Yoon Suhyeon, Noh Hyuna, Jin Heejin, Lee Sungyoung, Han Soyul, Kim Sung-Hee, Kim Jiseon, Seo Jung Seon, Kim Jeong Jin, Park In Ho, Oh Jooyeon, Bae Joon-Yong, Lee Gee Eun, Woo Sun-Je, Seo Sun-Min, Kim Na-Won, Lee Youn Woo, Jang Hui Jeong, Hong Seung-Min, An Se-Hee, Lyoo Kwang-Soo, Yeom Minjoo, Lee Hanbyeul, Jung Bud, Yoon Sun-Woo, Kang Jung-Ah, Seok Sang-Hyuk, Lee Yu Jin, Kim Seo Yeon, Kim Young Been, Hwang Ji-Yeon, On Dain, Lim Soo-Yeon, Kim Sol Pin, Jang Ji Yun, Lee Ho, Kim Kyoungmi, Lee Hyo-Jung, Kim Hong Bin, Park Jun Won, Jeong Dae Gwin, Song Daesub, Choi Kang-Seuk, Lee Ho-Young, Choi Yang-Kyu, Choi Jung-Ah, Song Manki, Park Man-Seong, Seo Jun-Young, Nam Ki Taek, Shin Jeon-Soo, Won Sungho, Yun Jun-Won, Seong Je Kyung
Korea Mouse Phenotyping Center, Seoul National University, Seoul, 08826, Republic of Korea.
Institute of Health and Environment, Seoul National University, Seoul, 08826, Republic of Korea.
Lab Anim Res. 2022 Jun 28;38(1):17. doi: 10.1186/s42826-022-00127-2.
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.
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.
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.
随着涉及多个组织生成数据的大规模研究数量稳步增加，需要一个通用的可互操作格式的集成系统。为应对2019年冠状病毒病（COVID-19）大流行，全球正在开展多项开发疫苗和治疗方法的工作。因此，我们看到COVID-19数据呈爆炸式增长，同时参与COVID-19大流行研究的多个机构强烈要求实现数据互操作性。
在本研究中，采用了实验室信息管理系统（LIMS）方法，通过网络界面系统地管理来自多个机构的各种COVID-19非临床试验数据，包括死亡率、临床症状、体重、体温、器官重量、病毒滴度（病毒复制和病毒RNA）以及多器官组织病理学。实施该系统的主要目的是整合、标准化和整理从多个机构实验室收集的用于COVID-19非临床疗效测试的数据。六个动物生物安全3级机构证明了我们系统的可行性。通过最大化协作式高质量非临床研究显示出了显著益处。
这个LIMS平台可用于未来的疫情爆发，通过系统管理非临床动物研究的大量数据，加速医疗产品的开发。
