| Autor: |
Melissa Laverack, Rebecca L. Tallmadge, Roopa Venugopalan, Daniel Sheehan, Scott Ross, Rahim Rustamov, Casey Frederici, Kim S. Potter, François Elvinger, Lorin D. Warnick, Gary A. Koretzky, Robert Lawlis, Elizabeth Plocharczyk, Diego G. Diel |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Viruses, Vol 15, Iss 7, p 1555 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1999-4915 |
| DOI: |
10.3390/v15071555 |
| Popis: |
The unprecedented COVID-19 pandemic posed major challenges to local, regional, and global economies and health systems, and fast clinical diagnostic workflows were urgently needed to contain the spread of SARS-CoV-2. Here, we describe the platform and workflow established at the Cornell COVID-19 Testing Laboratory (CCTL) for the high-throughput testing of clinical samples from the university and the surrounding community. This workflow enabled efficient and rapid detection and the successful control of SARS-CoV-2 infection on campus and its surrounding communities. Our cost-effective and fully automated workflow enabled the testing of over 8000 pooled samples per day and provided results for over 2 million samples. The automation of time- and effort-intensive sample processing steps such as accessioning and pooling increased laboratory efficiency. Customized software applications were developed to track and store samples, deconvolute positive pools, track and report results, and for workflow integration from sample receipt to result reporting. Additionally, quality control dashboards and turnaround-time tracking applications were built to monitor assay and laboratory performance. As infectious disease outbreaks pose a constant threat to both human and animal health, the highly effective workflow implemented at CCTL could be modeled to establish regional high-capacity testing hubs for infectious disease preparedness and emergency response. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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