Exploring rabbit as a nonrodent species for general toxicology studies.

To avoid adverse events in humans, toxicity studies in nonclinical species have been the foundation of safety evaluation in the pharmaceutical industry. However, it is recognized that working with animals in research is a privilege, and conscientious use should always respect the 3Rs: replacement, reduction, and refinement. In the wake of the shortages in routine nonrodent species and considering that nonanimal methods are not yet sufficiently mature, the value of the rabbit as a nonrodent species is worth exploring. Historically used in vaccine, cosmetic, and medical device testing, the rabbit is seldom used today as a second species in pharmaceutical development, except for embryo-fetal development studies, ophthalmic therapeutics, some medical devices and implants, and vaccines. Although several factors affect the decision of species selection, including pharmacological relevance, pharmacokinetics, and ADME considerations, there are no perfect animal models. In this forum article, we bring together experts from veterinary medicine, industry, contract research organizations, and government to explore the pros and cons, residual concerns, and data gaps regarding the use of the rabbit for general toxicity testing.

Lower cardiotoxicity of CPX-351 relative to daunorubicin plus cytarabine free-drug combination in hiPSC-derived cardiomyocytes in vitro.

Liposomal formulations are hypothesized to alleviate anthracycline cardiotoxicity, although this has only been documented clinically for doxorubicin. We developed an in vitro multiparametric model using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) to assess the relative toxicity of anthracyclines across formulations. Proof of concept was established by treating hiPSC-CM with equivalent concentrations of free and liposomal doxorubicin. The study was then repeated with free daunorubicin plus cytarabine and CPX-351, a dual-drug liposomal encapsulation of daunorubicin/cytarabine. hiPSC-CM were treated with free-drug or liposomal formulations for 24 h on Days 1, 3, and 5 at equivalent concentrations ranging from 0 to 1000 ng/mL and assessed on subsequent days. Free-drug treatment resulted in concentration-dependent cumulative cytotoxicity (microscopy), more profound decrease in ATP levels, and significant time- and concentration-dependent decreases in oxygen consumption versus liposomal formulations (p < 0.01). Repeated free-drug exposure also resulted in greater release of biomarkers (cardiac troponin I, FABP3) and lactate dehydrogenase, as well as in a biphasic rhythmicity response (initial increase followed by slowing/quiescence of beating) indicating significant injury, which was not observed after repeated exposure to liposomal formulations. Overall, liposomal formulations were considerably less toxic to hiPSC-CM than their free-drug counterparts. Clinical data will be needed to confirm findings for CPX-351.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs.

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

Genetic toxicology in silico protocol.

In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

In silico toxicology protocols.

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

Adverse outcome pathway networks II: Network analytics.

Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734-1748. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Adverse outcome pathway networks I: Development and applications.

Based on the results of a Horizon Scanning exercise sponsored by the Society of Environmental Toxicology and Chemistry that focused on advancing the adverse outcome pathway (AOP) framework, the development of guidance related to AOP network development was identified as a critical need. This not only included questions focusing directly on AOP networks, but also on related topics such as mixture toxicity assessment and the implementation of feedback loops within the AOP framework. A set of two articles has been developed to begin exploring these concepts. In the present article (part I), we consider the derivation of AOP networks in the context of how it differs from the development of individual AOPs. We then propose the use of filters and layers to tailor AOP networks to suit the needs of a given research question or application. We briefly introduce a number of analytical approaches that may be used to characterize the structure of AOP networks. These analytical concepts are further described in a dedicated, complementary article (part II). Finally, we present a number of case studies that illustrate concepts underlying the development, analysis, and application of AOP networks. The concepts described in the present article and in its companion article (which focuses on AOP network analytics) are intended to serve as a starting point for further development of the AOP network concept, and also to catalyze AOP network development and application by the different stakeholder communities. Environ Toxicol Chem 2018;37:1723-1733. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Air Pollution and the Epigenome: A Model Relationship for the Exploration of Toxicoepigenetics.

The field of toxicoepigenetics is rapidly emerging to provide new insights into the relationship between environmental factors, the epigenome, and public health. Toxicoepigenetic data have the potential to revolutionize our understanding of environmental exposure effects and susceptibility. Studies in recent years have demonstrated that exposure to air pollution alters epigenetic modification states; however, continued advancement of the field is limited by the intrinsic complexity of the epigenome and inherent limitations of different types of studies (epidemiological, clinical, and in vitro) that are used in toxicoepigenetics. Overcoming these challenges will require a concerted and collaborative effort between molecular and cellular biologists, toxicologists, epidemiologists, and risk assessors to develop a thorough and practical understanding of the relationship between air pollution exposure, the epigenome, and health effects. Here we review the current state of air pollution epigenetics and discuss perspectives on the necessary steps to move the field forward to determine the role that the epigenome plays in air pollution exposure effects and susceptibility.

Remembering the dynamic changes in pain intensity and unpleasantness: a psychophysical study.

This study investigated the short-term memory of dynamic changes in acute pain using psychophysical methods. Pain intensity or unpleasantness induced by painful contact-heat stimuli of 8, 9, or 10s was rated continuously during the stimulus or after a 14-s delay using an electronic visual analog scale in 10 healthy volunteers. Because the continuous visual analog scale time courses contained large amounts of redundant information, a principal component analysis was applied to characterize the main features inherent to both the concurrent rating and retrospective evaluations. Three components explained about 90% of the total variance across all trials and subjects, with the first component reflecting the global perceptual profile, and the second and third components explaining finer perceptual aspects (eg, changes in slope at onset and offset and shifts in peak latency). We postulate that these 3 principal components may provide some information about the structure of the mental representations of what one perceives, stores, and remembers during the course of few seconds. Analysis performed on the components confirmed significant memory distortions and revealed that the discriminative information about pain dimensions in concurrent ratings was partly or completely lost in retrospective ratings. Importantly, our results highlight individual differences affecting these memory processes. These results provide further evidence of the important transformations underlying the processing of pain in explicit memory and raise fundamental questions about the conversion of dynamic nociceptive signals into a mental representation of pain in perception and memory.

Alteration of the expression of pesticide-metabolizing enzymes in pregnant mice: potential role in the increased vulnerability of the developing brain.

Studies on therapeutic drug disposition in humans have shown significant alterations as the result of pregnancy. However, it is not known whether pesticide metabolic capacity changes throughout pregnancy, which could affect exposure of the developing brain. We sought to determine the effect of pregnancy on the expression of hepatic enzymes involved in the metabolism of pesticides. Livers were collected from virgin and pregnant C57BL/6 mice at gestational days (GD)7, GD11, GD14, GD17, and postpartum days (PD)1, PD15, and PD30. Relative mRNA expression of several enzymes involved in the metabolism of pesticides, including hepatic cytochromes (Cyp) P450s, carboxylesterases (Ces), and paraoxonase 1 (Pon1), were assessed in mice during gestation and the postpartum period. Compared with virgin mice, alterations in the expression occurred at multiple time points, with the largest changes observed on GD14. At this time point, the expression of most of the Cyps involved in pesticide metabolism in the liver (Cyp1a2, Cyp2d22, Cyp2c37, Cyp2c50, Cyp2c54, and Cyp3a11) were downregulated by 30% or more. Expression of various Ces isoforms and Pon1 were also decreased along with Pon1 activity. These data demonstrate significant alterations in the expression of key enzymes that detoxify pesticides during pregnancy, which could alter exposure of developing animals to these chemicals.

Increased lead biomarker levels are associated with changes in hormonal response to stress in occupationally exposed male participants.

BACKGROUND: Lead (Pb) exposure has been associated with a host of pathological conditions in humans. In rodents Pb exposure has been shown to alter the hypothalamic-pituitary-adrenal (HPA) axis function. OBJECTIVE: We investigated the effects of lead on responses of the HPA axis to a psychosocial laboratory stressor administered to Pb-exposed workers. METHODS: Seventy male participants completed the Trier Social Stress Test (TSST). Serum cortisol (CORT) and plasma adrenocorticotropic hormone (ACTH) were assessed in response to and during recovery from the stressor. We measured Pb in blood, a biomarker of recent exposure, and in tibia bone by X-ray fluorescence (XRF), a biomarker of chronic exposure. RESULTS: The TSST induced statistically significant increases in ACTH and CORT in the participants. At baseline, ACTH was not significantly higher (p = 0.052) in participants with higher blood Pb concentration, but CORT was significantly lower in these participants (p = 0.016). Adjusted linear regression models indicated a positive association between blood and bone Pb and the increase in ACTH in response to stress. However, Pb was not strongly associated with changes in CORT in response to stress. Pb was also associated with the ACTH:CORT ratio at baseline and throughout the course of the protocol, suggesting an adrenal hyporesponsiveness in participants with higher Pb concentrations. CONCLUSION: The altered HPA-axis stress response observed in participants exposed to higher levels of Pb further supports the idea that lead may contribute to a host of biological dysfunctions beyond the classical neurotoxic effects.

Fused-core silica column ultra-performance liquid chromatography-ion trap tandem mass spectrometry for determination of global DNA methylation status.

Epigenetic modifications, such as DNA methylation, play key roles in transcriptional regulation of gene expression. More recently, global DNA methylation levels have been documented to be altered in several diseases, including cancer, and as the result of exposure to environmental toxicants. Based on the potential use of global DNA methylation status as a biomarker of disease status and exposure to environmental toxicants, we sought to develop a rapid, sensitive, and precise analytical method for the quantitative measurement of global DNA methylation status using ultra-performance liquid chromatography with detection by ion trap tandem mass spectrometry. Using a fused-core silica column, 2'-deoxyguanosine (2dG) and 5-methyl-2'-deoxycytidine (5mdC) were resolved in less than 1 min with detection limits of 0.54 and 1.47 fmol for 5mdC and 2dG, respectively. The accuracy of detection was 95% or higher, and the day-to-day coefficient of variation was found to be 3.8%. The method was validated by quantification of global DNA methylation status following treatment of cells with the DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine, which reduced DNA methylation from 3.1% in control cells to 1.1% in treated cells. The sensitivity and high throughput of this method rend it suitable for large-scale analysis of epidemiological and clinical DNA samples.