Health Datapalooza 2013: Datalab - Steven Edwards
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The document provides information about computational toxicology data resources available from the EPA's Office of Research and Development including the Aggregated Computational Toxicology Resource (ACToR), DSSTox Database, ExpoCast Database, ToxCast Database, ToxRefDB, and Tox21 Collaboration. It also lists exposure data resources such as the Consolidated Human Activity Database (CHAD), Consumer Product Chemical Profiles Database, ExpoCast, and Stochastic Human Exposure and Dose Simulation Model (SHEDS). Finally, it mentions toxicological data shared via the Comparative Toxicogenomics Database (CTD) from the NIEHS.
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Multiple regulatory bodies (EPA, ECHA, Health Canada) are currently tasked with prioritizing chemicals for data collection and risk assessments. These prioritization efforts are in response to regulatory mandates to identify chemicals for further assessment. We have developed a web-based application that enables a rapid, flexible and transparent prioritization process. The tool includes multiple data streams related to human and ecological hazard, exposure, and physicochemical properties (persistence and bioaccumulation). For human hazard, the data streams include quantitative points of departure (PODs) that are compiled from multiple sources such as EPA ToxRefDB, ECHA, COSMOS; estimated PODs from high-throughput in vitro screening assays and computational models; and qualitative measurements and predictions of specific endpoints (e.g., genotoxicity, endocrine activity). For ecological hazard, quantitative PODs are taken from the EPA ECOTOX database. Exposure information includes production volume, quantitative predictions using the EPA ExpoCast and SHEDS models, biomonitoring data, and qualitative information such as media occurrence, use profiles and likelihood of consumer and childhood exposures. The use of the tool is illustrated by prioritizing chemicals related to TSCA and the Safer Choice Ingredient List. The underpinning data streams for this application are already available in the EPA CompTox Chemistry Dashboard and have been repurposed to deliver this application. This is in keeping with our overarching software development methodology of providing multiple “building blocks” in the form of databases, web services and visualization components to deliver fit-for purpose applications to the relevant audiences. This abstract does not necessarily represent U.S. EPA policy.Development of a Tool for Systematic Integration of Traditional and New Appro...
Development of a Tool for Systematic Integration of Traditional and New Appro...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new CompTox Chemistry Dashboard and the developing architecture to support real-time property and toxicity endpoint prediction. This abstract does not reflect U.S. EPA policy.New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Slides from my talk at the ACS CINF Symposium on Chemical Nomenclature & Representation on 26 August 2019 in San Diego.
Abstract:
The first edition of the Beilstein Handbook of Organic Chemistry was published nearly 140 years ago. Electronic laboratory notebooks have been in use in chemistry for almost 20 years. And the life science industry still doesn't have a well-defined way of capturing and exchanging information about chemical reactions and relies on imprecise or vendor-specific data formats. Without a common language and structure to describe experiments, data integration is unnecessarily expensive and a significant part of published data has not been readily available for processing or analysis.
The Unified Data Model (UDM) project team aims to improve the situation. UDM is a collective effort of vendors and life science organizations to create an open, extendable and freely available reference model and data format for exchange of experimental information about compound synthesis and testing. Run under the umbrella of the Pistoia Alliance, the project team has published two releases of the UDM data format and it is expected that the model will continue to be improved as demand stipulates working with the Pistoia FAIR data implementation by industry community.UDM (Unified Data Model) - Enabling Exchange of Comprehensive Reaction Inform...
UDM (Unified Data Model) - Enabling Exchange of Comprehensive Reaction Inform...Frederik van den Broek
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are advancing the identification of emerging contaminants in environmental matrices, improving the means by which exposure analyses can be conducted. However, confidence in structure identification of unknowns in NTA presents challenges to analytical chemists. Structure identification requires integration of complementary data types such as reference databases, fragmentation prediction tools, and retention time prediction models. The goal of this research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemistry Dashboard, an open chemistry resource and web application containing data for ~760,000 substances. Rank-ordering the number of sources associated with chemical records within the Dashboard (Data Source Ranking) improves the identification of unknowns by bringing the most likely candidate structures to the top of a search results list. Database searching has been further optimized with the generation of MS-Ready Structures. MS-Ready structures are de-salted, stripped of stereochemistry, and mixture separated to replicate the form of a chemical observed via HRMS. Functionality to conduct batch searching of molecular formulae and monoisotopic masses was designed and released to improve searching efforts. Finally, a scoring-based identification scheme was developed, optimized, and surfaced via the Dashboard using multiple data streams contained within the database underlying the Dashboard. The scoring-based identification scheme improved the identification of unknowns over previous efforts using data source ranking alone. Combining these steps within an open chemistry resource provides a freely available software tool for structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...
Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Identification of unknowns in mass spectrometry based non-targeted analyses (NTA) requires the integration of complementary pieces of data to arrive at a confident, consensus structure. Researchers use chemical reference databases, spectral matching, fragment prediction tools, retention time prediction tools, and a variety of other data to arrive at tentative, probable, and confirmed, if possible, identifications. With the diverse, robust data contained within the US EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov), the goal of this research is to identify and implement a harmonized identification tool and workflow using previously generated chemistry data. Data has been compiled from product use, functional use prediction models, environmental media occurrence prediction models, and PubMed references, among other sources. We will report on our development of a visualization tool whereby users can visualize the relative contribution of identification-based metrics on a list of candidate structures and observe the greatest likelihood of occurrence. These data and visualization tools support NTA identification via the Dashboard and demonstrate an open, accessible tool for all users of HRMS data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification by Mass Spectrometry Non-Targeted Analysis using the...
Structure identification by Mass Spectrometry Non-Targeted Analysis using the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The EPA CompTox Chemistry Dashboard provides access to data associated with ~760,000 chemical substances. The available data includes experimental and predicted physicochemical properties, environmental fate and transport data, in vivo and in silico toxicity data, in vitro bioassay data, exposure data and a variety of other types of information. The data are under continuous expansion and curation and the experimental data have been used to develop QSAR and QSPR models. A number of these models are available via a web interface so that users can submit a chemical structure and predict properties in real time. The dashboard also provides access to pre-compiled chemical lists and categories, including pesticides, and chemicals detected in the environment via non-targeted mass spectrometry analysis. The data are searchable using chemical identifiers (systematic names, trade names, CAS Registry Numbers), by structure, mass and formula. Batch searches allow for data associated with thousands of chemicals to be obtained in a few seconds, with just a few button clicks, and downloaded to the desktop. This presentation will provide an overview of the Dashboard and its applications to accessing source data associated with agriculturally related chemicals. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Web-based access to experimental and predicted data for environmental fate, t...
Web-based access to experimental and predicted data for environmental fate, t...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Chemical risk assessment is both time-consuming and difficult because it requires the assembly of data for chemicals generally distributed across multiple sources. The US EPA CompTox Chemistry Dashboard is a publicly accessible web-based application providing access to various data streams on ~760,000 chemical substances. These data include experimental and predicted physicochemical property data, bioassay screening data associated with the ToxCast program, consumer product and functional use information and a myriad of related data of value to environmental scientists and toxicologists. At this stage of development, the public dashboard provides access to almost 20 predicted physicochemical and environmental fate and transport endpoints with full transparency in terms of model performance. Experimental and predicted human and ecological toxicity data are also available, as are in vitro to in vivo extrapolation dosimetry predictions and predicted exposure and functional use. In parallel to the CompTox Chemistry Dashboard we are developing RapidTox, a web-based application that enables a rapid, flexible and transparent prioritization process for sets of chemicals using several previously used workflows focused on scoring of traditional risk metrics and the inclusion of alternative hazard and exposure estimates. This presentation will give an overview of the CompTox Chemistry Dashboard, RapidTox, our approaches to building transparent and open prediction models, and our efforts to provide access to real time predictions. This abstract does not necessarily represent U.S. EPA policy.US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...
US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
In the domain of chemistry one of the greatest benefits to publishing research is that data can be shared. Unfortunately, the vast majority of chemical structure data associated with scientific publications remain locked up in document form, primarily in PDF files or trapped on webpages. Despite the explosive growth of online chemical databases and the overall maturity of cheminformatics platforms, many barriers stifle the exchange of chemical structures via publications. These challenges include incomplete support by accepted standards (especially InChI) for advanced stereochemistry, organometallic compounds and generic “Markush” representations, the difference between human-readable and computer-readable forms of data, and challenges with the computer representation of chemical structures. To address these obstacles to chemical structure sharing, US EPA National Center for Computational Toxicology scientists are using a combination of cheminformatics applications and online repositories to distribute chemical structure data associated with their publications. This presentation will describe how EPA-NCCT chemical structure data that is amenable to indexing and distribution are shared and highlight the benefit of open data sharing for modeling, data integration, and increasing research impact. This abstract does not reflect U.S. EPA policy.Sharing chemical structures with peer reviewed publications
Sharing chemical structures with peer reviewed publications US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Recommandé
Multiple regulatory bodies (EPA, ECHA, Health Canada) are currently tasked with prioritizing chemicals for data collection and risk assessments. These prioritization efforts are in response to regulatory mandates to identify chemicals for further assessment. We have developed a web-based application that enables a rapid, flexible and transparent prioritization process. The tool includes multiple data streams related to human and ecological hazard, exposure, and physicochemical properties (persistence and bioaccumulation). For human hazard, the data streams include quantitative points of departure (PODs) that are compiled from multiple sources such as EPA ToxRefDB, ECHA, COSMOS; estimated PODs from high-throughput in vitro screening assays and computational models; and qualitative measurements and predictions of specific endpoints (e.g., genotoxicity, endocrine activity). For ecological hazard, quantitative PODs are taken from the EPA ECOTOX database. Exposure information includes production volume, quantitative predictions using the EPA ExpoCast and SHEDS models, biomonitoring data, and qualitative information such as media occurrence, use profiles and likelihood of consumer and childhood exposures. The use of the tool is illustrated by prioritizing chemicals related to TSCA and the Safer Choice Ingredient List. The underpinning data streams for this application are already available in the EPA CompTox Chemistry Dashboard and have been repurposed to deliver this application. This is in keeping with our overarching software development methodology of providing multiple “building blocks” in the form of databases, web services and visualization components to deliver fit-for purpose applications to the relevant audiences. This abstract does not necessarily represent U.S. EPA policy.Development of a Tool for Systematic Integration of Traditional and New Appro...
Development of a Tool for Systematic Integration of Traditional and New Appro...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new CompTox Chemistry Dashboard and the developing architecture to support real-time property and toxicity endpoint prediction. This abstract does not reflect U.S. EPA policy.New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Slides from my talk at the ACS CINF Symposium on Chemical Nomenclature & Representation on 26 August 2019 in San Diego.
Abstract:
The first edition of the Beilstein Handbook of Organic Chemistry was published nearly 140 years ago. Electronic laboratory notebooks have been in use in chemistry for almost 20 years. And the life science industry still doesn't have a well-defined way of capturing and exchanging information about chemical reactions and relies on imprecise or vendor-specific data formats. Without a common language and structure to describe experiments, data integration is unnecessarily expensive and a significant part of published data has not been readily available for processing or analysis.
The Unified Data Model (UDM) project team aims to improve the situation. UDM is a collective effort of vendors and life science organizations to create an open, extendable and freely available reference model and data format for exchange of experimental information about compound synthesis and testing. Run under the umbrella of the Pistoia Alliance, the project team has published two releases of the UDM data format and it is expected that the model will continue to be improved as demand stipulates working with the Pistoia FAIR data implementation by industry community.UDM (Unified Data Model) - Enabling Exchange of Comprehensive Reaction Inform...
UDM (Unified Data Model) - Enabling Exchange of Comprehensive Reaction Inform...Frederik van den Broek
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are advancing the identification of emerging contaminants in environmental matrices, improving the means by which exposure analyses can be conducted. However, confidence in structure identification of unknowns in NTA presents challenges to analytical chemists. Structure identification requires integration of complementary data types such as reference databases, fragmentation prediction tools, and retention time prediction models. The goal of this research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemistry Dashboard, an open chemistry resource and web application containing data for ~760,000 substances. Rank-ordering the number of sources associated with chemical records within the Dashboard (Data Source Ranking) improves the identification of unknowns by bringing the most likely candidate structures to the top of a search results list. Database searching has been further optimized with the generation of MS-Ready Structures. MS-Ready structures are de-salted, stripped of stereochemistry, and mixture separated to replicate the form of a chemical observed via HRMS. Functionality to conduct batch searching of molecular formulae and monoisotopic masses was designed and released to improve searching efforts. Finally, a scoring-based identification scheme was developed, optimized, and surfaced via the Dashboard using multiple data streams contained within the database underlying the Dashboard. The scoring-based identification scheme improved the identification of unknowns over previous efforts using data source ranking alone. Combining these steps within an open chemistry resource provides a freely available software tool for structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...
Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Identification of unknowns in mass spectrometry based non-targeted analyses (NTA) requires the integration of complementary pieces of data to arrive at a confident, consensus structure. Researchers use chemical reference databases, spectral matching, fragment prediction tools, retention time prediction tools, and a variety of other data to arrive at tentative, probable, and confirmed, if possible, identifications. With the diverse, robust data contained within the US EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov), the goal of this research is to identify and implement a harmonized identification tool and workflow using previously generated chemistry data. Data has been compiled from product use, functional use prediction models, environmental media occurrence prediction models, and PubMed references, among other sources. We will report on our development of a visualization tool whereby users can visualize the relative contribution of identification-based metrics on a list of candidate structures and observe the greatest likelihood of occurrence. These data and visualization tools support NTA identification via the Dashboard and demonstrate an open, accessible tool for all users of HRMS data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification by Mass Spectrometry Non-Targeted Analysis using the...
Structure identification by Mass Spectrometry Non-Targeted Analysis using the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The EPA CompTox Chemistry Dashboard provides access to data associated with ~760,000 chemical substances. The available data includes experimental and predicted physicochemical properties, environmental fate and transport data, in vivo and in silico toxicity data, in vitro bioassay data, exposure data and a variety of other types of information. The data are under continuous expansion and curation and the experimental data have been used to develop QSAR and QSPR models. A number of these models are available via a web interface so that users can submit a chemical structure and predict properties in real time. The dashboard also provides access to pre-compiled chemical lists and categories, including pesticides, and chemicals detected in the environment via non-targeted mass spectrometry analysis. The data are searchable using chemical identifiers (systematic names, trade names, CAS Registry Numbers), by structure, mass and formula. Batch searches allow for data associated with thousands of chemicals to be obtained in a few seconds, with just a few button clicks, and downloaded to the desktop. This presentation will provide an overview of the Dashboard and its applications to accessing source data associated with agriculturally related chemicals. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Web-based access to experimental and predicted data for environmental fate, t...
Web-based access to experimental and predicted data for environmental fate, t...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Chemical risk assessment is both time-consuming and difficult because it requires the assembly of data for chemicals generally distributed across multiple sources. The US EPA CompTox Chemistry Dashboard is a publicly accessible web-based application providing access to various data streams on ~760,000 chemical substances. These data include experimental and predicted physicochemical property data, bioassay screening data associated with the ToxCast program, consumer product and functional use information and a myriad of related data of value to environmental scientists and toxicologists. At this stage of development, the public dashboard provides access to almost 20 predicted physicochemical and environmental fate and transport endpoints with full transparency in terms of model performance. Experimental and predicted human and ecological toxicity data are also available, as are in vitro to in vivo extrapolation dosimetry predictions and predicted exposure and functional use. In parallel to the CompTox Chemistry Dashboard we are developing RapidTox, a web-based application that enables a rapid, flexible and transparent prioritization process for sets of chemicals using several previously used workflows focused on scoring of traditional risk metrics and the inclusion of alternative hazard and exposure estimates. This presentation will give an overview of the CompTox Chemistry Dashboard, RapidTox, our approaches to building transparent and open prediction models, and our efforts to provide access to real time predictions. This abstract does not necessarily represent U.S. EPA policy.US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...
US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
In the domain of chemistry one of the greatest benefits to publishing research is that data can be shared. Unfortunately, the vast majority of chemical structure data associated with scientific publications remain locked up in document form, primarily in PDF files or trapped on webpages. Despite the explosive growth of online chemical databases and the overall maturity of cheminformatics platforms, many barriers stifle the exchange of chemical structures via publications. These challenges include incomplete support by accepted standards (especially InChI) for advanced stereochemistry, organometallic compounds and generic “Markush” representations, the difference between human-readable and computer-readable forms of data, and challenges with the computer representation of chemical structures. To address these obstacles to chemical structure sharing, US EPA National Center for Computational Toxicology scientists are using a combination of cheminformatics applications and online repositories to distribute chemical structure data associated with their publications. This presentation will describe how EPA-NCCT chemical structure data that is amenable to indexing and distribution are shared and highlight the benefit of open data sharing for modeling, data integration, and increasing research impact. This abstract does not reflect U.S. EPA policy.Sharing chemical structures with peer reviewed publications
Sharing chemical structures with peer reviewed publications US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Cheminformatics methods form an essential basis for providing analytical scientists with access to data, algorithms and workflows. There are an increasing number of free online databases (compound databases, spectral libraries, data repositories) and a rich collection of software approaches that can be used to support automated structure verification and elucidation, specifically for Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS). This presentation will provide an overview of freely available data, tools, databases and approaches available to support chemical structure verification and elucidation and highlight some of the known issues regarding data quality and suggest approaches for resolving some of the issues. The importance of structure and spectral standards for data exchange will be discussed, especially with regard to how spectral data can be made openly available to the community via online tools and through scientific publishing. This work does not necessarily reflect U.S. EPA policy.Overview of open resources to support automated structure verification and e...
Overview of open resources to support automated structure verification and e...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted and suspect screening studies using high resolution mass spectrometry (HRMS) have revolutionized the detection of chemicals in complex matrices. However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. The US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov) to address challenges related to data processing and analysis in HRMS. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will introduce the tools and combined workflow, including visualization and access via the CompTox Chemicals Dashboard. These tools, data, and visualization approaches within an open chemistry resource provides a publicly available software tool to support structure identification and non-targeted analyses. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Chemical identification of unknowns in high resolution mass spectrometry usin...
Chemical identification of unknowns in high resolution mass spectrometry usin...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Read-across, a popular data gap filling technique, traditionally relies on a thorough expert assessment. This approach can lead to inconsistent predictions, has limitations in terms of the numbers of chemicals that can be evaluated and offers little insight into the generalizability of the approach or its performance. We sought to evaluate the baseline performance of read-across for a large set of chemicals in a systematic, objective and reproducible manner and to provide quantitative measures of uncertainty for the predictions derived. The approach developed, generalized read-across (GenRA), relies on chemical descriptor information and/or in vitro bioactivity data (from ToxCast high throughput screening data) to derive read-across predictions of effects observed in in vivo repeat-dose toxicity studies. A web-based GenRA tool was then developed anchored around the established category workflow and a dynamic grid interface structure. The default starting point is identifying source analogues with associated in vivo data on the basis of chemical fingerprints. The next step is to analyze the scope and quantity of available data (both in vitro and in vivo). The third step generates a data matrix in order to evaluate the analogues – in terms of their consistency and concordance of effects across the different toxicity effects. The final steps involve generating a GenRA prediction and exporting the predictions. Here we describe the functionality and features of the GenRA web application which has recently been released as a new feature in the US EPA CompTox Chemistry Dashboard. Users are able to search the dashboard for a substance of interest, browse available information including toxicity information and then derive GenRA predictions. GenRA offers a novel and practical means of being able to perform objective read-across that can be helpful in screening level hazard assessments. This abstract does not necessarily represent U.S. EPA policy.Translating research into practical tools: A case study of GenRA, a new read...
Translating research into practical tools: A case study of GenRA, a new read...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The increasing popularity of high mass accuracy non-target mass spectrometry methods has yielded extensive identification efforts based on chemical compound databases. Candidate structures are often retrieved with either exact mass or molecular formula from large resources such as PubChem, ChemSpider or the EPA CompTox Chemistry Dashboard. Additional data (e.g. fragmentation, physicochemical properties, reference and data source information) is then used to select potential candidates, depending on the experimental context. However, these strategies require the presence of substances of interest in these compound databases, which is often not the case as no database can be fully inclusive. A prominent example with clear data gaps are surfactants, used in many products in our daily lives, yet often absent as discrete structures in compound databases. Linear alkylbenzene sulfonates (LAS) are a common, high use and high priority surfactant class that have highly complex transformation behaviour in wastewater. Despite extensive reports in the environmental literature, few of the LAS and none of the related transformation products were reported in any compound databases during an investigation into Swiss wastewater effluents, despite these forming the most intense signals. The LAS surfactant class will be used to demonstrate how the coupling of environmental observations with high resolution mass spectrometry and detailed literature data (expert knowledge) on the transformation of these species can be used to progressively “fill the gaps” in compound databases. The LAS and their transformation products have been added to the CompTox Chemistry Dashboard (https://comptox.epa.gov/) using a combination of “representative structures” and “related structures” starting from the structural information contained in the literature. By adding this information into a centralized open resource, future environmental investigations can now profit from the expert knowledge previously scattered throughout the literature. Note: This abstract does not reflect US EPA policy.Adding complex expert knowledge into chemical database and transforming surfa...
Adding complex expert knowledge into chemical database and transforming surfa...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted analysis (NTA) uses high-resolution mass spectrometry to better understand the identity of a wide variety of chemicals present in environmental samples (and other matrices). However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. Analysis of the resultant mass spectrometry information relies on cheminformatics to identify and rank chemicals and the US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) to address challenges related to this analysis. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will review how the CompTox Chemicals Dashboard via its flexible search capabilities, rich data for ~900,000 chemical substances, and visualization approaches within this open chemistry resource provides a freely available software tool to support structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Non-targeted analysis supported by data and cheminformatics delivered via the...
Non-targeted analysis supported by data and cheminformatics delivered via the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The internet has changed the way we access chemistry data as well as providing access to data that can quickly proliferate and becomes referenceable. Web access to chemical structures and their integration with biological data has become massively enabling with numbers for UniChem, PubChem and ChemSpider reaching 157, 97 and 71 million respectively (at the time of writing). A range of specialist databases small enough to be curated have stand-alone utility and synergies when integrated into the larger collections. These include DrugBank, BindingDB, ChEBI, and many others. Databases of any size have inherent quality challenges but at large scale various forms of “noise” accumulate to problematic levels. The unfortunate consequence is that “bigger gets worse”. This is particularly associated with large uncurated submissions from vendors and automated document extractions (even though these are high-value). Virtual enumerations and circularity between overlapping sources add to the problem. As a result of some of the noise in the larger databases the value becomes highly dependent on the specific applications. An example includes using the databases to support non-targeted analysis. This presentation covers examples of these noise and quality issues and suggests at least some options to ameliorate the problem. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency. Does bigger mean better in the world of chemistry databases?
Does bigger mean better in the world of chemistry databases? US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
EPA’s National Center for Computational Toxicology is developing automated workflows for curating large databases within the DSSTox project and for providing accurate linkages of data to chemical structures, exposure, and hazard data. The data are made available via the EPA’s CompTox Chemicals Dashboard1 (https://comptox.epa.gov/dashboard), a publicly accessible website providing access to data for ~875,000 chemical substances, the majority of these represented with chemical structures. The web application delivers a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data, and linkages to a growing list of literature, toxicology, and analytical chemistry websites. The dashboard version 3:March 2019 release includes support for the invitroDBv3.1 data release2 and includes new functionality to interact with all ToxCast and Tox21 data with the intention of replacing the previously available EDSP21 and ToxCast dashboards. The previous dashboards will be retired in summer 2019.
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine Assays
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine AssaysUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Access to both experimental and predicted environmental fate and transport data is facilitated by the US-EPA CompTox Chemicals Dashboard. Providing access to various types of data associated with ~900,000 chemical substances, the dashboard is a web-based application supporting computational toxicology research in environmental chemistry. When experimental physicochemical and fate and transport data are not available, QSAR models developed using curated datasets are used for the prediction of properties. These include: bioaccumulation factors, bioconcentration factors, and biodegradation and fish biotransformation half-lives. For chemicals of interest that are not already registered in the dashboard real-time predictions based on structural inputs are available. This presentation will provide an overview of the dashboard with a focus on the availability of environmental fate and transport data, access to real time predictions, and our ongoing efforts to harvest and curate available experimental data from the literature and online databases. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.US-EPA CompTox Chemicals Dashboard providing access to experimental and predi...
US-EPA CompTox Chemicals Dashboard providing access to experimental and predi...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program utilizes computational and data-driven approaches that integrate chemistry, exposure and biological data to help characterize potential risks from chemical exposure. The National Center for Computational Toxicology (NCCT) has measured, assembled and delivered an enormous quantity and diversity of data for the environmental sciences, including high-throughput in vitro screening data, in vivo and functional use data, exposure models and chemical databases with associated properties. The CompTox Chemicals Dashboard website provides access to data associated with ~900,000 chemical substances. New data are added on an ongoing basis, including the registration of new and emerging chemicals, data extracted from the literature, chemicals studied in our labs, and data of interest to specific research projects at the EPA. Hazard and exposure data have been assembled from a large number of public databases and as a result the dashboard surfaces hundreds of thousands of data points. Other data includes experimental and predicted physicochemical property data, in vitro bioassay data for over 4000 chemicals and 2000 assays, and millions of chemical identifiers (names and CAS Registry Numbers) to facilitate searching. Other integrated modules include an interactive read-across module, real-time physicochemical and toxicity endpoint prediction and an integrated search to PubMed. This presentation will provide an overview of the latest release of the CompTox Chemicals Dashboard and how it has developed into an integrated data hub for environmental data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.US-EPA CompTox Chemicals Dashboard – integrating chemistry and biology data t...
US-EPA CompTox Chemicals Dashboard – integrating chemistry and biology data t...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Contenu connexe
Tendances
Cheminformatics methods form an essential basis for providing analytical scientists with access to data, algorithms and workflows. There are an increasing number of free online databases (compound databases, spectral libraries, data repositories) and a rich collection of software approaches that can be used to support automated structure verification and elucidation, specifically for Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS). This presentation will provide an overview of freely available data, tools, databases and approaches available to support chemical structure verification and elucidation and highlight some of the known issues regarding data quality and suggest approaches for resolving some of the issues. The importance of structure and spectral standards for data exchange will be discussed, especially with regard to how spectral data can be made openly available to the community via online tools and through scientific publishing. This work does not necessarily reflect U.S. EPA policy.Overview of open resources to support automated structure verification and e...
Overview of open resources to support automated structure verification and e...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted and suspect screening studies using high resolution mass spectrometry (HRMS) have revolutionized the detection of chemicals in complex matrices. However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. The US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov) to address challenges related to data processing and analysis in HRMS. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will introduce the tools and combined workflow, including visualization and access via the CompTox Chemicals Dashboard. These tools, data, and visualization approaches within an open chemistry resource provides a publicly available software tool to support structure identification and non-targeted analyses. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Chemical identification of unknowns in high resolution mass spectrometry usin...
Chemical identification of unknowns in high resolution mass spectrometry usin...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Read-across, a popular data gap filling technique, traditionally relies on a thorough expert assessment. This approach can lead to inconsistent predictions, has limitations in terms of the numbers of chemicals that can be evaluated and offers little insight into the generalizability of the approach or its performance. We sought to evaluate the baseline performance of read-across for a large set of chemicals in a systematic, objective and reproducible manner and to provide quantitative measures of uncertainty for the predictions derived. The approach developed, generalized read-across (GenRA), relies on chemical descriptor information and/or in vitro bioactivity data (from ToxCast high throughput screening data) to derive read-across predictions of effects observed in in vivo repeat-dose toxicity studies. A web-based GenRA tool was then developed anchored around the established category workflow and a dynamic grid interface structure. The default starting point is identifying source analogues with associated in vivo data on the basis of chemical fingerprints. The next step is to analyze the scope and quantity of available data (both in vitro and in vivo). The third step generates a data matrix in order to evaluate the analogues – in terms of their consistency and concordance of effects across the different toxicity effects. The final steps involve generating a GenRA prediction and exporting the predictions. Here we describe the functionality and features of the GenRA web application which has recently been released as a new feature in the US EPA CompTox Chemistry Dashboard. Users are able to search the dashboard for a substance of interest, browse available information including toxicity information and then derive GenRA predictions. GenRA offers a novel and practical means of being able to perform objective read-across that can be helpful in screening level hazard assessments. This abstract does not necessarily represent U.S. EPA policy.Translating research into practical tools: A case study of GenRA, a new read...
Translating research into practical tools: A case study of GenRA, a new read...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The increasing popularity of high mass accuracy non-target mass spectrometry methods has yielded extensive identification efforts based on chemical compound databases. Candidate structures are often retrieved with either exact mass or molecular formula from large resources such as PubChem, ChemSpider or the EPA CompTox Chemistry Dashboard. Additional data (e.g. fragmentation, physicochemical properties, reference and data source information) is then used to select potential candidates, depending on the experimental context. However, these strategies require the presence of substances of interest in these compound databases, which is often not the case as no database can be fully inclusive. A prominent example with clear data gaps are surfactants, used in many products in our daily lives, yet often absent as discrete structures in compound databases. Linear alkylbenzene sulfonates (LAS) are a common, high use and high priority surfactant class that have highly complex transformation behaviour in wastewater. Despite extensive reports in the environmental literature, few of the LAS and none of the related transformation products were reported in any compound databases during an investigation into Swiss wastewater effluents, despite these forming the most intense signals. The LAS surfactant class will be used to demonstrate how the coupling of environmental observations with high resolution mass spectrometry and detailed literature data (expert knowledge) on the transformation of these species can be used to progressively “fill the gaps” in compound databases. The LAS and their transformation products have been added to the CompTox Chemistry Dashboard (https://comptox.epa.gov/) using a combination of “representative structures” and “related structures” starting from the structural information contained in the literature. By adding this information into a centralized open resource, future environmental investigations can now profit from the expert knowledge previously scattered throughout the literature. Note: This abstract does not reflect US EPA policy.Adding complex expert knowledge into chemical database and transforming surfa...
Adding complex expert knowledge into chemical database and transforming surfa...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted analysis (NTA) uses high-resolution mass spectrometry to better understand the identity of a wide variety of chemicals present in environmental samples (and other matrices). However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. Analysis of the resultant mass spectrometry information relies on cheminformatics to identify and rank chemicals and the US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) to address challenges related to this analysis. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will review how the CompTox Chemicals Dashboard via its flexible search capabilities, rich data for ~900,000 chemical substances, and visualization approaches within this open chemistry resource provides a freely available software tool to support structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Non-targeted analysis supported by data and cheminformatics delivered via the...
Non-targeted analysis supported by data and cheminformatics delivered via the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The internet has changed the way we access chemistry data as well as providing access to data that can quickly proliferate and becomes referenceable. Web access to chemical structures and their integration with biological data has become massively enabling with numbers for UniChem, PubChem and ChemSpider reaching 157, 97 and 71 million respectively (at the time of writing). A range of specialist databases small enough to be curated have stand-alone utility and synergies when integrated into the larger collections. These include DrugBank, BindingDB, ChEBI, and many others. Databases of any size have inherent quality challenges but at large scale various forms of “noise” accumulate to problematic levels. The unfortunate consequence is that “bigger gets worse”. This is particularly associated with large uncurated submissions from vendors and automated document extractions (even though these are high-value). Virtual enumerations and circularity between overlapping sources add to the problem. As a result of some of the noise in the larger databases the value becomes highly dependent on the specific applications. An example includes using the databases to support non-targeted analysis. This presentation covers examples of these noise and quality issues and suggests at least some options to ameliorate the problem. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency. Does bigger mean better in the world of chemistry databases?
Does bigger mean better in the world of chemistry databases? US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
EPA’s National Center for Computational Toxicology is developing automated workflows for curating large databases within the DSSTox project and for providing accurate linkages of data to chemical structures, exposure, and hazard data. The data are made available via the EPA’s CompTox Chemicals Dashboard1 (https://comptox.epa.gov/dashboard), a publicly accessible website providing access to data for ~875,000 chemical substances, the majority of these represented with chemical structures. The web application delivers a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data, and linkages to a growing list of literature, toxicology, and analytical chemistry websites. The dashboard version 3:March 2019 release includes support for the invitroDBv3.1 data release2 and includes new functionality to interact with all ToxCast and Tox21 data with the intention of replacing the previously available EDSP21 and ToxCast dashboards. The previous dashboards will be retired in summer 2019.
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine Assays
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine AssaysUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Access to both experimental and predicted environmental fate and transport data is facilitated by the US-EPA CompTox Chemicals Dashboard. Providing access to various types of data associated with ~900,000 chemical substances, the dashboard is a web-based application supporting computational toxicology research in environmental chemistry. When experimental physicochemical and fate and transport data are not available, QSAR models developed using curated datasets are used for the prediction of properties. These include: bioaccumulation factors, bioconcentration factors, and biodegradation and fish biotransformation half-lives. For chemicals of interest that are not already registered in the dashboard real-time predictions based on structural inputs are available. This presentation will provide an overview of the dashboard with a focus on the availability of environmental fate and transport data, access to real time predictions, and our ongoing efforts to harvest and curate available experimental data from the literature and online databases. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.US-EPA CompTox Chemicals Dashboard providing access to experimental and predi...
US-EPA CompTox Chemicals Dashboard providing access to experimental and predi...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program utilizes computational and data-driven approaches that integrate chemistry, exposure and biological data to help characterize potential risks from chemical exposure. The National Center for Computational Toxicology (NCCT) has measured, assembled and delivered an enormous quantity and diversity of data for the environmental sciences, including high-throughput in vitro screening data, in vivo and functional use data, exposure models and chemical databases with associated properties. The CompTox Chemicals Dashboard website provides access to data associated with ~900,000 chemical substances. New data are added on an ongoing basis, including the registration of new and emerging chemicals, data extracted from the literature, chemicals studied in our labs, and data of interest to specific research projects at the EPA. Hazard and exposure data have been assembled from a large number of public databases and as a result the dashboard surfaces hundreds of thousands of data points. Other data includes experimental and predicted physicochemical property data, in vitro bioassay data for over 4000 chemicals and 2000 assays, and millions of chemical identifiers (names and CAS Registry Numbers) to facilitate searching. Other integrated modules include an interactive read-across module, real-time physicochemical and toxicity endpoint prediction and an integrated search to PubMed. This presentation will provide an overview of the latest release of the CompTox Chemicals Dashboard and how it has developed into an integrated data hub for environmental data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.US-EPA CompTox Chemicals Dashboard – integrating chemistry and biology data t...
US-EPA CompTox Chemicals Dashboard – integrating chemistry and biology data t...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Tendances (20)
Overview of open resources to support automated structure verification and e...
Overview of open resources to support automated structure verification and e...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Chemical identification of unknowns in high resolution mass spectrometry usin...
Chemical identification of unknowns in high resolution mass spectrometry usin...
Translating research into practical tools: A case study of GenRA, a new read...
Translating research into practical tools: A case study of GenRA, a new read...
Adding complex expert knowledge into chemical database and transforming surfa...
Adding complex expert knowledge into chemical database and transforming surfa...
Automate your literature monitoring for more effective pharmacovigilance
Automate your literature monitoring for more effective pharmacovigilance
Non-targeted analysis supported by data and cheminformatics delivered via the...
Non-targeted analysis supported by data and cheminformatics delivered via the...
Does bigger mean better in the world of chemistry databases?
Does bigger mean better in the world of chemistry databases?
Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine Assays
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine Assays
US-EPA CompTox Chemicals Dashboard providing access to experimental and predi...
US-EPA CompTox Chemicals Dashboard providing access to experimental and predi...
Artificial Intelligence in Life Sciences and Agriculture.
Artificial Intelligence in Life Sciences and Agriculture.
US-EPA CompTox Chemicals Dashboard – integrating chemistry and biology data t...
US-EPA CompTox Chemicals Dashboard – integrating chemistry and biology data t...
An open workflow to generate "MS-Ready" structures and improve non-targeted m...
An open workflow to generate "MS-Ready" structures and improve non-targeted m...
Similaire à Health Datapalooza 2013: Datalab - Steven Edwards
Information and data on chemicals is used by scientists to evaluate potential health and ecological risks due to environmental exposures. EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov) helps evaluate the safety of chemicals by providing public access to a variety of information on over 760,000 chemicals. Within the Dashboard, users can access chemical structures, chemistry information, toxicity data, hazard data, exposure information, and additional links to relevant websites and applications. These data are compiled from sources including EPA’s computational toxicology research databases, from public domain databases and with collaborators across the world. Chemical lists have been added that provide access to various classes of chemicals and project-based datasets are under constant development. Specific functionality has been delivered within the Dashboard to support mass spectrometry including “MS-ready forms” of chemical substances that would be detectable by mass spectrometry. Workflows have been developed to assist in candidate identification and have now been proven with multiple published studies. An integration path between the dashboard and MetFrag has also been established to provide users the significant benefits resulting from the marriage between the two applications. The datasets underpinning the dashboard are freely available (https://comptox.epa.gov/dashboard/downloads) for integration into third party databases. This presentation will provide an overview of the available data types and functionality of the dashboard prior to examining how it is developing to support mass spectrometry based analyses within the agency and for the community in general. This will include a review of our research efforts to enhance the dashboard using in silico MS/MS fragmentation prediction for spectral matching. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.CompTox Chemicals Dashboard: Data and tools to support chemical and environme...
CompTox Chemicals Dashboard: Data and tools to support chemical and environme...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new publicly-accessible CompTox Dashboard as the first application built on our newly developed architecture. This abstract does not reflect U.S. EPA policy. Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data driven approaches that integrate chemistry, exposure and biological data. As an outcome of these efforts the National Center for Computational Toxicology (NCCT) has measured, assembled and delivered an enormous quantity and diversity of data for the environmental sciences including high-throughput in vitro screening data, in vivo and functional use data, exposure models and chemical databases with associated properties. A series of software applications and databases have been produced over the past decade to deliver these data but recent developments have focused on the development of a new software architecture that assembles the resources into a single platform. A new web application, the CompTox Chemistry Dashboard provides access to data associated with ~720,000 chemical substances. These data include experimental and predicted physicochemical property data, bioassay screening data associated with the ToxCast program, product and functional use information and a myriad of related data of value to environmental scientists.
The dashboard provides chemical-based searching based on chemical names, synonyms and CAS Registry Numbers. Flexible search capabilities allow for chemical identification based on non-targeted analysis studies using mass spectrometry. Chemical identification using both mass and formula-based searching utilizes rank-ordering of results via functional use statistics, thereby providing a solution to help prioritize chemicals for further review when detected in environmental media.
This presentation will provide an overview of the CompTox Dashboard, its capabilities for delivering data to the environmental toxicology community and how the architecture provides a foundation for the development of additional applications to support chemical risk assessment. This abstract does not reflect U.S. EPA policy.
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are advancing the identification of emerging contaminants in environmental matrices, improving the means by which exposure analyses can be conducted. However, confidence in structure identification of unknowns in NTA presents challenges to analytical chemists. Structure identification requires integration of complementary data types such as reference databases (either commercial or open databases), fragmentation prediction tools, and retention time prediction models. One goal of our research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemicals Dashboard, an open chemistry resource and web application containing data for ~900,000 substances. Database searching using mass or formula-based inputs has been optimized for structure identification using “MS-Ready Structures”: de-salted, stripped of stereochemistry, and mixture separated to replicate the form of a chemical observed via HRMS. Functionality to conduct batch searching of molecular formulae and monoisotopic masses has also been implemented. While the increasing number of free online databases are of value to support chemical structure verification and elucidation there are known issues regarding data quality and careful data curation is a very necessary part of the development of these resources. This presentation will provide an overview of our latest enhancements to the dashboard to support mass spectrometry, incorporation of specific datasets (e.g., to support breath research (the volatilome) and household dust analysis), and the value of metadata and predicted fragmentation spectral matching to support structure identification. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.The US-EPA CompTox Chemicals Dashboard – an online data integration hub suppo...
The US-EPA CompTox Chemicals Dashboard – an online data integration hub suppo...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. This poster reviews the benefits of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. Standard approaches for both mass and formula lookup are available but the dashboard delivers a novel approach for hit ranking based on functional use of the chemicals. The focus on high-quality data, novel ranking approaches and integration to other resources of value to mass spectrometrists makes the CompTox Dashboard a valuable resource for the identification of environmental chemicals. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are utilized to identify emerging contaminants and chemical signatures of interest detected in various media. At the US Environmental Protection Agency the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is an open chemistry resource and web-based application containing data for ~900,000 substances and supports non-targeted and suspect screening analyses. Searching functionality includes identifier searches (e.g. systematic names, trade names and CAS Registry Numbers), mass and formula-based searches and prototype developments include combined substructure-mass/formula searches and searching experimental mass spectral data against predicted fragmentation spectra. A specific type of data mapping in the database uses “MS-Ready” structures, a way to process all registered substances to separate multi-component chemicals into their individual components, removal of stereochemical bonds and desalting and neutralization. This MS-Ready processing supports batch-searching using either mass or formulae to identify candidate chemicals and their mapped substances. A number of chemical lists (https://comptox.epa.gov/dashboard/chemical_lists) have also been developed to support the identification of chemicals related to agrochemistry, specifically pesticides (both active and inert constituents), insecticides and their metabolites and environmental breakdown products). This presentation will provide an overview of how the CompTox Chemicals Dashboard supports mass spectrometry based structure identification and non-targeted analysis of chemicals in agrochemistry. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
A presentation given at the Global Marine Summit at UNC Wilmington on October 9th 2019. The focus of the presentation was an overview of the EPA CompTox Chemicals Dashboard with a specific focus on providing access to data to chemicals such as algal toxins and mycotoxins. US EPA CompTox Chemicals Dashboard Data Integration Hub to Support Environmen...
US EPA CompTox Chemicals Dashboard Data Integration Hub to Support Environmen...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
In recent years, the growth of scientific data and the increasing need for data sharing and collaboration in the field of environmental chemistry has led to the creation of various software and databases that facilitate research and development into the safety and toxicity of chemicals. The US-EPA Center for Computational Toxicology and Exposure has been developing software and databases that serve the chemistry community for many years. This presentation will focus on several web-based software applications which have been developed at the US-EPA and made available to the community. While the primary software application from the Center is the CompTox Chemicals Dashboard almost a dozen proof-of-concept applications have been built serving various capabilities. The publicly accessible Cheminformatics Modules (https://www.epa.gov/chemical-research/cheminformatics) provides access to six individual modules to allow for hazard comparison for sets of chemicals, structure-substructure-similarity searching, structure alerts and batch QSAR prediction of both physicochemical and toxicity endpoints. Each of these depends on the underlying DSSTox chemicals database, a rich source of chemistry data for over 1.2 million chemical substances. This presentation will provide an overview of all tools in development and the integrated nature of the applications based on the underlying chemistry data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection AgencyUtilizing US-EPA Data Dashboards to Support Exposomics research
Utilizing US-EPA Data Dashboards to Support Exposomics researchUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Similaire à Health Datapalooza 2013: Datalab - Steven Edwards (20)
CompTox Chemicals Dashboard: Data and tools to support chemical and environme...
CompTox Chemicals Dashboard: Data and tools to support chemical and environme...
Using the US EPA's CompTox Chemistry Dashboard to support identification and ...
Using the US EPA's CompTox Chemistry Dashboard to support identification and ...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...
The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Tox...
Amet tm chemical evaluation_and_safety assessment_for_usa_sds_authoring
Amet tm chemical evaluation_and_safety assessment_for_usa_sds_authoring
Leveraging chemistry data to improve exposure analyses using the EPA’s CompTo...
Leveraging chemistry data to improve exposure analyses using the EPA’s CompTo...
The US-EPA CompTox Chemicals Dashboard – an online data integration hub suppo...
The US-EPA CompTox Chemicals Dashboard – an online data integration hub suppo...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Consensus Models to Predict Endocrine Disruption for All Human-Exposure Chemi...
Consensus Models to Predict Endocrine Disruption for All Human-Exposure Chemi...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...
CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity
CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity
EDSP Prioritization: Collaborative Estrogen Receptor Activity Prediction Proj...
EDSP Prioritization: Collaborative Estrogen Receptor Activity Prediction Proj...
US EPA CompTox Chemicals Dashboard Data Integration Hub to Support Environmen...
US EPA CompTox Chemicals Dashboard Data Integration Hub to Support Environmen...
Utilizing US-EPA Data Dashboards to Support Exposomics research
Utilizing US-EPA Data Dashboards to Support Exposomics research
PubChem as an Emerging Toxicological Information Resource
PubChem as an Emerging Toxicological Information Resource
Plus de Health Data Consortium
Watch the webinar here: http://encore.meetingbridge.com/MB005418/140528/
Webinar transcript: http://hdc.membershipsoftware.org/Files/webinars/HDC-PwC%20NIH%20&%20PCORI%20Webinar%20Transcript%205_28_14.pdf
Patient-Centered Outcomes Research Institute (PCORI) Executive Director Joe Selby, MD, MPH; National Institutes of Health (NIH) Director and PCORI Board of Governors member Francis Collins, MD, PhD; and NIH Associate Director for Data Science Philip Bourne, PhD discussed new and emerging trends in big data for health, including:
- How researchers, patients, clinicians, and others are forging new models for data-sharing.
- Leveraging the quantity, variety, and analytic potential of health-related data for research and practice.
- Addressing patients’ perspectives, needs, and concerns in creating new opportunities for innovation and translational science.
- Exciting initiatives such as PCORnet, the National Patient-Centered Clinical Research Network initiative that PCORI is now helping to develop, and related open data and technology efforts such - as the NIH Health Systems Collaboratory and Big Data to Knowledge (BD2K) initiative.
Discover more health data resources on our website at http://www.healthdataconsortium.org/From Research to Practice - New Models for Data-sharing and Collaboration to ...
From Research to Practice - New Models for Data-sharing and Collaboration to ...Health Data Consortium
Watch the webinar here: http://www.screencast.com/t/6E1ZgTOb
Deven McGraw, Partner at Manatt, Phelps & Phillips, discussed privacy and security concerns in regards to the liberation and usage of health data. There is enormous potential to glean valuable insights from large data sets of health (and health-related) information - but the collection and use of health information for analytics purposes raises privacy and security concerns. Solution of these issues is key to realizing the benefits of health big data. This presentation will focus primarily on some of the regulatory challenges to learning uses of clinical and administrative claims data but also touch on challenges to big data analytics in other contexts (for example, government data and data collected by consumer-facing commercial entities like mobile health apps, social networking sites, search engines, and other personal health tools).
Discover more health data resources on our website at http://www.healthdataconsortium.org/Addressing Privacy and Security Concerns to Unlock Insights in Big Data in He...
Addressing Privacy and Security Concerns to Unlock Insights in Big Data in He...Health Data Consortium
Watch the webinar here: http://www.screencast.com/t/a43QB5zqjP5
Damon Davis, Director of the Health Data Initiative at the U.S. Department of Health and Human Services, discussed HHS' new Health Data Strategy and Execution Plan. Since the Department of Health and Human Services (HHS) launched its efforts to make the vast array of data resources it curates openly available for public consumption in 2010, the data available in HealthData.gov catalog has grown exponentially. HHS’s efforts to release data for the purpose of sparking innovations in healthcare and the delivery of human services is known as the Health Data Initiative (HDI). The mission of HDI is to help improve health, healthcare, and the delivery of human services by harnessing the power of data and fostering a culture of innovative uses of data in public and private sector institutions, communities, research groups, and policy making arenas.
Discover more health data resources on our website at http://www.healthdataconsortium.org/The HHS Health Data Initiative (HDI) Strategy & Execution Plan with Damon Davis
The HHS Health Data Initiative (HDI) Strategy & Execution Plan with Damon DavisHealth Data Consortium
Watch the webinar here: http://www.screencast.com/t/0lATKYlJ8
Dr. Chris Boone, then-VP in Avalere’s Evidence Translation and Implementation Practice, discussed clinical trial data transparency and considerations for governance and open data sharing. Clinical trials are extremely valuable as the primary data source for seeking regulatory approval of products. Historically, regulatory agencie have been the sole recipients of clinical trial data, butthere has been a recent push from various stakeholder groups to open access to clinical trial data to non-regulatory researchers as an act of ethical responsibility to patients, a contribution to public health, and a demonstrated commitment to advancing the science. Some of the barriers include developing a sound approach for de-identifying patient data, adopting universal clinical trial data format, and managing the proactive and non-selective access and security of clinical data once collected. Dr. Boone discusses rationales and benefits/risks of clinical trial transparency, responsible use of publicly sharing this data, barriers and legal implications, and reasonable data sharing models.
Discover more health data resources on our website at http://www.healthdataconsortium.org/Clinical Trial Data Transparency: Explaining Governance for Public Data Sharing
Clinical Trial Data Transparency: Explaining Governance for Public Data SharingHealth Data Consortium
Health Datapalooza IV: June 3rd-4th, 2013
HEALTH DATA CONSORTIUM AFFILIATES APP DEMOS
Monday June 3, 2013 • 4:30pm - 5:30pm
Location: Regency Ballroom
Moderator: Sunnie Southern, Founder and Chief Executive Officer, Viable Synergy, LLC; Ohio Health Data Affiliate
hGraph is an open source information visualization which provides a complete overview of an
individual’s health from an aggregated, high-level “how am I doing” status to detailed, metriclevel results and analysis. This single picture method can have a profound effect on a person’s
understanding of his/her total well-being, because it compiles multiple metrics and inputs into a
unified graph that can be viewed at a glance.Health Datapalooza 2013: HDC Affiliates Apps Demos - Involution Studios hGraph
Health Datapalooza 2013: HDC Affiliates Apps Demos - Involution Studios hGraphHealth Data Consortium
Plus de Health Data Consortium (20)
The Health Care Cost Institute’s National Transparency Initiative
The Health Care Cost Institute’s National Transparency Initiative
From Research to Practice - New Models for Data-sharing and Collaboration to ...
From Research to Practice - New Models for Data-sharing and Collaboration to ...
Addressing Privacy and Security Concerns to Unlock Insights in Big Data in He...
Addressing Privacy and Security Concerns to Unlock Insights in Big Data in He...
The HHS Health Data Initiative (HDI) Strategy & Execution Plan with Damon Davis
The HHS Health Data Initiative (HDI) Strategy & Execution Plan with Damon Davis
Clinical Trial Data Transparency: Explaining Governance for Public Data Sharing
Clinical Trial Data Transparency: Explaining Governance for Public Data Sharing
Exchanges go live: early trends in competitor dynamics
Exchanges go live: early trends in competitor dynamics
Liberating Health Data: What we learned in New York, with Dr. Nirav Shah
Liberating Health Data: What we learned in New York, with Dr. Nirav Shah
Health Datapalooza 2013: HDC Affiliates Apps Demos - Involution Studios hGraph
Health Datapalooza 2013: HDC Affiliates Apps Demos - Involution Studios hGraph
Health Datapalooza 2013: Cooperation Without Coordination
Health Datapalooza 2013: Cooperation Without Coordination
Health Datapalooza 2013: Hearing from the Community - Richard Martin
Health Datapalooza 2013: Hearing from the Community - Richard Martin
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Health Datapalooza 2013: Datalab - Steven Edwards
- 1. Office of Research and Development National Health and Environmental Effects Research Laboratory Photo image area measures 2” H x 6.93” W and can be masked by a collage strip of one, two or three images. The photo image area is located 3.19” from left and 3.81” from top of page. Each image used in collage should be reduced or cropped to a maximum of 2” high, stroked with a 1.5 pt white frame and positioned edge-to-edge with accompanying images. June 25, 2013 EPA Data from the Office of Research and Development Stephen W. Edwards Edwards.stephen@epa.gov This talk does not necessarily reflect the views of the Environmental Protection Agency.
- 2. Office of Research and Development National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division One Stop Shopping for EPA Data http://epa.gov/datafinder/
- 3. Office of Research and Development National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division Computational Toxicology Data • Aggregated Computational Toxicology Resource (ACToR) –http://www.epa.gov/actor/ • Distributed Structure-Searchable Toxicity (DSSTox) Database –http://actor.epa.gov/actor/faces/DSSTox/Home.jsp • Exposure foreCaster (ExpoCastTM) Database –http://www.epa.gov/ncct/expocast/ • Toxicity foreCaster (ToxCastTM) Database –http://www.epa.gov/ncct/toxcast/ • Toxicity Reference Database (ToxRefDB) –http://actor.epa.gov/toxrefdb/faces/Home.jsp • Tox21 Collaboration (NIH, FDA) –http://www.epa.gov/ncct/Tox21/ http://epa.gov/ncct/index.html
- 4. Office of Research and Development National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division Exposure Data • Consolidated Human Activity Database - CHAD –http://www.epa.gov/heasd/chad.html • Consumer Product Chemical Profiles Database – CPCPDB –Coming soon to ACToR: http://www.epa.gov/actor/ • ExpoCast –http://www.epa.gov/ncct/expocast/ • Stochastic Human Exposure and Dose Simulation Model (SHEDS) – http://www.epa.gov/heasd/research/sheds.html
- 5. Office of Research and Development National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division DSS Tox ToxCast ExpoCast SHEDS Virtual Tissue, Biomarker, and Adverse Outcome Pathway Knowledgebases ToxRefDB WikiLIMS Tox21 Data Housed at EPA
- 6. Office of Research and Development National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division Toxicological Data Shared via CEBS (NIEHS) Proteomics Core 2D Gel Mass Spec Metabolomics / Anal Chem Core NMR Mass Spec ToxicoGenomics Core Microarray qPCR Sequencing WikiLIMS Many different investigators Experimental Design Human, Animal, Culture Treatment Schedule Stressor (Compound) Assay descriptions Timeline Animal Care Cell Culture Conditions Sample Preparation Laboratory/Field Data Histopathology Clinical Chemistry In Life Observations Behavioral Obs Developmental Obs Necropsy Obs Exposure biomarkers Exit http://cebs.niehs.nih.gov/