Using quantitative modeling tools to assess pharmacokinetic bias in epidemiological studies showing associations between biomarkers and health outcomes at low exposures.

Biomarkers of exposure can be measured at lower and lower levels due to advances in analytical chemistry. Using these sensitive methods, some epidemiology studies report associations between biomarkers and health outcomes at biomarker levels much below those associated with effects in animal studies. While some of these low exposure associations may arise from increased sensitivity of humans compared with animals or from species-specific responses, toxicology studies with drugs, commodity chemicals and consumer products have not generally indicated significantly greater sensitivity of humans compared with test animals for most health outcomes. In some cases, these associations may be indicative of pharmacokinetic (PK) bias, i.e., a situation where a confounding factor or the health outcome itself alters pharmacokinetic processes affecting biomarker levels. Quantitative assessment of PK bias combines PK modeling and statistical methods describing outcomes across large numbers of individuals in simulated populations. Here, we first provide background on the types of PK models that can be used for assessing biomarker levels in human population and then outline a process for considering PK bias in studies intended to assess associations between biomarkers and health outcomes at low levels of exposure. After providing this background, we work through published examples where these PK methods have been applied with several chemicals/chemical classes - polychlorinated biphenyls (PCBs), perfluoroalkyl substances (PFAS), polybrominated biphenyl ethers (PBDE) and phthalates - to assess the possibility of PK bias. Studies of the health effects of low levels of exposure will be improved by developing some confidence that PK bias did not play significant roles in the observed associations.

Quantitative bias analysis of the association between subclinical thyroid disease and two perfluoroalkyl substances in a single study.

Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) has been associated with the occurrence of thyroid disease in some epidemiologic studies. We hypothesized that in a specific epidemiologic study based on the National Health and Nutrition Examination Survey, the association of subclinical thyroid disease with serum concentration of PFOA and PFOS was due to reverse causality. Thyroid hormone affects glomerular filtration, which in turn affects excretion of PFOA and PFOS. We evaluated this by linking a model of thyroid disease status over the lifetime to physiologically based pharmacokinetic models of PFOA and PFOS. Using Monte Carlo methods, we simulated the target study population and analyzed the data using multivariable logistic regression. The target and simulated populations were similar with respect to age, estimated glomerular filtration rate, serum concentrations of PFOA and PFOS, and prevalence of subclinical thyroid disease. Our findings suggest that in the target study the associations with subclinical hypothyroidism were overstated and the results for subclinical hyperthyroidism were, in general, understated. For example, for subclinical hypothyroidism in men, the reported odds ratio per ln(PFOS) increase was 1.98 (95% CI 1.19-3.28), whereas in the simulated data the bias due to reverse causality gave an odds ratio of 1.19 (1.16-1.23). Our results provide evidence of bias due to reverse causality in a specific cross-sectional study of subclinical thyroid disease with exposure to PFOA and PFOS among adults.

Biological system considerations for application of toxicogenomics in next-generation risk assessment and predictive toxicology.

There is increasing interest in using modern 'omics technologies, such as whole transcriptome sequencing, to inform decisions about human health safety and chemical toxicity hazard. High throughput methodologies using in vitro assays offer a path forward in reducing or eliminating animal testing. However, many aspects of these technologies need assessment before they will gain the trust of regulators and the public as viable alternative test methods for human health and safety. We used a high throughput whole transcriptome sequence assay (TempO-Seq) to assess the use of three widely used cancer cell lines (HepG2, MCF7, and Ishikawa cells) as in vitro systems for determination of cellular modes of action for two well studied compounds with canonical liver responses: ketoconazole and phenobarbital. We evaluated transcriptomic data to infer points of departure for use in risk analyses of compounds. Both compounds displayed shortcomings in evidence for canonical liver-related responses in any cell line, despite a strong dose response in all three. This raises questions about the competence of simple, mono-cultured cancer cell lines as appropriate surrogates for some adverse effects or toxic endpoints. Points of departure derived from benchmark doses were highly consistent across all three cell lines however, indicating the use of transcriptomic BMD analyses for such purposes would be a reliable and consistent approach.

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.

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.

The Evolving Druggability and Developability Space: Chemically Modified New Modalities and Emerging Small Molecules.

The druggability and developability space is rapidly evolving in the post-genomic era. In the past, Lipinski's rule-of-five (Ro5) emerged and served as a guide for drug-like molecule design for oral delivery in the traditional druggable target space. In contrast, in this new era, a transition is occurring in drug discovery towards novel approaches to bind and modulate challenging biological targets that have led to transformative treatments for patients. Consequently, drugging novel targets using a variety of emerging molecular modalities, namely beyond the Ro5 (bRo5) small molecules (such as protein-protein interaction modulators, protein-targeted chimeras, or PROTACs), peptide/peptidomimetics, and nucleic acid-based modalities, have become a key focus in drug discovery. Herein, the emerging druggability and developability space is discussed side by side to build a general understanding of the potential development challenges of these novel modalities. An overview is provided on the evolving novel targets and molecular modalities, followed by a detailed analysis of the druggability aspects as well as the strategies used to progress drug candidate, and the trending chemistry and formulation strategies used to assess developability.

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.

Impact of diet on irinotecan toxicity in mice.

Irinotecan is highly effective in the treatment of metastatic colorectal cancer as well as many other cancers. However, irinotecan is known to cause severe diarrhea, which pose significant problems in patients undergoing irinotecan based chemotherapy. Dietary and herbal components have shown promise in improving gastrointestinal health. Therefore, we compared the effect of grain-based chow diet containing phytoestrogens and corn/alfalfa as fat source to purified diets containing either animal-derived fat source (lard) or plant-derived fat source (soybean oil) on irinotecan-induced toxicities in mice. The concentration of the toxic metabolite, SN-38, was measured in the serum, and the activity of main enzyme, carboxylesterase (CEs) involved in biotransformation of irinotecan to SN-38 formation was measured in the liver. We found that the grain-based diet was protective against irinotecan-induced diarrhea. Interestingly, purified diet containing lard caused fatty liver in mice, while grain-based chow diet containing corn/alfa-alfa or purified diet with soybean oil did not cause fat deposition in the liver. Serum SN-38 concentration was significantly higher in the mice fed with purified diets compared to the chow-fed mice. Hepatic CEs activity was induced in the presence of irinotecan in mice on purified diets, but not chow diet. These results indicate that components of grain-based natural diet (presumably phytoestrogens and/or the macronutrients balance) compared to purified diets may have a beneficial effect by controlling the adverse effects of irinotecan in cancer patients.

Role of Toll-like receptor 4 in drug-drug interaction between paclitaxel and irinotecan in vitro.

The bacterial receptor, Toll-like receptor (TLR) 4 mediates inflammatory responses and has been linked to a broad array of diseases. TLR4 agonists are being explored as potential treatments for cancer and other diseases. We have previously shown that activation of TLR4 by lipopolysaccharide (LPS) leads to down-regulation of drug metabolizing enzymes/transporters (DMETs), and altered pharmacokinetics/pharmacodynamics (PK/PD) of drugs. These changes can increase the risk of drug-drug interactions (DDIs) in patients on multiple medications. Clinically, DDI was observed for combination chemotherapy of paclitaxel (TLR4 ligand) and irinotecan. To determine the role of TLR4 in DDI between paclitaxel and irinotecan in vitro, primary hepatocytes from TLR4-wild-type (WT) and mutant mice were pre-treated with paclitaxel, followed by irinotecan. Gene expression of DMETs was determined. Paclitaxel treatment increased the levels of irinotecan metabolites, SN-38 and SN-38 glucuronide (SN-38G) in TLR4-dependent manner. Paclitaxel-mediated induction of genes involved in irinotecan metabolism such as Cyp3a11 and Ugt1a1 was TLR4-dependent, while induction of the transporter Mrp2 was TLR4-independent. These novel findings demonstrate that paclitaxel can affect irinotecan metabolism by a TLR4-dependent mechanism. This provides a new perspective towards evaluation of marketed drugs according to their potential to exert DDIs in TLR4-dependent manner.

Regulation of drug-metabolizing enzymes in infectious and inflammatory disease: implications for biologics-small molecule drug interactions.

INTRODUCTION: Drug-metabolizing enzymes (DMEs) are primarily down-regulated during infectious and inflammatory diseases, leading to disruption in the metabolism of small molecule drugs (smds), which are increasingly being prescribed therapeutically in combination with biologics for a number of chronic diseases. The biologics may exert pro- or anti-inflammatory effect, which may in turn affect the expression/activity of DMEs. Thus, patients with infectious/inflammatory diseases undergoing biologic/smd treatment can have complex changes in DMEs due to combined effects of the disease and treatment. Areas covered: We will discuss clinical biologics-SMD interaction and regulation of DMEs during infection and inflammatory diseases. Mechanistic studies will be discussed and consequences on biologic-small molecule combination therapy on disease outcome due to changes in drug metabolism will be highlighted. Expert opinion: The involvement of immunomodulatory mediators in biologic-SMDs is well known. Regulatory guidelines recommend appropriate in vitro or in vivo assessments for possible interactions. The role of cytokines in biologic-SMDs has been documented. However, the mechanisms of drug-drug interactions is much more complex, and is probably multi-factorial. Studies aimed at understanding the mechanism by which biologics effect the DMEs during inflammation/infection are clinically important.

In Vitro Approaches to Study Regulation of Hepatic Cytochrome P450 (CYP) 3A Expression by Paclitaxel and Rifampicin.

Cancer is the second leading cause of mortality worldwide; however the response rate to chemotherapy treatment remains slow, mainly due to narrow therapeutic index and multidrug resistance. Paclitaxel (taxol) has a superior outcome in terms of response rates and progression-free survival. However, numerous cancer patients are resistant to this drug. In this investigation, we tested the hypothesis that induction of cytochrome P450 (Cyp)3a11 gene by paclitaxel is downregulated by the inflammatory mediator, lipopolysaccharide (LPS), and that the pro-inflammatory cytokine, tumor necrosis factor (TNF)-α, attenuates human CYP3A4 gene induction by rifampicin. Primary mouse hepatocytes were pretreated with LPS (1 µg/ml) for 10 min, followed by paclitaxel (20 µM) or vehicle for 24 h. RNA was extracted from the cells by trizol method followed by cDNA synthesis and analysis by real-time PCR. Paclitaxel significantly induced gene expression of Cyp3a11 (~30-fold) and this induction was attenuated in LPS-treated samples. Induction and subsequent downregulation of CYP3A enzyme can impact paclitaxel treatment in cancer patients where inflammatory mediators are activated. It has been shown that the nuclear receptor, pregnane X receptor (PXR), plays a role in the induction of CYP enzymes. In order to understand the mechanisms of regulation of human CYP3A4 gene, we co-transfected HepG2 cells (human liver cell line) with CYP3A4-luciferase construct and a PXR expression plasmid. The cells were then treated with the pro-inflammatory cytokine, TNFα, followed by the prototype CYP3A inducer rifampicin. It is well established that rifampicin activates PXR, leading to CYP3A4 induction. We found that induction of CYP3A4-luciferase activity by rifampicin was significantly attenuated by TNFα. In conclusion, we describe herein several in vitro approaches entailing primary and cultured hepatocytes, real-time PCR, and transcriptional activation (transfection) assays to investigate the molecular regulation of CYP3A, which plays a pivotal role in the metabolism of numerous chemotherapeutic drugs. Genetic or drug-induced variation in CYP3A and/or PXR expression could contribute to drug resistance to chemotherapeutic agents in cancer patients.

Impact of obesity on accumulation of the toxic irinotecan metabolite, SN-38, in mice.

AIM: Our aim is to investigate the impact of high fat diet-induced obesity on plasma concentrations of the toxic irinotecan metabolite, SN-38, in mice. MAIN METHODS: Diet-induced obese (DIO, 60% kcal fed) and lean mice (10% kcal fed) were treated orally with a single dose of 10mg/kg irinotecan to determine pharmacokinetic (PK) parameters. Feces and livers were collected for quantification of irinotecan and its metabolites (SN-38 & SN-38G). SN-38G formation by Ugt1a1 enzyme was analyzed in liver S9 fractions. Expression of the pro-inflammatory cytokine, TNF-α was determined in liver and plasma. Hepatic ß-glucuronidase and carboxylesterase enzymes (CES) were also determined. KEY FINDINGS: AUC0-8 and Cmax of SN-38 increased by 2-fold in DIO mice compared to their lean controls. This was accompanied by a~2-fold reduction in AUC0-8 and Cmax of SN-38G in DIO mice. There were no differences in the PK parameters of irinotecan in DIO or lean mice. Conversion of SN-38 to SN-38G by Ugt1a1 enzyme was reduced by ~2-fold in liver S9 fractions in DIO mice. Furthermore, in DIO mice, ß-glucuronidase activity increased by 2-fold, whereas there was no change in CES activity. TNF-α mRNA expression was 3 fold higher in DIO mice. SIGNIFICANCE: Our study demonstrates that reduced hepatic Ugt1a activity during obesity likely contributes to reduced glucuronidation, and results in higher levels of the toxic metabolite, SN-38. Thus, irinotecan dosage should be closely monitored for effective and safe chemotherapy in obese cancer patients who are at a higher risk of developing liver toxicity.