Suhyeon Yoon, Hyuna Noh, Heejin Jin, Sungyoung Lee, Soyul Han, Sung-Hee Kim, Jiseon Kim, Jung Seon Seo, Jeong Jin Kim, In Ho Park, Jooyeon Oh, Joon-Yong Bae, Gee Eun Lee, Sun-Je Woo, Sun-Min Seo, Na-Won Kim, Youn Woo Lee, Hui Jeong Jang, Seung-Min Hong, Se-Hee An, Kwang-Soo Lyoo, Minjoo Yeom, Hanbyeul Lee, Bud Jung, Sun-Woo Yoon, Jung-Ah Kang, Sang-Hyuk Seok, Yu Jin Lee, Seo Yeon Kim, Young Been Kim, Ji-Yeon Hwang, Dain On, Soo-Yeon Lim, Sol Pin Kim, Ji Yun Jang, Ho Lee, Kyoungmi Kim, Hyo-Jung Lee, Hong Bin Kim, Jun Won Park, Dae Gwin Jeong, Daesub Song, Kang-Seuk Choi, Ho-Young Lee, Yang-Kyu Choi, Jung-Ah Choi, Manki Song, Man-Seong Park, Jun-Young Seo, Ki Taek Nam, Jeon-Soo Shin, Sungho Won, Jun-Won Yun, Je Kyung Seong
{"title":"COVID-19非临床疗效试验数据实验室信息管理系统。","authors":"Suhyeon Yoon, Hyuna Noh, Heejin Jin, Sungyoung Lee, Soyul Han, Sung-Hee Kim, Jiseon Kim, Jung Seon Seo, Jeong Jin Kim, In Ho Park, Jooyeon Oh, Joon-Yong Bae, Gee Eun Lee, Sun-Je Woo, Sun-Min Seo, Na-Won Kim, Youn Woo Lee, Hui Jeong Jang, Seung-Min Hong, Se-Hee An, Kwang-Soo Lyoo, Minjoo Yeom, Hanbyeul Lee, Bud Jung, Sun-Woo Yoon, Jung-Ah Kang, Sang-Hyuk Seok, Yu Jin Lee, Seo Yeon Kim, Young Been Kim, Ji-Yeon Hwang, Dain On, Soo-Yeon Lim, Sol Pin Kim, Ji Yun Jang, Ho Lee, Kyoungmi Kim, Hyo-Jung Lee, Hong Bin Kim, Jun Won Park, Dae Gwin Jeong, Daesub Song, Kang-Seuk Choi, Ho-Young Lee, Yang-Kyu Choi, Jung-Ah Choi, Manki Song, Man-Seong Park, Jun-Young Seo, Ki Taek Nam, Jeon-Soo Shin, Sungho Won, Jun-Won Yun, Je Kyung Seong","doi":"10.1186/s42826-022-00127-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research.</p><p><strong>Results: </strong>In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research.</p><p><strong>Conclusions: </strong>This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.</p>","PeriodicalId":17993,"journal":{"name":"Laboratory Animal Research","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238008/pdf/","citationCount":"1","resultStr":"{\"title\":\"Laboratory information management system for COVID-19 non-clinical efficacy trial data.\",\"authors\":\"Suhyeon Yoon, Hyuna Noh, Heejin Jin, Sungyoung Lee, Soyul Han, Sung-Hee Kim, Jiseon Kim, Jung Seon Seo, Jeong Jin Kim, In Ho Park, Jooyeon Oh, Joon-Yong Bae, Gee Eun Lee, Sun-Je Woo, Sun-Min Seo, Na-Won Kim, Youn Woo Lee, Hui Jeong Jang, Seung-Min Hong, Se-Hee An, Kwang-Soo Lyoo, Minjoo Yeom, Hanbyeul Lee, Bud Jung, Sun-Woo Yoon, Jung-Ah Kang, Sang-Hyuk Seok, Yu Jin Lee, Seo Yeon Kim, Young Been Kim, Ji-Yeon Hwang, Dain On, Soo-Yeon Lim, Sol Pin Kim, Ji Yun Jang, Ho Lee, Kyoungmi Kim, Hyo-Jung Lee, Hong Bin Kim, Jun Won Park, Dae Gwin Jeong, Daesub Song, Kang-Seuk Choi, Ho-Young Lee, Yang-Kyu Choi, Jung-Ah Choi, Manki Song, Man-Seong Park, Jun-Young Seo, Ki Taek Nam, Jeon-Soo Shin, Sungho Won, Jun-Won Yun, Je Kyung Seong\",\"doi\":\"10.1186/s42826-022-00127-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research.</p><p><strong>Results: </strong>In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research.</p><p><strong>Conclusions: </strong>This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.</p>\",\"PeriodicalId\":17993,\"journal\":{\"name\":\"Laboratory Animal Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2022-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238008/pdf/\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Laboratory Animal Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s42826-022-00127-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory Animal Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s42826-022-00127-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Laboratory information management system for COVID-19 non-clinical efficacy trial data.
Background: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research.
Results: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research.
Conclusions: This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.