The Experts below are selected from a list of 119319 Experts worldwide ranked by ideXlab platform
Wail Baalawi - One of the best experts on this subject based on the ideXlab platform.
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pharmacodb an integrative database for mining in vitro anticancer Drug Screening studies
Nucleic Acids Research, 2018Co-Authors: Petr Smirnov, Victor Kofia, Alexander Maru, Mark Freeman, Nehme Elhachem, Georgealexandru Adam, Wail BaalawiAbstract:Recent cancer pharmacogenomic studies profiled large panels of cell lines against hundreds of approved Drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbations, correlate these measures to genomic features, and thereby develop novel predictors of Drug response. However, leveraging these valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying Drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale Drug Screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest cancer pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust Drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated cancer pharmacogenomic datasets that are otherwise disparate and difficult to integrate.
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pharmacodb an integrative database for mining in vitro anticancer Drug Screening studies
bioRxiv, 2017Co-Authors: Petr Smirnov, Victor Kofia, Alexander Maru, Mark Freeman, Nehme Elhachem, Georgealexandru Adam, Wail Baalawi, Zhaleh Safikhani, Benjamin HaibekainsAbstract:Recent pharmacogenomic studies profiled large panels of cancer cell lines against hundreds of approved Drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbation, correlate these measures to genomic features, and thereby develop novel predictors of Drug response. However, leveraging this valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying Drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale Drug Screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust Drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated pharmacogenomic datasets that are otherwise disparate and difficult to integrate.
Vincent Van Duinen - One of the best experts on this subject based on the ideXlab platform.
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robust and scalable angiogenesis assay of perfused 3d human ipsc derived endothelium for anti angiogenic Drug Screening
International Journal of Molecular Sciences, 2020Co-Authors: Vincent Van Duinen, Wendy Stam, Eva Mulder, Farbod Famili, Arie Reijerkerk, Paul Vulto, Thomas Hankemeier, Anton Jan Van ZonneveldAbstract:To advance pre-clinical vascular Drug research, in vitro assays are needed that closely mimic the process of angiogenesis in vivo. Such assays should combine physiological relevant culture conditions with robustness and scalability to enable Drug Screening. We developed a perfused 3D angiogenesis assay that includes endothelial cells (ECs) from induced pluripotent stem cells (iPSC) and assessed its performance and suitability for anti-angiogenic Drug Screening. Angiogenic sprouting was compared with primary ECs and showed that the microvessels from iPSC-EC exhibit similar sprouting behavior, including tip cell formation, directional sprouting and lumen formation. Inhibition with sunitinib, a clinically used vascular endothelial growth factor (VEGF) receptor type 2 inhibitor, and 3-(3-pyridinyl)-1-(4-pyridinyl)-2-propen-1-one (3PO), a transient glycolysis inhibitor, both significantly reduced the sprouting of both iPSC-ECs and primary ECs, supporting that both cell types show VEGF gradient-driven angiogenic sprouting. The assay performance was quantified for sunitinib, yielding a minimal signal window of 11 and Z-factor of at least 0.75, both meeting the criteria to be used as Screening assay. In conclusion, we have developed a robust and scalable assay that includes physiological relevant culture conditions and is amenable to Screening of anti-angiogenic compounds.
Joseph C Wu - One of the best experts on this subject based on the ideXlab platform.
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induced pluripotent stem cells as a disease modeling and Drug Screening platform
Journal of Cardiovascular Pharmacology, 2012Co-Authors: Antje D Ebert, Ping Liang, Joseph C WuAbstract:Induced pluripotent stem cells (iPSCs) hold great hopes for therapeutic application in various diseases. While ongoing research is dedicated to achieving clinical translation of iPSCs, further understanding of the mechanisms that underlie complex pathogenic conditions is required. Compared to other classical models for studying diseases, iPSCs provide considerable advantages. A newly emerging application of iPSCs is in vitro disease modeling, which can significantly improve the never-ending search for new pharmacological cures. Here, we will discuss current efforts to create iPSC-dependent, patient-specific disease models. Furthermore, we will review the use of iPSCs for development and testing of new therapeutic agents, and the implications for high-throughput Drug Screening.
Anton Jan Van Zonneveld - One of the best experts on this subject based on the ideXlab platform.
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robust and scalable angiogenesis assay of perfused 3d human ipsc derived endothelium for anti angiogenic Drug Screening
International Journal of Molecular Sciences, 2020Co-Authors: Vincent Van Duinen, Wendy Stam, Eva Mulder, Farbod Famili, Arie Reijerkerk, Paul Vulto, Thomas Hankemeier, Anton Jan Van ZonneveldAbstract:To advance pre-clinical vascular Drug research, in vitro assays are needed that closely mimic the process of angiogenesis in vivo. Such assays should combine physiological relevant culture conditions with robustness and scalability to enable Drug Screening. We developed a perfused 3D angiogenesis assay that includes endothelial cells (ECs) from induced pluripotent stem cells (iPSC) and assessed its performance and suitability for anti-angiogenic Drug Screening. Angiogenic sprouting was compared with primary ECs and showed that the microvessels from iPSC-EC exhibit similar sprouting behavior, including tip cell formation, directional sprouting and lumen formation. Inhibition with sunitinib, a clinically used vascular endothelial growth factor (VEGF) receptor type 2 inhibitor, and 3-(3-pyridinyl)-1-(4-pyridinyl)-2-propen-1-one (3PO), a transient glycolysis inhibitor, both significantly reduced the sprouting of both iPSC-ECs and primary ECs, supporting that both cell types show VEGF gradient-driven angiogenic sprouting. The assay performance was quantified for sunitinib, yielding a minimal signal window of 11 and Z-factor of at least 0.75, both meeting the criteria to be used as Screening assay. In conclusion, we have developed a robust and scalable assay that includes physiological relevant culture conditions and is amenable to Screening of anti-angiogenic compounds.
Petr Smirnov - One of the best experts on this subject based on the ideXlab platform.
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pharmacodb an integrative database for mining in vitro anticancer Drug Screening studies
Nucleic Acids Research, 2018Co-Authors: Petr Smirnov, Victor Kofia, Alexander Maru, Mark Freeman, Nehme Elhachem, Georgealexandru Adam, Wail BaalawiAbstract:Recent cancer pharmacogenomic studies profiled large panels of cell lines against hundreds of approved Drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbations, correlate these measures to genomic features, and thereby develop novel predictors of Drug response. However, leveraging these valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying Drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale Drug Screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest cancer pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust Drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated cancer pharmacogenomic datasets that are otherwise disparate and difficult to integrate.
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pharmacodb an integrative database for mining in vitro anticancer Drug Screening studies
bioRxiv, 2017Co-Authors: Petr Smirnov, Victor Kofia, Alexander Maru, Mark Freeman, Nehme Elhachem, Georgealexandru Adam, Wail Baalawi, Zhaleh Safikhani, Benjamin HaibekainsAbstract:Recent pharmacogenomic studies profiled large panels of cancer cell lines against hundreds of approved Drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbation, correlate these measures to genomic features, and thereby develop novel predictors of Drug response. However, leveraging this valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying Drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale Drug Screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust Drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated pharmacogenomic datasets that are otherwise disparate and difficult to integrate.
