Dataset Information

Httk: R Package for High-Throughput Toxicokinetics.

ABSTRACT: Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concentrations resulting from chemical exposure, and a "reverse dosimetry" approach can be used to predict exposure doses sufficient to cause tissue concentrations that have been identified as bioactive by high-throughput screening. We have created four toxicokinetic models within the R software package httk. These models are designed to be parameterized using high-throughput in vitro data (plasma protein binding and hepatic clearance), as well as structure-derived physicochemical properties and species-specific physiological data. The package contains tools for Monte Carlo sampling and reverse dosimetry along with functions for the analysis of concentration vs. time simulations. The package can currently use human in vitro data to make predictions for 553 chemicals in humans, rats, mice, dogs, and rabbits, including 94 pharmaceuticals and 415 ToxCast chemicals. For 67 of these chemicals, the package includes rat-specific in vitro data. This package is structured to be augmented with additional chemical data as they become available. Package httk enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.

SUBMITTER: Pearce RG

PROVIDER: S-EPMC6134854 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

httk: R Package for High-Throughput Toxicokinetics.

Pearce Robert G RG Setzer R Woodrow RW Strope Cory L CL Wambaugh John F JF Sipes Nisha S NS

Journal of statistical software 20170701 4

Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concentrations resulting from chemical exposure, and a "reverse dosimetry" approach can be used to predict exposure doses sufficient to cause tissue concentrations that have been identified as bioactive by high-throughput scree ...[more]

PMID: 30220889

Similar Datasets

Project description:Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure-Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure-property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

Project description:Computational methods are needed to more efficiently leverage data from in vitro cell-based models to predict what occurs within whole body systems after chemical insults. This study set out to test the hypothesis that in vitro high-throughput screening (HTS) data can more effectively predict in vivo biological responses when chemical disposition and toxicokinetic (TK) modeling are employed. In vitro HTS data from the Tox21 consortium were analyzed in concert with chemical disposition modeling to derive nominal, aqueous, and intracellular estimates of concentrations eliciting 50% maximal activity. In vivo biological responses were captured using rat liver transcriptomic data from the DrugMatrix and TG-Gates databases and evaluated for pathway enrichment. In vivo dosing data were translated to equivalent body concentrations using HTTK modeling. Random forest models were then trained and tested to predict in vivo pathway-level activity across 221 chemicals using in vitro bioactivity data and physicochemical properties as predictor variables, incorporating methods to address imbalanced training data resulting from high instances of inactivity. Model performance was quantified using the area under the receiver operator characteristic curve (AUC-ROC) and compared across pathways for different combinations of predictor variables. All models that included toxicokinetics were found to outperform those that excluded toxicokinetics. Biological interpretation of the model features revealed that rather than a direct mapping of in vitro assays to in vivo pathways, unexpected combinations of multiple in vitro assays predicted in vivo pathway-level activities. To demonstrate the utility of these findings, the highest-performing model was leveraged to make new predictions of in vivo biological responses across all biological pathways for remaining chemicals tested in Tox21 with adequate data coverage (n = 6617). These results demonstrate that, when chemical disposition and toxicokinetics are carefully considered, in vitro HT screening data can be used to effectively predict in vivo biological responses to chemicals.

Project description:BACKGROUND: Microsatellites (MSs) are DNA markers with high analytical power, which are widely used in population genetics, genetic mapping, and forensic studies. Currently available software solutions for high-throughput MS design (i) have shortcomings in detecting and distinguishing imperfect and perfect MSs, (ii) lack often necessary interactive design steps, and (iii) do not allow for the development of primers for multiplex amplifications. We present a set of new tools implemented as extensions to the STADEN package, which provides the backbone functionality for flexible sequence analysis workflows. The possibility to assemble overlapping reads into unique contigs (provided by the base functionality of the STADEN package) is important to avoid developing redundant markers, a feature missing from most other similar tools. RESULTS: Our extensions to the STADEN package provide the following functionality to facilitate microsatellite (and also minisatellite) marker design: The new modules (i) integrate the state-of-the-art tandem repeat detection and analysis software PHOBOS into workflows, (ii) provide two separate repeat detection steps - with different search criteria - one for masking repetitive regions during assembly of sequencing reads and the other for designing repeat-flanking primers for MS candidate loci, (iii) incorporate the widely used primer design program PRIMER3 into STADEN workflows, enabling the interactive design and visualization of flanking primers for microsatellites, and (iv) provide the functionality to find optimal locus- and primer pair combinations for multiplex primer design. Furthermore, our extensions include a module for storing analysis results in an SQLite database, providing a transparent solution for data access from within as well as from outside of the STADEN Package. CONCLUSION: The STADEN package is enhanced by our modules into a highly flexible, high-throughput, interactive tool for conventional and multiplex microsatellite marker design. It gives the user detailed control over the workflow, enabling flexible combinations of manual and automated analysis steps. The software is available under the OpenBSD License 12. The high efficiency of our automated marker design workflow has been confirmed in three microsatellite development projects.

Dataset Information

Httk: R Package for High-Throughput Toxicokinetics.

Publications

httk: R Package for High-Throughput Toxicokinetics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets