but chemical-independent, differences improved pathway concordance by 36% between in vivo and in vitro models.

Assessing bioactivity-exposure profiles of fruit and vegetable extracts in the BioMAP profiling system.

The ToxCast program has generated in vitro screening data on over a thousand chemicals to assess potential disruption of important biological processes and assist in hazard identification and chemical testing prioritization. Few results have been reported for complex mixtures. To extend these ToxCast efforts to mixtures, we tested extracts from 30 organically grown fruits and vegetables in concentration-response in the BioMAP® assays. BioMAP systems use human primary cells primed with endogenous pathway activators to identify phenotypic perturbations related to proliferation, inflammation, immunomodulation, and tissue remodeling. Clustering of bioactivity profiles revealed separation of these produce extracts and ToxCast chemicals. Produce extracts elicited 87 assay endpoint responses per item compared to 20 per item for ToxCast chemicals. On a molar basis, the produce extracts were 10 to 50-fold less potent and when constrained to the maximum testing concentration of the ToxCast chemicals, the produce extracts did not show activity in as many assay endpoints. Using intake adjusted measures of dose, the bioactivity potential was higher for produce extracts than for agrichemicals, as expected based on the comparatively small amounts of agrichemical residues present on conventionally grown produce. The evaluation of BioMAP readouts and the dose responses for produce extracts showed qualitative and quantitative differences from results with single chemicals, highlighting challenges in the interpretation of bioactivity data and dose-response from complex mixtures.

Strain-related differences in mouse lung gene expression over a two-year period of inhalation exposure to styrene: Relevance to human risk assessment.

Both CD-1 and C57BL/6 wildtype (C57BL/6-WT) mice show equivalent short-term lung toxicity from exposures to styrene, while long-term tumor responses are greater in CD-1 mice. We analyzed lung gene expression from styrene exposures lasting from 1-day to 2-years in male mice from these two strains, including a Cyp2f2(-/-) knockout (C57BL/6-KO) and a Cyp2F1/2A13/2B6 transgenic mouse (C57BL/6-TG). With short term exposures (1-day to 1-week), CD-1 and C57BL/6-WT mice had thousands of differentially expressed genes (DEGs), consistent with changes in pathways for cell proliferation, cellular lipid metabolism, DNA-replication and inflammation. C57BL/6-WT mice responded within a single day; CD-1 mice required several days of exposure. The numbers of exposure related DEGs were greatly reduced at longer times (4-weeks to 2-years) with enrichment only for biological oxidations in C57BL/6-WT and metabolism of lipids and lipoproteins in CD-1. Gene expression results indicate a non-genotoxic, mouse specific mode of action for short-term styrene responses related to activation of nuclear receptor signaling and cell proliferation. Greater tumor susceptibility in CD-1 mice correlated with the presence of the Pas1 loci, differential Cytochrome P450 gene expression, down-regulation of Nr4a, and greater inflammatory pathway activation. Very few exposure-related responses occurred at any time in C57BL/6-KO or -TG mice indicating that neither the short term nor long term responses of styrene in mice are relevant endpoints for assessing human risks.

Assessing molecular initiating events (MIEs), key events (KEs) and modulating factors (MFs) for styrene responses in mouse lungs using whole genome gene expression profiling following 1-day and multi-week exposures.

Styrene increased lung tumors in mice at chronic inhalation exposures of 20ppm and greater. MIEs, KEs and MFs were examined using gene expression in three strains of male mice (the parental C57BL/6 strain, a CYP2F2(-/-) knock out and a CYP2F2(-/-) transgenic containing human CYP2F1, 2A13 and 2B6). Exposures were for 1-day and 1, 4 and 26weeks. After 1-day exposures at 1, 5, 10, 20, 40 and 120ppm significant increases in differentially expressed genes (DEGs) occurred only in parental strain lungs where there was already an increase in DEGs at 5ppm and then many thousands of DEGs by 120ppm. Enrichment for 1-day and 1-week exposures included cell cycle, mitotic M-M/G1 phases, DNA-synthesis and metabolism of lipids and lipoproteins pathways. The numbers of DEGs decreased steadily over time with no DEGs meeting both statistical significance and fold-change criteria at 26weeks. At 4 and 26weeks, some key transcription factors (TFs) - Nr1d1, Nr1d2, Dbp, Tef, Hlf, Per3, Per2 and Bhlhe40 - were upregulated (|FC|>1.5), while others - Npas, Arntl, Nfil3, Nr4a1, Nr4a2, and Nr4a3 - were down-regulated. At all times, consistent changes in gene expression only occurred in the parental strain. Our results support a MIE for styrene of direct mitogenicity from mouse-specific CYP2F2-mediated metabolites activating Nr4a signaling. Longer-term MFs include down-regulation of Nr4a genes and shifts in both circadian clock TFs and other TFs, linking circadian clock to cellular metabolism. We found no gene expression changes indicative of cytotoxicity or activation of p53-mediated DNA-damage pathways.

Using exposure prediction tools to link exposure and dosimetry for risk-based decisions: A case study with phthalates.

A few different exposure prediction tools were evaluated for use in the new in vitro-based safety assessment paradigm using di-2-ethylhexyl phthalate (DEHP) and dibutyl phthalate (DnBP) as case compounds. Daily intake of each phthalate was estimated using both high-throughput (HT) prediction models such as the HT Stochastic Human Exposure and Dose Simulation model (SHEDS-HT) and the ExpoCast heuristic model and non-HT approaches based on chemical specific exposure estimations in the environment in conjunction with human exposure factors. Reverse dosimetry was performed using a published physiologically based pharmacokinetic (PBPK) model for phthalates and their metabolites to provide a comparison point. Daily intakes of DEHP and DnBP were estimated based on the urinary concentrations of their respective monoesters, mono-2-ethylhexyl phthalate (MEHP) and monobutyl phthalate (MnBP), reported in NHANES (2011-2012). The PBPK-reverse dosimetry estimated daily intakes at the 50th and 95th percentiles were 0.68 and 9.58 µg/kg/d and 0.089 and 0.68 µg/kg/d for DEHP and DnBP, respectively. For DEHP, the estimated median from PBPK-reverse dosimetry was about 3.6-fold higher than the ExpoCast estimate (0.68 and 0.18 µg/kg/d, respectively). For DnBP, the estimated median was similar to that predicted by ExpoCast (0.089 and 0.094 µg/kg/d, respectively). The SHEDS-HT prediction of DnBP intake from consumer product pathways alone was higher at 0.67 µg/kg/d. The PBPK-reverse dosimetry-estimated median intake of DEHP and DnBP was comparable to values previously reported for US populations. These comparisons provide insights into establishing criteria for selecting appropriate exposure prediction tools for use in an integrated modeling platform to link exposure to health effects.

Combining transcriptomics and PBPK modeling indicates a primary role of hypoxia and altered circadian signaling in dichloromethane carcinogenicity in mouse lung and liver.

Dichloromethane (DCM) is a lung and liver carcinogen in mice at inhalation exposures≥2000ppm. The modes of action (MOA) of these responses have been attributed to formation of genotoxic, reactive metabolite(s). Here, we examined gene expression in lung and liver from female B6C3F1 mice exposed to 0, 100, 500, 2000, 3000 and 4000ppm DCM for 90days. We also simulated dose measures - rates of DCM oxidation to carbon monoxide (CO) in lung and liver and expected blood carboxyhemoglobin (HbCO) time courses with a PBPK model inclusive of both conjugation and oxidation pathways. Expression of large numbers of genes was altered at 100ppm with maximal changes in the numbers occurring by 500 or 2000ppm. Most changes in genes common to the two tissues were related to cellular metabolism and circadian clock. At the lower concentrations, the changes in metabolism-related genes were discordant - up in liver and down in lung. These processes included organelle biogenesis, TCA cycle, and respiratory electron transport. Changes in circadian cycle genes - primarily transcription factors - showed strong concentration-related response at higher concentrations (Arntl, Npas2, and Clock were down-regulated; Cry2, Wee1, Bhlhe40, Per3, Nr1d1, Nr1d2 and Dbp) were up-regulated with similar directionality in both tissues. Overall, persistently elevated HbCO from DCM oxidation appears to cause extended periods of hypoxia, leading to altered circadian coupling to cellular metabolism. The dose response for altered circadian processes correlates with the cancer outcome. We found no evidence of changes in genes indicative of responses to cytotoxic, DNA-reactive metabolites.

Editor's Highlight: Screening ToxCast Prioritized Chemicals for PPARG Function in a Human Adipose-Derived Stem Cell Model of Adipogenesis.

The developmental origins of obesity hypothesis posits a multifaceted contribution of factors to the fetal origins of obesity and metabolic disease. Adipocyte hyperplasia in gestation and early childhood may result in predisposition for obesity later in life. Rodent in vitro and in vivo studies indicate that some chemicals may directly affect adipose progenitor cell differentiation, but the human relevance of these findings is unclear. The nuclear receptor peroxisome proliferator-activated receptor gamma (PPARG) is the master regulator of adipogenesis. Human adipose-derived stem cells (hASC) isolated from adipose tissue express endogenous isoforms of PPARG and represent a biologically relevant cell-type for evaluating activity of PPARG ligands. Here, a multi-endpoint approach based on a phenotypic adipogenesis assay was applied to screen a set of 60 chemical compounds identified in ToxCast Phase I as PPARG active (49) or inactive (11). Chemicals showing activity in the adipogenesis screen were further evaluated in a series of 4 orthogonal assays representing 7 different key events in PPARG-dependent adipogenesis, including gene transcription, protein expression, and adipokine secretion. An siRNA screen was also used to evaluate PPARG-dependence of the adipogenesis phenotype. A universal concentration-response design enabled inter-assay comparability and implementation of a weight-of-evidence approach for bioactivity classification. Collectively, a total of 14/49 (29%) prioritized chemicals were identified with moderate-to-strong activity for human adipogenesis. These results provide the first integrated screening approach of prioritized ToxCast chemicals in a human stem cell model of adipogenesis and provide insight into the capacity of PPARG-activating chemicals to modulate early life programming of adipose tissue.

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity.

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17ß estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERß were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.

The Human Toxome Collaboratorium: A Shared Environment for Multi-Omic Computational Collaboration within a Consortium.

The Human Toxome Project is part of a long-term vision to modernize toxicity testing for the 21st century. In the initial phase of the project, a consortium of six academic, commercial, and government organizations has partnered to map pathways of toxicity, using endocrine disruption as a model hazard. Experimental data is generated at multiple sites, and analyzed using a range of computational tools. While effectively gathering, managing, and analyzing the data for high-content experiments is a challenge in its own right, doing so for a growing number of -omics technologies, with larger data sets, across multiple institutions complicates the process. Interestingly, one of the most difficult, ongoing challenges has been the computational collaboration between the geographically separate institutions. Existing solutions cannot handle the growing heterogeneous data, provide a computational environment for consistent analysis, accommodate different workflows, and adapt to the constantly evolving methods and goals of a research project. To meet the needs of the project, we have created and managed The Human Toxome Collaboratorium, a shared computational environment hosted on third-party cloud services. The Collaboratorium provides a familiar virtual desktop, with a mix of commercial, open-source, and custom-built applications. It shares some of the challenges of traditional information technology, but with unique and unexpected constraints that emerge from the cloud. Here we describe the problems we faced, the current architecture of the solution, an example of its use, the major lessons we learned, and the future potential of the concept. In particular, the Collaboratorium represents a novel distribution method that could increase the reproducibility and reusability of results from similar large, multi-omic studies.