Fast-Track COVID-19 Research Programme

In a rapid response to the emerging COVID-19 pandemic, the BRCCH launched its Fast Track Call (FTC) for Acute Global Health Challenges in 2020.

The FTC's objectives were to quickly enable research to help immediately mitigate health challenges presented by the virus in the short-term and to contribute to preparedness and a reduced disease burden in the future.

Brief descriptions of each funded project can be found below. Click on the descriptions for further information and links to other resources associated with each project. 

Lessons from the Deceased to the Living and Back

At the outset of the COVID-19 pandemic, there were many unanswered questions about how the virus that causes the disease would affect human tissues and organs. Through carrying out post-mortem examinations and investigating the effects of the virus on the tissues and organs of those who had experienced severe COVID-19, this consortium provided crucial information about the effects of the disease on the human body’s circulatory system, immune system and brain.

Identification, Characterisation, and Optimisation of High-Affinity Antibodies Against SARS-CoV2

In this project, crucial new understanding was developed of the adaptive immune responses elicited by two subsets of immune cell types in response to infection with the COVID-19 virus: virus-killing CD8+ T cells and antibody-producing B cells. Profiles were provided of these cells’ characteristics and functions during the acute infection phase and during the cells’ memory phase at both six- and twelve-months post-infection. 

High-throughput Testing of SARS-CoV-2 Infection, Evolution and Immunity by Deep Sequencing

Protein engineering was used to profile the evolution of SARS-CoV-2 and its escape from the human immune system. Testing was carried out to ascertain how well the variants interacted with human cell receptors and their capability to evade neutralising antibodies. The data collected was used to train a deep learning model that is capable of predicting the efficacy of various therapeutic antibody candidates against different combinations of mutations. 

Mitigation Strategies for Communities with Covid-19 Transmission in Lesotho Using Artificial Intelligence on Chest X-Rays and Novel Rapid Diagnostic Tests (MistraL)

Project partners developed and tested disease detection and control strategies specifically tailored to Lesotho. Following an initial disease screening and triage phase, individuals received a suite of integrated tuberculosis (TB), COVID-19 and human immunodeficiency virus (HIV) diagnostic services and were referred for treatment if needed.

A Novel Rapid, Mobile, Lab-Independent and Sensitive SARS-CoV-2 Test at the Point of Need, to Break the Chain of Infection

COVID-19 testing often relied on people attending testing facilities when they experienced symptoms. The virus therefore often went undetected in asymptomatic people who were nevertheless able to infect others. This consortium developed an accurate, inexpensive diagnostic test for COVID-19 that can be implemented by people within their own homes, before they are symptomatic. 

Immune Senescence in COVID-19

Researchers examined how patients’ responses to infection with SARS-CoV-2 lead to different acute or prolonged disease outcomes and patients' underlying biological differences underpinning different disease courses. Using a statistical modelling approach, the trajectories of different people’s experiences of COVID-19 were reconstructed. A model was then built which is capable of using data about specific biological markers soon after disease onset, to predict an individual’s prognosis.

Using Model-based Evidence to Optimise Medical Intervention Profiles and Disease Management Strategies for COVID-19 Control

This project's multidisciplinary team of researchers combined expertise in mathematical modelling and epidemiology to develop and put into operation a model-based decision framework called OpenCOVID. This was used to inform the optimal properties of strategies for the delivery of disease prevention and therapeutic approaches.

COVent – Improve Ventilation Safety by Means of Intra-Tracheal Pressure Monitoring – A Short-term Solution

The researchers involved in this project developed a novel intra-tracheal pressure monitoring system. The device works in conjunction with a modified ventilator controller. These developments provide a practical solution to reduce the risks associated with the mechanical ventilation of patients suffering from respiratory failure (a common complication of COVID-19).

Development and Validation of a Lateral Flow Immuno-Assay to Diagnose Covid-19 in Saliva (DAVINCI)

The DAVINCI consortium developed and validated a test, suitable for home use, that uses saliva samples to identify the presence of SARS-CoV-2 antigens and antibodies. The test can therefore simultaneously inform the user whether they are currently infected with the COVID-19 virus and whether they have had prior exposure to the virus. A smartphone app was also developed to support the test user.

peakPCR: Making DNA Analyses Faster and More Accessible

This project, carried out by an international team of biologists, biotechnologists and chemical and mechanical engineers, led to the development of a radically new rapid, portable polymerase chain reaction (PCR) testing platform called ‘peakPCR’. This device can detect several different viral and bacterial infections in a short time with high reliability. The relatively low cost of the device makes it a comparatively feasible option for use in low-resource settings.

Identifying Pathogenic Genetic Variants with Gene Editing

To study the disease-causing effects of genetic mutations in human cells, the precision gene editing tool CRISPR was used to introduce mutations into cells. High-throughput technologies were then used to examine the effects of these mutations on cells. Compelling evidence was produced that these techniques are effective in identifying well-known pathogenic mutations as well as predicting the likely pathogenicity of previously unknown mutations. 

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