Diagnostic testing plays a critical role in any large-scale biological event. The ability to quickly separate infected from healthy individuals, or to understand if an environment is contaminated, requires rapid, accurate and abundant testing capabilities. For the past two decades, LLNL bioscientists and bioengineers have developed, deployed and/or commercialized numerous diagnostic technologies. We are applying this expertise to COVID-19 with several research efforts.
Rapid, point-of-need diagnostics
- We are adapting our Viral Sensing Diagnostic system to detect the virus that causes COVID-19. This genetic diagnostic system will provide medical professionals, emergency responders and others with an inexpensive, non-invasive and highly sensitive point-of-need tool for rapid (<30 minutes) detection of COVID-19.
Diagnostics to assess co-infection
- We are updating our DNA microarray system, the Lawrence Livermore Microbial Detection Array (LLMDA), which is useful for conducting broad spectrum analysis of all known/sequenced viruses, bacteria and fungi (>12,000 microbes), to include accurate detection of the virus that causes COVID-19. In a clinical diagnostic setting, this system can help assess co-infection with other viruses or bacteria to help better inform clinical care.
Evaluating options to accelerate RNA extraction
- The time required to extract RNA from clinical samples (first step in the process to test for the virus that causes COVID-19) is time-consuming, and there also is a critical shortage of RNA extraction kits. To help address these issues, LLNL is part of a multi-laboratory DOE team of experts working to identify options that will accelerate testing.
- Accelerated publication - High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models
- Publication - Quantitative Fit Evaluation of N95 Filtering Facepiece Respirators and Coronavirus Inactivation Following Heat Treatment
- Accelerated publication - Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing
- October 21, 2021 - LLNL joins Human Vaccines Project to accelerate vaccine development and understanding of immune response
- October 11, 2021 - Tackling the COVID-19 pandemic
- June 2, 2021 - Decontaminating N95 masks for reuse
- May 3, 2021 - Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models
- April 1, 2021 - COVID-19 HPC Consortium reflects on past year
- February 19, 2021 - Physics of particle dispersion may lend insight into reducing the airborne spread of COVID-19 virus
- January 19, 2021 - LLNL and United Kingdom company to collaborate on development of universal coronavirus vaccine
- November 18, 2020 - Model for COVID-19 drug discovery a Gordon Bell finalist
- November 12, 2020 - LLNL welcomes 'Ruby' supercomputer for national nuclear security mission and COVID-19 research
- November 4, 2020 - Mammoth computing cluster to aid COVID research
- October 19, 2020 - AI gets a boost via LLNL, SambaNova collaboration
- October 7, 2020 - Corona supercomputer gets funding for COVID-19 work
- June 25, 2020 - Lab technologies help fight COVID-19
- June 9, 2020 - Lab, BMI produce FDA-approved emergency ventilator
- June 8, 2020 - Multi-lab research to improve COVID-19 diagnostics
- May 29, 2020 - Lab team studies calibrated AI and deep learning models to more reliably diagnose and treat disease
- May 21, 2020 - Lab provides assistance in national swab shortage
- May 19, 2020 - COVID-19 research goes public through new portal
- May 14, 2020 - Deactivating coronavirus on N95 respirators for reuse
- May 1, 2020 - LLNL’s new machine learning platform generates novel COVID-19 antibody sequences for experimental testing
- April 29, 2020 - LLNL develops ‘stopgap’ ventilator for COVID-19 use
- April 21, 2020 - Upgrades for LLNL supercomputer from AMD, Penguin Computing aid COVID-19 research
- March 26, 2020 - New partnership to unleash U.S. supercomputing resources in the fight against COVID-19
- March 26, 2020 - Lab antibody, anti-viral research aids COVID-19 response
- February 3, 2020 - Lawrence Livermore researchers release 3D protein structure predictions for the novel coronavirus
- April 21, 2021 - Corona vs coronavirus: AMD and Penguin Computing to upgrade aptly named LLNL supercomputer
- April 1, 2021 - Beating back the coronavirus requires a bigger arsenal
- March 26, 2021 - The COVID-19 HPC Consortium looks ahead to a ‘National Strategic Computing Reserve’
- March 22, 2021 - What is a universal coronavirus vaccine and is it achievable?
- February 21, 2021 - 'This has to be the moment' to invest in coronavirus vaccines and treatments against future pandemics, experts warn
- February 11, 2021 - Worries About Viral Resistance to Covid-19 Vaccines Are Overdone
- January 13, 2021 - Why There's Still Need for Rapid Accessible Pathogen Testing, During and After the Crisis
- November 4, 2020 - AMD-Supermicro-Cornelis (Omni-Path) ‘Mammoth’ cluster at LLNL targets COVID-19
- May 5, 2020 - Advanced manufacturing innovation helps industry in COVID-19 fight
- May 5, 2020 - 3-D printed COVID-19 test swabs pass their own tests
- May 4, 2020 - Swab Shortage: FATHOM & Abiogenix Bridge the Gap with 3D Printed NP Swabs
- April 14, 2020 - LLNL’s Jim Brase explains how DOE labs are fighting (and coping with) COVID-19
- February 5, 2020 - Coronavirus: Lawrence Livermore Lab researchers examine virus in hopes of blocking, treating it
For more information about the U.S. government's response to COVID-19, see coronavirus.gov and usa.gov/coronavirus. For the latest public health and safety information from the Centers for Disease Control and Prevention, see cdc.gov/coronavirus.