The Experts below are selected from a list of 4737 Experts worldwide ranked by ideXlab platform
Sirarat Sarntivijai - One of the best experts on this subject based on the ideXlab platform.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Yongqun He, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Abstract Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. Objectives The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Results Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. Conclusion By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.
Darrell R. Abernethy - One of the best experts on this subject based on the ideXlab platform.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Yongqun He, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Abstract Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. Objectives The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Results Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. Conclusion By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.
Gilbert S. Omenn - One of the best experts on this subject based on the ideXlab platform.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Yongqun He, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Abstract Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. Objectives The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Results Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. Conclusion By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.
Shelley Zhang - One of the best experts on this subject based on the ideXlab platform.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Yongqun He, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Abstract Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. Objectives The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Results Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. Conclusion By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.
Desikan Jagannathan - One of the best experts on this subject based on the ideXlab platform.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Yongqun He, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Abstract Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. Objectives The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Results Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. Conclusion By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.
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linking meddra coded clinical phenotypes to biological mechanisms by the ontology of adverse events a pilot study on tyrosine kinase inhibitors
Drug Safety, 2016Co-Authors: Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Brian D Athey, Sirarat Sarntivijai, Keith Burkhart, Gilbert S. Omenn, Darrell R. AbernethyAbstract:Introduction A Translational Bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.
