A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients
ObjectivesScalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings.Materials and MethodsWe developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase,...
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creator | Pishvaian, Michael J Blais, Edik M Bender, R Joseph Rao, Shruti Boca, Simina M Chung, Vincent Hendifar, Andrew E Mikhail, Sam Sohal, Davendra P S Pohlmann, Paula R Moore, Kathleen N He, Kai Monk, Bradley J Coleman, Robert L Herzog, Thomas J Halverson, David D DeArbeloa, Patricia Petricoin, Emanuel F Madhavan, Subha |
description | ObjectivesScalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings.Materials and MethodsWe developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase, scoring model, rules engine, an asynchronous virtual chat room and a reporting tool that generated a treatment plan for each of the 1725 patients based on their molecular profile, previous treatment history, structured trial eligibility criteria, clinically relevant cancer gene-variant assertions, biomarker-treatment associations, and current treatment guidelines. The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations.ResultsThe VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support.DiscussionVMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand.ConclusionFurther development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care. |
doi_str_mv | 10.1093/jamiaopen/ooz045 |
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The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations.ResultsThe VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support.DiscussionVMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand.ConclusionFurther development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care.</description><identifier>ISSN: 2574-2531</identifier><identifier>EISSN: 2574-2531</identifier><identifier>DOI: 10.1093/jamiaopen/ooz045</identifier><identifier>PMID: 32025647</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Analysis ; Cancer ; Care and treatment ; Genetic aspects ; Immunotherapy ; Medical records ; Research and Applications</subject><ispartof>JAMIA open, 2019-12, Vol.2 (4), p.505-515</ispartof><rights>The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. 2019</rights><rights>The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association.</rights><rights>COPYRIGHT 2019 Oxford University Press</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-97075eb6bee10e92c53b14622cc459dad40fe13643e2e443c5d8a088a8b68dcb3</citedby><cites>FETCH-LOGICAL-c499t-97075eb6bee10e92c53b14622cc459dad40fe13643e2e443c5d8a088a8b68dcb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6994017/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6994017/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,1598,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32025647$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pishvaian, Michael J</creatorcontrib><creatorcontrib>Blais, Edik M</creatorcontrib><creatorcontrib>Bender, R Joseph</creatorcontrib><creatorcontrib>Rao, Shruti</creatorcontrib><creatorcontrib>Boca, Simina M</creatorcontrib><creatorcontrib>Chung, Vincent</creatorcontrib><creatorcontrib>Hendifar, Andrew E</creatorcontrib><creatorcontrib>Mikhail, Sam</creatorcontrib><creatorcontrib>Sohal, Davendra P S</creatorcontrib><creatorcontrib>Pohlmann, Paula R</creatorcontrib><creatorcontrib>Moore, Kathleen N</creatorcontrib><creatorcontrib>He, Kai</creatorcontrib><creatorcontrib>Monk, Bradley J</creatorcontrib><creatorcontrib>Coleman, Robert L</creatorcontrib><creatorcontrib>Herzog, Thomas J</creatorcontrib><creatorcontrib>Halverson, David D</creatorcontrib><creatorcontrib>DeArbeloa, Patricia</creatorcontrib><creatorcontrib>Petricoin, Emanuel F</creatorcontrib><creatorcontrib>Madhavan, Subha</creatorcontrib><title>A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients</title><title>JAMIA open</title><addtitle>JAMIA Open</addtitle><description>ObjectivesScalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings.Materials and MethodsWe developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase, scoring model, rules engine, an asynchronous virtual chat room and a reporting tool that generated a treatment plan for each of the 1725 patients based on their molecular profile, previous treatment history, structured trial eligibility criteria, clinically relevant cancer gene-variant assertions, biomarker-treatment associations, and current treatment guidelines. The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations.ResultsThe VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support.DiscussionVMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand.ConclusionFurther development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care.</description><subject>Analysis</subject><subject>Cancer</subject><subject>Care and treatment</subject><subject>Genetic aspects</subject><subject>Immunotherapy</subject><subject>Medical records</subject><subject>Research and Applications</subject><issn>2574-2531</issn><issn>2574-2531</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNqFkstq3DAYhU1paUKafVdF0E2hTKKbL9oUhtAbBLpp10KWf88oyPpdyR5wXqCvXU2dDgkUihYS0nc-SXCK4jWjV4wqcX1nBmdwhHCNeE9l-aw452UtN7wU7Pmj9VlxmdIdpZQppSpBXxZnglNeVrI-L35tycHFaTaeDOjBzt5EMs0DRtKiiR2ZkLhhjHgAAn3vrINgF2JCR5I13rTOu2kh2JMOvDtAdGFHxgjWJYeBYLDocbccNeN-STlvQvoTn_bgIhnNlI1TelW86I1PcPkwXxQ_Pn38fvNlc_vt89eb7e3GSqWmjappXUJbtQCMguK2FC2TFefWylJ1ppO0ByYqKYCDlMKWXWNo05imrZrOtuKi-LB6x7kdoLP57mi8HqMbTFw0GqefngS31zs86EopSVmdBe8eBBF_zpAmPbhkwXsTAOekuSg5LUUtaUbfrujOeNAu9JiN9ojrbdUodkR5pq7-QeXRweAsBuhd3n8SoGvARkwpQn96PaP62Ax9aoZem5Ejbx7_-hT424MMvF8BnMf_634DB8jKMw</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Pishvaian, Michael J</creator><creator>Blais, Edik M</creator><creator>Bender, R Joseph</creator><creator>Rao, Shruti</creator><creator>Boca, Simina M</creator><creator>Chung, Vincent</creator><creator>Hendifar, Andrew E</creator><creator>Mikhail, Sam</creator><creator>Sohal, Davendra P S</creator><creator>Pohlmann, Paula R</creator><creator>Moore, Kathleen N</creator><creator>He, Kai</creator><creator>Monk, Bradley J</creator><creator>Coleman, Robert L</creator><creator>Herzog, Thomas J</creator><creator>Halverson, David D</creator><creator>DeArbeloa, Patricia</creator><creator>Petricoin, Emanuel F</creator><creator>Madhavan, Subha</creator><general>Oxford University Press</general><scope>TOX</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20191201</creationdate><title>A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients</title><author>Pishvaian, Michael J ; Blais, Edik M ; Bender, R Joseph ; Rao, Shruti ; Boca, Simina M ; Chung, Vincent ; Hendifar, Andrew E ; Mikhail, Sam ; Sohal, Davendra P S ; Pohlmann, Paula R ; Moore, Kathleen N ; He, Kai ; Monk, Bradley J ; Coleman, Robert L ; Herzog, Thomas J ; Halverson, David D ; DeArbeloa, Patricia ; Petricoin, Emanuel F ; Madhavan, Subha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c499t-97075eb6bee10e92c53b14622cc459dad40fe13643e2e443c5d8a088a8b68dcb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Analysis</topic><topic>Cancer</topic><topic>Care and treatment</topic><topic>Genetic aspects</topic><topic>Immunotherapy</topic><topic>Medical records</topic><topic>Research and Applications</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pishvaian, Michael J</creatorcontrib><creatorcontrib>Blais, Edik M</creatorcontrib><creatorcontrib>Bender, R Joseph</creatorcontrib><creatorcontrib>Rao, Shruti</creatorcontrib><creatorcontrib>Boca, Simina M</creatorcontrib><creatorcontrib>Chung, Vincent</creatorcontrib><creatorcontrib>Hendifar, Andrew E</creatorcontrib><creatorcontrib>Mikhail, Sam</creatorcontrib><creatorcontrib>Sohal, Davendra P S</creatorcontrib><creatorcontrib>Pohlmann, Paula R</creatorcontrib><creatorcontrib>Moore, Kathleen N</creatorcontrib><creatorcontrib>He, Kai</creatorcontrib><creatorcontrib>Monk, Bradley J</creatorcontrib><creatorcontrib>Coleman, Robert L</creatorcontrib><creatorcontrib>Herzog, Thomas J</creatorcontrib><creatorcontrib>Halverson, David D</creatorcontrib><creatorcontrib>DeArbeloa, Patricia</creatorcontrib><creatorcontrib>Petricoin, Emanuel F</creatorcontrib><creatorcontrib>Madhavan, Subha</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>JAMIA open</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pishvaian, Michael J</au><au>Blais, Edik M</au><au>Bender, R Joseph</au><au>Rao, Shruti</au><au>Boca, Simina M</au><au>Chung, Vincent</au><au>Hendifar, Andrew E</au><au>Mikhail, Sam</au><au>Sohal, Davendra P S</au><au>Pohlmann, Paula R</au><au>Moore, Kathleen N</au><au>He, Kai</au><au>Monk, Bradley J</au><au>Coleman, Robert L</au><au>Herzog, Thomas J</au><au>Halverson, David D</au><au>DeArbeloa, Patricia</au><au>Petricoin, Emanuel F</au><au>Madhavan, Subha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients</atitle><jtitle>JAMIA open</jtitle><addtitle>JAMIA Open</addtitle><date>2019-12-01</date><risdate>2019</risdate><volume>2</volume><issue>4</issue><spage>505</spage><epage>515</epage><pages>505-515</pages><issn>2574-2531</issn><eissn>2574-2531</eissn><abstract>ObjectivesScalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings.Materials and MethodsWe developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase, scoring model, rules engine, an asynchronous virtual chat room and a reporting tool that generated a treatment plan for each of the 1725 patients based on their molecular profile, previous treatment history, structured trial eligibility criteria, clinically relevant cancer gene-variant assertions, biomarker-treatment associations, and current treatment guidelines. The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations.ResultsThe VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support.DiscussionVMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand.ConclusionFurther development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>32025647</pmid><doi>10.1093/jamiaopen/ooz045</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Cancer Care and treatment Genetic aspects Immunotherapy Medical records Research and Applications |
title | A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients |
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