Hamner Institutes for Health Sciences

Golden Triangle, NC, United States

Hamner Institutes for Health Sciences

Golden Triangle, NC, United States
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Zhao Y.,Hamner Institutes for Health Sciences | Hu Z.-Y.,University of Tennessee Health Science Center
British Journal of Pharmacology | Year: 2014

Background and purpose In vitro inhibitory potency (Ki)-based predictions of P-glycoprotein (P-gp)-mediated drug-drug interactions (DDIs) are hampered by the substantial variability in inhibitory potency. In this study, in vivo-based [I]/Ki values were used to predict the DDI risks of a P-gp substrate dabigatran etexilate (DABE) using physiologically based pharmacokinetic (PBPK) modelling. Experimental approach A baseline PBPK model was established with digoxin, a known P-gp substrate. The Km (P-gp transport) of digoxin in the baseline PBPK model was adjusted to K mi to fit the change of digoxin pharmacokinetics in the presence of a P-gp inhibitor. Then 'in vivo' [I]/Ki of this P-gp inhibitor was calculated using Kmi/Km. Baseline PBPK model was developed for DABE, and the 'in vivo' [I]/Ki was incorporated into this model to simulate the static effect of P-gp inhibitor on DABE pharmacokinetics. This approach was verified by comparing the observed and the simulated DABE pharmacokinetics in the presence of five different P-gp inhibitors. Key results This approach accurately predicted the effects of five P-gp inhibitors on DABE pharmacokinetics (98-133% and 89-104% for the ratios of AUC and Cmax respectively). The effects of 16 other P-gp inhibitors on the pharmacokinetics of DABE were also confidently simulated. Conclusions and implications 'In vivo' [I]/Ki and PBPK modelling, used in combination, can accurately predict P-gp-mediated DDIs. The described framework provides a mechanistic basis for the proper design of clinical DDI studies, as well as avoiding unnecessary clinical DDI studies. © 2013 The British Pharmacological Society.

Thomas R.S.,Hamner Institutes for Health Sciences | Black M.B.,Hamner Institutes for Health Sciences | Healy E.,Hamner Institutes for Health Sciences | Andersen M.E.,Hamner Institutes for Health Sciences
Toxicological Sciences | Year: 2012

Over the past 5 years, increased attention has been focused on using high-throughput in vitro screening for identifying chemical hazards and prioritizing chemicals for additional in vivo testing. The U.S. Environmental Protection Agency's ToxCast program has generated a significant amount of high-throughput screening data allowing a broad-based assessment of the utility of these assays for predicting in vivo responses. In this study, a comprehensive cross-validation model comparison was performed to evaluate the predictive performance of the more than 600 in vitro assays from the ToxCast phase I screening effort across 60 in vivo endpoints using 84 different statistical classification methods. The predictive performance of the in vitro assays was compared and combined with that from chemical structure descriptors. With the exception of chronic in vivo cholinesterase inhibition, the overall predictive power of both the in vitro assays and the chemical descriptors was relatively low. The predictive power of the in vitro assays was not significantly different from that of the chemical descriptors and aggregating the assays based on genes reduced predictive performance. Prefiltering the in vitro assay data outside the cross-validation loop, as done in some previous studies, significantly biased estimates of model performance. The results suggest that the current ToxCast phase I assays and chemicals have limited applicability for predicting in vivo chemical hazards using standard statistical classification methods. However, if viewed as a survey of potential molecular initiating events and interpreted as risk factors for toxicity, the assays may still be useful for chemical prioritization. © The Author 2012. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.

Yoon M.,Hamner Institutes for Health Sciences | Campbell J.L.,Hamner Institutes for Health Sciences | Andersen M.E.,Hamner Institutes for Health Sciences | Clewell H.J.,Hamner Institutes for Health Sciences
Critical Reviews in Toxicology | Year: 2012

The field of toxicology is currently undergoing a global paradigm shift to use of in vitro approaches for assessing the risks of chemicals and drugs in a more mechanistic and high throughput manner than current approaches relying primarily on in vivo testing. However, reliance on in vitro data entails a number of new challenges associated with translating the in vitro results to corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides an effective framework for conducting quantitative in vitro to in vivo extrapolation (QIVIVE). Their physiological structure facilitates the incorporation of in silico-and in vitro-derived chemical-specific parameters in order to predict in vivo absorption, distribution, metabolism and excretion. In particular, the combination of in silico-and in vitro parameter estimation with PBPK modeling can be used to predict the in vivo exposure conditions that would produce chemical concentrations in the target tissue equivalent to the concentrations at which effects were observed with in vitro assays of tissue/organ toxicity. This review describes the various elements of QIVIVE and highlights key aspects of the process, with an emphasis on extrapolation of in vitro metabolism data to predict in vivo clearance as the key element. Other important elements include characterization of free concentration in the toxicity assay and potential complications associated with intestinal absorption and renal clearance. Examples of successful QIVIVE approaches are described ranging from a simple steady-state approach that is suitable for a high throughput environment to more complicated approaches requiring full PBPK models. © 2012 Informa Healthcare USA, Inc.

LeCluyse E.L.,Hamner Institutes for Health Sciences | Witek R.P.,Life Technologies | Andersen M.E.,Hamner Institutes for Health Sciences | Powers M.J.,Life Technologies
Critical Reviews in Toxicology | Year: 2012

Prediction of chemical-induced hepatotoxicity in humans from in vitro data continues to be a significant challenge for the pharmaceutical and chemical industries. Generally, conventional in vitro hepatic model systems (i.e. 2-D static monocultures of primary or immortalized hepatocytes) are limited by their inability to maintain histotypic and phenotypic characteristics over time in culture, including stable expression of clearance and bioactivation pathways, as well as complex adaptive responses to chemical exposure. These systems are less than ideal for longer-term toxicity evaluations and elucidation of key cellular and molecular events involved in primary and secondary adaptation to chemical exposure, or for identification of important mediators of inflammation, proliferation and apoptosis. Progress in implementing a more effective strategy for in vitro-in vivo extrapolation and human risk assessment depends on significant advances in tissue culture technology and increasing their level of biological complexity. This article describes the current and ongoing need for more relevant, organotypic in vitro surrogate systems of human liver and recent efforts to recreate the multicellular architecture and hemodynamic properties of the liver using novel culture platforms. As these systems become more widely used for chemical and drug toxicity testing, there will be a corresponding need to establish standardized testing conditions, endpoint analyses and acceptance criteria. In the future, a balanced approach between sample throughput and biological relevance should provide better in vitro tools that are complementary with animal testing and assist in conducting more predictive human risk assessment. © 2012 Informa Healthcare USA, Inc.

Zhang Q.,Hamner Institutes for Health Sciences | Bhattacharya S.,Hamner Institutes for Health Sciences | Andersen M.E.,Hamner Institutes for Health Sciences
Open Biology | Year: 2013

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input-output relationship that is steeper than the Michaelis-Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. © 2013 The Authors.

Campbell Jr. J.L.,Hamner Institutes for Health Sciences
Methods in molecular biology (Clifton, N.J.) | Year: 2012

Physiologically based pharmacokinetic (PBPK) models differ from conventional compartmental pharmacokinetic models in that they are based to a large extent on the actual physiology of the organism. The application of pharmacokinetics to toxicology or risk assessment requires that the toxic effects in a particular tissue are related in some way to the concentration time course of an active form of the substance in that tissue. The motivation for applying pharmacokinetics is the expectation that the observed effects of a chemical will be more simply and directly related to a measure of target tissue exposure than to a measure of administered dose. The goal of this work is to provide the reader with an understanding of PBPK modeling and its utility as well as the procedures used in the development and implementation of a model to chemical safety assessment using the styrene PBPK model as an example.

Pi J.,Hamner Institutes for Health Sciences | Collins S.,Sanford Burnham Institute for Medical Research
Diabetes, Obesity and Metabolism | Year: 2010

Growing evidence indicates that reactive oxygen species (ROS) are not just deleterious by-products of respiratory metabolism in mitochondria, but can be essential elements for many biological responses, including in pancreatic β-cells. ROS can be a 'second-messenger signal' in response to hormone/receptor activation that serves as part of the 'code' to trigger the ultimate biological response, or it can be a 'protective signal' to increase the levels of antioxidant enzymes and small molecules to scavenge ROS, thus restoring cellular redox homeostasis. In pancreatic β-cells evidence is emerging that acute and transient glucose-dependent ROS contributes to normal glucose-stimulated insulin secretion (GSIS). However, chronic and persistent elevation of ROS, resulting from inflammation or excessive metabolic fuels such as glucose and fatty acids, may elevate antioxidant enzymes such that they blunt ROS and redox signalling, thus impairing β-cell function. An interesting mitochondrial protein whose main function appears to be the control of ROS is uncoupling protein 2 (UCP2). Despite continuing investigation of the exact mechanism by which UCP2 is 'activated', it is clear that UCP2 levels and/or activity impact the efficacy of GSIS in pancreatic islets. This review will focus on the paradoxical roles of ROS in pancreatic β-cell function and the regulatory role of UCP2 in ROS signalling and GSIS. © 2010 Blackwell Publishing Ltd.

Grimes J.H.,Hamner Institutes for Health Sciences | O'Connell T.M.,Hamner Institutes for Health Sciences | O'Connell T.M.,University of North Carolina at Chapel Hill
Journal of Biomolecular NMR | Year: 2011

Increasing the sensitivity and throughput of NMR-based metabolomics is critical for the continued growth of this field. In this paper the application of micro-coil NMR probe technology was evaluated for this purpose. The most commonly used biofluids in metabolomics are urine and serum. In this study we examine different sample limited conditions and compare the detection sensitivity of the micro-coil with a standard 5 mm NMR probe. Sample concentration is evaluated as a means to leverage the greatly improved mass sensitivity of the micro-coil probes. With very small sample volumes, the sensitivity of the micro-coil probe does indeed provide a significant advantage over the standard probe. Concentrating the samples does improve the signal detection, but the benefits do not follow the expected linear increase and are both matrix and metabolite specific. Absolute quantitation will be affected by concentration, but an analysis of relative concentrations is still possible. The choice of the micro-coil probe over a standard tube based probe will depend upon a number of factors including number of samples and initial volume but this study demonstrates the feasibility of high-throughput metabolomics with the micro-probe platform. © 2011 Springer Science+Business Media B.V.

Krewski D.,University of Ottawa | Westphal M.,University of Ottawa | Al-Zoughool M.,University of Ottawa | Croteau M.C.,University of Ottawa | Andersen M.E.,Hamner Institutes for Health Sciences
Annual Review of Public Health | Year: 2011

In 2007, the U.S. National Research Council (NRC) published a groundbreaking report entitled Toxicity Testing in the 21st Century: A Vision and a Strategy. The purpose of this report was to develop a long-range strategic plan to update and advance the way environmental agents are tested for toxicity. The vision focused on the identification of critical perturbations of toxicity pathways that lead to adverse human health outcomes using modern scientific tools and technologies. This review describes how emerging scientific methods will move the NRC vision forward and improve the manner in which the potential health risks associated with exposure to environmental agents are assessed. The new paradigm for toxicity testing is compatible with the widely used four-stage risk assessment framework originally proposed by the NRC in 1983 in the so-called Red Book. The Nrf2 antioxidant pathway provides a detailed example of how relevant pathway perturbations will be identified within the context of the new NRC vision for the future of toxicity testing. The implications of the NRC vision for toxicity testing for regulatory risk assessment are also discussed. © 2011 by Annual Reviews. rights reserved.

Wetmore B.A.,Hamner Institutes for Health Sciences
Toxicology | Year: 2015

High-throughput in vitro toxicity screening provides an efficient way to identify potential biological targets for environmental and industrial chemicals while conserving limited testing resources. However, reliance on the nominal chemical concentrations in these in vitro assays as an indicator of bioactivity may misrepresent potential in vivo effects of these chemicals due to differences in clearance, protein binding, bioavailability, and other pharmacokinetic factors. Development of high-throughput in vitro hepatic clearance and protein binding assays and refinement of quantitative in vitro-to-. in vivo extrapolation (QIVIVE) methods have provided key tools to predict xenobiotic steady state pharmacokinetics. Using a process known as reverse dosimetry, knowledge of the chemical steady state behavior can be incorporated with HTS data to determine the external in vivo oral exposure needed to achieve internal blood concentrations equivalent to those eliciting bioactivity in the assays. These daily oral doses, known as oral equivalents, can be compared to chronic human exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. This review will describe the use of QIVIVE methods in a high-throughput environment and the promise they hold in shaping chemical testing priorities and, potentially, high-throughput risk assessment strategies. © 2014 Elsevier Ireland Ltd.

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