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- Title
- Laboratory information management system for COVID-19 non-clinical efficacy trial data
- Author(s)
- S Yoon; H Noh; H Jin; S Lee; S Han; S H Kim; J Kim; J S Seo; J J Kim; I H Park; J Oh; J Y Bae; G E Lee; S J Woo; S M Seo; N W Kim; Y W Lee; H J Jang; S M Hong; S H An; K S Lyoo; M Yeom; H Lee; B Jung; Sun Woo Yoon; Jung-Ah Kang; Dae Gwin Jeong; S Won; J W Yun; J K Seong
- Bibliographic Citation
- Laboratory Animal Research, vol. 38, no. 1, pp. 17-17
- Publication Year
- 2022
- Abstract
- 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.
- Keyword
- SARS-CoV-2COVID-19Non-clinicalLaboratory information management systemData
- ISSN
- 1738-6055
- Publisher
- Springer-BMC
- DOI
- http://dx.doi.org/10.1186/s42826-022-00127-2
- Type
- Article
- Appears in Collections:
- Division of Research on National Challenges > Bionanotechnology Research Center > 1. Journal Articles
- Files in This Item:
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