Predicting drug‐induced arrhythmias by multiscale modeling
Drugs often have undesired side effects. In the heart, they can induce lethal arrhythmias such as torsades de pointes. The risk evaluation of a new compound is costly and can take a long time, which often hinders the development of new drugs. Here, we establish a high‐resolution, multiscale computat...
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Veröffentlicht in: | International journal for numerical methods in biomedical engineering 2018-05, Vol.34 (5), p.e2964-n/a |
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description | Drugs often have undesired side effects. In the heart, they can induce lethal arrhythmias such as torsades de pointes. The risk evaluation of a new compound is costly and can take a long time, which often hinders the development of new drugs. Here, we establish a high‐resolution, multiscale computational model to quickly assess the cardiac toxicity of new and existing drugs. The input of the model is the drug‐specific current block from single cell electrophysiology; the output is the spatio‐temporal activation profile and the associated electrocardiogram. We demonstrate the potential of our model for a low‐risk drug, ranolazine, and a high‐risk drug, quinidine: For ranolazine, our model predicts a prolonged QT interval of 19.4% compared with baseline and a regular sinus rhythm at 60.15 beats per minute. For quinidine, our model predicts a prolonged QT interval of 78.4% and a spontaneous development of torsades de pointes both in the activation profile and in the electrocardiogram. Our model reveals the mechanisms by which electrophysiological abnormalities propagate across the spatio‐temporal scales, from specific channel blockage, via altered single cell action potentials and prolonged QT intervals, to the spontaneous emergence of ventricular tachycardia in the form of torsades de pointes. Our model could have important implications for researchers, regulatory agencies, and pharmaceutical companies on rationalizing safe drug development and reducing the time‐to‐market of new drugs.
We present a new multiscale exposure‐response simulator to quickly assess the cardiac toxicity of drugs. Our model converts drug‐specific current block characteristics from single cell electrophysiology into excitation profiles and electrocardiograms across the whole heart. For the low‐risk drug ranolazine, we predict a QT interval prolongation of 19% and a regular sinus rhythm at 60 beats per minute; for the high‐risk drug quinidine, we predict a QT interval prolongation of 78% and a spontaneous episode of torsades de pointes. |
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We present a new multiscale exposure‐response simulator to quickly assess the cardiac toxicity of drugs. Our model converts drug‐specific current block characteristics from single cell electrophysiology into excitation profiles and electrocardiograms across the whole heart. For the low‐risk drug ranolazine, we predict a QT interval prolongation of 19% and a regular sinus rhythm at 60 beats per minute; for the high‐risk drug quinidine, we predict a QT interval prolongation of 78% and a spontaneous episode of torsades de pointes.</description><identifier>ISSN: 2040-7939</identifier><identifier>EISSN: 2040-7947</identifier><identifier>DOI: 10.1002/cnm.2964</identifier><identifier>PMID: 29424967</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Abnormalities ; Activation ; Arrhythmia ; Cardiac arrhythmia ; cardiac toxicity ; Computer applications ; Drug development ; Drugs ; EKG ; Electrocardiography ; Electrophysiology ; finite element analysis ; Heart ; Heart diseases ; Mathematical models ; Multiscale analysis ; Pharmaceutical industry ; Quinidine ; Regulatory agencies ; Risk assessment ; Side effects ; Tachycardia ; Torsades de pointes ; Toxicity ; Ventricle</subject><ispartof>International journal for numerical methods in biomedical engineering, 2018-05, Vol.34 (5), p.e2964-n/a</ispartof><rights>Copyright © 2018 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3834-e5c08ad04884fb03f2ebe378e47a6abad92154e09e91df36ed9953b80cd2d0ea3</citedby><cites>FETCH-LOGICAL-c3834-e5c08ad04884fb03f2ebe378e47a6abad92154e09e91df36ed9953b80cd2d0ea3</cites><orcidid>0000-0002-6283-935X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcnm.2964$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcnm.2964$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29424967$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sahli Costabal, Francisco</creatorcontrib><creatorcontrib>Yao, Jiang</creatorcontrib><creatorcontrib>Kuhl, Ellen</creatorcontrib><title>Predicting drug‐induced arrhythmias by multiscale modeling</title><title>International journal for numerical methods in biomedical engineering</title><addtitle>Int J Numer Method Biomed Eng</addtitle><description>Drugs often have undesired side effects. In the heart, they can induce lethal arrhythmias such as torsades de pointes. The risk evaluation of a new compound is costly and can take a long time, which often hinders the development of new drugs. Here, we establish a high‐resolution, multiscale computational model to quickly assess the cardiac toxicity of new and existing drugs. The input of the model is the drug‐specific current block from single cell electrophysiology; the output is the spatio‐temporal activation profile and the associated electrocardiogram. We demonstrate the potential of our model for a low‐risk drug, ranolazine, and a high‐risk drug, quinidine: For ranolazine, our model predicts a prolonged QT interval of 19.4% compared with baseline and a regular sinus rhythm at 60.15 beats per minute. For quinidine, our model predicts a prolonged QT interval of 78.4% and a spontaneous development of torsades de pointes both in the activation profile and in the electrocardiogram. Our model reveals the mechanisms by which electrophysiological abnormalities propagate across the spatio‐temporal scales, from specific channel blockage, via altered single cell action potentials and prolonged QT intervals, to the spontaneous emergence of ventricular tachycardia in the form of torsades de pointes. Our model could have important implications for researchers, regulatory agencies, and pharmaceutical companies on rationalizing safe drug development and reducing the time‐to‐market of new drugs.
We present a new multiscale exposure‐response simulator to quickly assess the cardiac toxicity of drugs. Our model converts drug‐specific current block characteristics from single cell electrophysiology into excitation profiles and electrocardiograms across the whole heart. For the low‐risk drug ranolazine, we predict a QT interval prolongation of 19% and a regular sinus rhythm at 60 beats per minute; for the high‐risk drug quinidine, we predict a QT interval prolongation of 78% and a spontaneous episode of torsades de pointes.</description><subject>Abnormalities</subject><subject>Activation</subject><subject>Arrhythmia</subject><subject>Cardiac arrhythmia</subject><subject>cardiac toxicity</subject><subject>Computer applications</subject><subject>Drug development</subject><subject>Drugs</subject><subject>EKG</subject><subject>Electrocardiography</subject><subject>Electrophysiology</subject><subject>finite element analysis</subject><subject>Heart</subject><subject>Heart diseases</subject><subject>Mathematical models</subject><subject>Multiscale analysis</subject><subject>Pharmaceutical industry</subject><subject>Quinidine</subject><subject>Regulatory agencies</subject><subject>Risk assessment</subject><subject>Side effects</subject><subject>Tachycardia</subject><subject>Torsades de pointes</subject><subject>Toxicity</subject><subject>Ventricle</subject><issn>2040-7939</issn><issn>2040-7947</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kMtKAzEUQIMottSCXyADbtxMzSSZR8CNFF9QHwtdh0xyp02ZR01mkNn5CX6jX2Lq1O7M5mZx7rlwEDqN8CzCmFyqupoRnrADNCaY4TDlLD3c_ykfoalza-wf4Zyn9BiNCGeE8SQdo6sXC9qo1tTLQNtu-f35ZWrdKdCBtHbVt6vKSBfkfVB1ZWuckiUEVaOh9Bsn6KiQpYPpbk7Q2-3N6_w-XDzfPcyvF6GiGWUhxApnUmOWZazIMS0I5EDTDFgqE5lLzUkUM8AceKQLmoDmPKZ5hpUmGoOkE3Q-eDe2ee_AtWLddLb2JwXBNOERiynx1MVAKds4Z6EQG2sqaXsRYbEtJXwpsS3l0bOdsMsr0Hvwr4sHwgH4MCX0_4rE_OnxV_gDvt1yrg</recordid><startdate>201805</startdate><enddate>201805</enddate><creator>Sahli Costabal, Francisco</creator><creator>Yao, Jiang</creator><creator>Kuhl, Ellen</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0002-6283-935X</orcidid></search><sort><creationdate>201805</creationdate><title>Predicting drug‐induced arrhythmias by multiscale modeling</title><author>Sahli Costabal, Francisco ; Yao, Jiang ; Kuhl, Ellen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3834-e5c08ad04884fb03f2ebe378e47a6abad92154e09e91df36ed9953b80cd2d0ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Abnormalities</topic><topic>Activation</topic><topic>Arrhythmia</topic><topic>Cardiac arrhythmia</topic><topic>cardiac toxicity</topic><topic>Computer applications</topic><topic>Drug development</topic><topic>Drugs</topic><topic>EKG</topic><topic>Electrocardiography</topic><topic>Electrophysiology</topic><topic>finite element analysis</topic><topic>Heart</topic><topic>Heart diseases</topic><topic>Mathematical models</topic><topic>Multiscale analysis</topic><topic>Pharmaceutical industry</topic><topic>Quinidine</topic><topic>Regulatory agencies</topic><topic>Risk assessment</topic><topic>Side effects</topic><topic>Tachycardia</topic><topic>Torsades de pointes</topic><topic>Toxicity</topic><topic>Ventricle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sahli Costabal, Francisco</creatorcontrib><creatorcontrib>Yao, Jiang</creatorcontrib><creatorcontrib>Kuhl, Ellen</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>International journal for numerical methods in biomedical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sahli Costabal, Francisco</au><au>Yao, Jiang</au><au>Kuhl, Ellen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting drug‐induced arrhythmias by multiscale modeling</atitle><jtitle>International journal for numerical methods in biomedical engineering</jtitle><addtitle>Int J Numer Method Biomed Eng</addtitle><date>2018-05</date><risdate>2018</risdate><volume>34</volume><issue>5</issue><spage>e2964</spage><epage>n/a</epage><pages>e2964-n/a</pages><issn>2040-7939</issn><eissn>2040-7947</eissn><abstract>Drugs often have undesired side effects. In the heart, they can induce lethal arrhythmias such as torsades de pointes. The risk evaluation of a new compound is costly and can take a long time, which often hinders the development of new drugs. Here, we establish a high‐resolution, multiscale computational model to quickly assess the cardiac toxicity of new and existing drugs. The input of the model is the drug‐specific current block from single cell electrophysiology; the output is the spatio‐temporal activation profile and the associated electrocardiogram. We demonstrate the potential of our model for a low‐risk drug, ranolazine, and a high‐risk drug, quinidine: For ranolazine, our model predicts a prolonged QT interval of 19.4% compared with baseline and a regular sinus rhythm at 60.15 beats per minute. For quinidine, our model predicts a prolonged QT interval of 78.4% and a spontaneous development of torsades de pointes both in the activation profile and in the electrocardiogram. Our model reveals the mechanisms by which electrophysiological abnormalities propagate across the spatio‐temporal scales, from specific channel blockage, via altered single cell action potentials and prolonged QT intervals, to the spontaneous emergence of ventricular tachycardia in the form of torsades de pointes. Our model could have important implications for researchers, regulatory agencies, and pharmaceutical companies on rationalizing safe drug development and reducing the time‐to‐market of new drugs.
We present a new multiscale exposure‐response simulator to quickly assess the cardiac toxicity of drugs. Our model converts drug‐specific current block characteristics from single cell electrophysiology into excitation profiles and electrocardiograms across the whole heart. For the low‐risk drug ranolazine, we predict a QT interval prolongation of 19% and a regular sinus rhythm at 60 beats per minute; for the high‐risk drug quinidine, we predict a QT interval prolongation of 78% and a spontaneous episode of torsades de pointes.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>29424967</pmid><doi>10.1002/cnm.2964</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-6283-935X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abnormalities Activation Arrhythmia Cardiac arrhythmia cardiac toxicity Computer applications Drug development Drugs EKG Electrocardiography Electrophysiology finite element analysis Heart Heart diseases Mathematical models Multiscale analysis Pharmaceutical industry Quinidine Regulatory agencies Risk assessment Side effects Tachycardia Torsades de pointes Toxicity Ventricle |
title | Predicting drug‐induced arrhythmias by multiscale modeling |
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