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Kramer J.,Chantest | Obejero-Paz C.A.,Chantest | Myatt G.,Leadscope, Inc. | Kuryshev Y.A.,Chantest | And 3 more authors.
Scientific Reports | Year: 2013

Drug-induced block of the cardiac hERG (human Ether-à-go-go-Related Gene) potassium channel delays cardiac repolarization and increases the risk of Torsade de Pointes (TdP), a potentially lethal arrhythmia. A positive hERG assay has been embraced by regulators as a non-clinical predictor of TdP despite a discordance of about 30%. To test whether assaying concomitant block of multiple ion channels (Multiple Ion Channel Effects or MICE) improves predictivity we measured the concentration-responses of hERG, Nav1.5 and Cav1.2 currents for 32 torsadogenic and 23 non-torsadogenic drugs from multiple classes. We used automated gigaseal patch clamp instruments to provide higher throughput along with accuracy and reproducibility. Logistic regression models using the MICE assay showed a significant reduction in false positives (Type 1 errors) and false negatives (Type 2 errors) when compared to the hERG assay. The best MICE model only required a comparison of the blocking potencies between hERG and Cav1.2.


Wang Y.-J.,U.S. Food and Drug Administration | Wang Y.-J.,GlobalNet Services Inc. | Dou J.,U.S. Food and Drug Administration | Cross K.P.,Leadscope, Inc. | Valerio L.G.,U.S. Food and Drug Administration
Regulatory Toxicology and Pharmacology | Year: 2011

Black cohosh, red clover, hops, and chasteberry are botanicals commonly used to alleviate menopausal symptoms in the US, and are examined in this study as part of a FDA Office of Women's Health research collaboration to expand knowledge on the safety of these botanical products. Computational approaches using classic (quantitative) structure-activity relationships ((Q)SAR), probabilistic reasoning, machine learning methods, and human expert rule-based systems were employed to deliver human hepatobiliary adverse effect predictions. The objective is to profile and analyze constituents that are alerting for the human hepatobiliary adverse effects. Computational analysis of positively predicted constituents showed that common structural features contributing to the hepatobiliary adverse effect predictions contain phenolic, flavone, isoflavone, glucoside conjugated flavone and isoflavone, and 4-hydroxyacetophenone structures. Specifically, protocatechuic acid from black cohosh, benzofuran and 4-vinylphenol from chasteberry, and xanthohumol I from hops were botanical constituents predicted positive for liver toxicity endpoints and were also confirmed with literature findings. However, comparison between the estimated human exposure to these botanical constituents and the LOAEL and NOAEL in published animal liver toxicology studies for these constituents demonstrated varying margins of safety. This study will serve as regulatory decision support information for regulators at the FDA to help with the process of prioritizing chemicals for testing. © 2010.


Valerio L.G.,U.S. Food and Drug Administration | Cross K.P.,Leadscope, Inc.
Toxicology and Applied Pharmacology | Year: 2012

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure-activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. © 2012.


Grant
Agency: European Commission | Branch: FP7 | Program: CP-IP | Phase: HEALTH.2010.4.2-9-6 | Award Amount: 3.13M | Year: 2011

ToxBank establishes a dedicated web-based warehouse for toxicity data management and modelling, a gold standards compound database and repository of selected test compounds, and a reference resource for cells, cell lines and tissues of relevance for in vitro systemic toxicity research carried out across the FP7 HEALTH.2010.4.2.9 Alternative Testing Strategies SEURAT program. The project develops infrastructure and service functions to create a sustainable predictive toxicology support resource going beyond the lifetime of the program. The following activities will be carried out: a) Establishment of a dedicated web-based data warehouse The ToxBank Data Warehouse will establish a centralised compilation of data for systemic toxicity. Data generated under the research program and additional public data will be uploaded and integrated whenever possible into computerised models capable of predicting repeated-dose toxicity. b) Establishment of a database of test compounds The ToxBank Gold Compound Database will provide a high quality information resource servicing the selection and use of test compounds. Chemicals in this database will be supported by high-quality repeated-dose toxicity in vivo and in vitro data, property data and, whenever available, human adverse event and epidemiological data. Selected test compounds for training or validation, and standard operating procedures for data quality control, processing and analyses will be provided. c) Establishment of a repository for the selected test compounds The ToxBank Chemical Repository will ensure the availability of test compounds to program researchers accompanied by sample preparation, handling and analytical quality control procedures. d) Setting up of a cell and tissue banking information resource for in vitro toxicity testing ToxBank will establish a banking information resource for access to qualified cells, cell lines (including stem cells and stem cell lines) and tissues and reference materials to be used for in vitro predictive toxicology research and testing activities.


PubMed | Novartis, Toxicology Solutions, The VERTEX, Eli Lilly and Company and 16 more.
Type: | Journal: Regulatory toxicology and pharmacology : RTP | Year: 2016

The ICH M7 guideline describes a consistent approach to identify, categorize, and control DNA reactive, mutagenic, impurities in pharmaceutical products to limit the potential carcinogenic risk related to such impurities. This paper outlines a series of principles and procedures to consider when generating (Q)SAR assessments aligned with the ICH M7 guideline to be included in a regulatory submission. In the absence of adequate experimental data, the results from two complementary (Q)SAR methodologies may be combined to support an initial hazard classification. This may be followed by an assessment of additional information that serves as the basis for an expert review to support or refute the predictions. This paper elucidates scenarios where additional expert knowledge may be beneficial, what such an expert review may contain, and how the results and accompanying considerations may be documented. Furthermore, the use of these principles and procedures to yield a consistent and robust (Q)SAR-based argument to support impurity qualification for regulatory purposes is described in this manuscript.


Jennings P.,Innsbruck Medical University | Schwarz M.,University of Tübingen | Landesmann B.,EU Joint Research Centre | Maggioni S.,Instituto Of Ricerche Farmacologiche Mario Negri | And 4 more authors.
Archives of Toxicology | Year: 2014

There is an urgent need for the development of alternative methods to replace animal testing for the prediction of repeat dose chemical toxicity. To address this need, the European Commission and Cosmetics Europe have jointly funded a research program for ‘Safety Evaluation Ultimately Replacing Animal Testing.’ The goal of this program was the development of in vitro cellular systems and associated computational capabilities for the prediction of hepatic, cardiac, renal, neuronal, muscle, and skin toxicities. An essential component of this effort is the choice of appropriate reference compounds that can be used in the development and validation of assays. In this review, we focus on the selection of reference compounds for liver pathologies in the broad categories of cytotoxicity and lipid disorders. Mitochondrial impairment, oxidative stress, and apoptosis are considered under the category of cytotoxicity, while steatosis, cholestasis, and phospholipidosis are considered under the category of lipid dysregulation. We focused on four compound classes capable of initiating such events, i.e., chemically reactive compounds, compounds with specific cellular targets, compounds that modulate lipid regulatory networks, and compounds that disrupt the plasma membrane. We describe the molecular mechanisms of these compounds and the cellular response networks which they elicit. This information will be helpful to both improve our understanding of mode of action and help in the selection of appropriate mechanistic biomarkers, allowing us to progress the development of animal-free models with improved predictivity to the human situation. © 2014, Springer-Verlag Berlin Heidelberg.


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 150.00K | Year: 2010

The last two decades have produced dramatic technological advances in molecular biology and computer science. The NTP is evaluating how best to incorporate these advances into its research and testing strategies in order to broaden scientific knowledge of exposure-related disease mechanisms. To support these efforts, the goal of this contract is to develop a PC and/or Mac-based integrated prediction system to support environment toxicological assessments. The developer will need to provide a user-friendly interface that will integrate tools commonly available for in silico predictions to provide data and predictions relating to the potential toxicological effects of a chemical of interest. The user must be able to enter a query via a Chemical Abstracts Service Registry Number, the chemical name, a structure data file, a molfile, a IUPAC International Chemical Identifier (InChl), or a Simplified Molecular Input Line Entry Systems (SMILES) code. Users must be able to limit their search criteria at least by toxicological endpoint (e.g., carcinogenicity, genotoxicity, immunotoxicity, reproductive toxicity).


Trademark
Leadscope, Inc. | Date: 2011-12-13

Computer software for use in chemical compound identification, data visualization and manuals distributed as a unit therewith.


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 149.18K | Year: 2014

DESCRIPTION (provided by applicant): The field of green chemistry was established in order to reduce or even eliminate any negative impact from the introduction of new chemical products such as new pesticides, cosmetics, or drugs to human health or the environment. Unfortunately, current approaches for testing chemicals are expensive, time-consuming and require the use and sacrifice of hundreds of animals which makes their routine use throughout product development impractical. New approaches to testing chemicals are being developed that are faster and cheaper. These tests rely on assays such as in vitro tests and computer models, and by using a tiered battery of these new tests, it will be eventually possible to make decision on safety throughout the entirechemical RandD process. Different testing approaches should provide an appropriate confidence level at the different phases of product development. This information will be used to make design decisions that mitigate any identified risks. The objective


Grant
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase I | Award Amount: 149.46K | Year: 2016

DESCRIPTION provided by applicant In many situations it is critical to rapidly estimate the safety of new or existing chemicals For example in the event of a sudden unexpected exposure of a chemical such as with a chemical spill or a terrorist attack an emergency response is needed to determine if and how to mitigate any potential risk from the chemicalsandapos toxicity and to monitor this risk over time To support chemical research and development toxicity estimates are needed to ensure compounds are prioritized to minimize safety concerns In these cases it is not possible to generate traditional in vivo or even in vitro safety studies ue to the time needed to perform the experiments and interpret the data as well as the cost associated with performing these tests The only viable approach for generating this safety assessment is to use computational approaches that retrieve any existing historical data and in the absence of data calculate a prediction These computational or in silico tools are becoming increasingly relied upon in product design and for product prioritization yet they are not routinely used in regulatory decisions or emergency response situations This situation is now changing through the introduction of a regulatory guideline that permits the use of in silico tools for prediction of bacterial mutagenicity of pharmaceutical impurities the ICH M guidance The development of an appropriate guideline along with supporting standard operating procedures SOPs has been instrumental in the adoption of in silico tools in this area In this phase I proposal two SOPs will be generated to support the evaluation of genetic toxicity and acute toxicity They will outline how to use and interpret available data generate predictions based on Q SAR methodologies and read across approaches how to appropriately interpret prediction results assess a confidence level for the results and define the contents of an accompanying expert opinion These SOPs will be created and then published in peer reviewed publications by a working group of interested parties Using the principles and procedures outlined in these SOPs a single software application will be developed to rapidly identify data generate toxicity predictions assess prediction confidence and make recommendations on exposure thresholds New in silico methods will be developed including Q SAR models to predict GHS Globally Harmonized System of Classification and Labelling of Chemicals classifications for acute toxicity as well methods for prediction of mutagenicity and clastogenicity In phase II several new SOPs will be generated to cover the use and interpretation of in silico approaches for all common toxic effects necessary for a complete safety assessment Existing and newly developed models will be incorporated into to platform This tool will be commercialized and licensed as an application to support the rapid response to safety questions including emergency response situations and product design PUBLIC HEALTH RELEVANCE This project is focused on the computational hazard identification of chemicals with the aim to improve environmental public health and prevent disease by addressing the backlog of thousands of untested chemicals

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