| A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | |
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1 | Requesting Institution/ Organisation | Applicant Name | Purpose | Material Requested | Funding | Decision | Request Date | Decision Date | Publication DOI | Other outcomes | |||||||||||||||
2 | University of Oxford | Theresa Lambe & Sarah Gilbert | Vaccine Development | Sera - 5ml | Internal funding | Approved | 29/02/2020 | 24/03/2020 | |||||||||||||||||
3 | Liverpool School of Tropical Medicine | Emily Adams | Assay Development | Serum from 10 convalescent patients 5ml | DFID/Wellcome | Approved | 10/03/2020 | 24/03/2020 | https://doi.org/10.12688/wellcomeopenres.16522.1 | ||||||||||||||||
4 | Regeneron | Sumathi Sivapalasingam | Production of therapeutic antibodies from B cells | 50ml of whole blood | Internally funded | Approved | 10/03/2020 | 24/03/2020 | |||||||||||||||||
6 | University of Edinburgh | Francisca Mutapi | Develop an elisa-based immunoassay for detecting Covid-19 antibodies | 100ul convalescent plasma/serum. 12.06.2020 1ml WO | We (NIHR Unit Tackling Infections to benefit Africa (TIBA) at the University of Edinburgh) are funded by the UK National Institutes of Health Research through the Global Health Research Fund. As part of this funding we were instructed to use some of the funding for research to respond to national of global health emergencies | Approved | 16/03/2020 | 24/03/2020 | |||||||||||||||||
8 | AstraZeneca | Mark Esser | Identify B cells that secrete neutralizing antibodies against the SARS-CoV-2 virus. | Convalescent serum – 5ml | Internal funding | Approved | 17/03/2020 | 24/03/2020 | |||||||||||||||||
9 | Ministry of Defence | Stevan Emmett | Partial validation of 3 commercially available lateral flow cassettes. | Day 1,3 and 9 plasma or serum | Governmentally funded | Approved for diagnostic evaluation platform | 20/03/2020 | 13/04/2020 | |||||||||||||||||
10 | Brighton and Sussex Medical School | Florian Kern | Expansive peptide array to detect antibody responses spanning full proteome | 10-20ul serum. Recovered patients. Clinical course must be known. ~ 100 samples. | Not yet funded | Approve if funded | 22/03/2020 | 13/04/2020 | |||||||||||||||||
11 | Health Protection Scotland | Antonio Ho | Validate a serological ELISA assay for immunological response curve | Serum samples at least 500ul. Helpful if it's pared as acute and convalescent. N=50. | Governmentally funded | Approved | 28/03/2020 | 13/04/2020 | |||||||||||||||||
12 | Quotient BD | Reginald Clayton | Diagnostic serology assay for use in hospitals and blood testing insitutions. | 5ml plasma or serum samples. Preferably dozens | Quotient R&D budget. | Approved | 28/03/2020 | 13/04/2020 | |||||||||||||||||
13 | University of Oxford | Roman Fischer | Determine the plasma proteome in COVID-19 patients | Plasma - 50µl from 400 patients | Internal funding | Approved | 02/04/2020 | 13/04/2020 | |||||||||||||||||
14 | Imperial College London | Katrina Pollock | Understanding the pathogenesis through standard lab techniques like ELISAs | Serum and Plasma. 1ml vial of urine and oral swabs if available. Male patients moderate and severe | MRC/UKRI rolling funding call | Approved | 03/04/2020 | 13/04/2020 | |||||||||||||||||
15 | University of Edinburgh | Chris Haley | GWAS of DNA methylation | Access to DNA samples | Funding pending | Approved | 06/04/2020 | 13/04/2020 | |||||||||||||||||
16 | University of Edinburgh | Alex von Kriegsheim | Quantify lipids and metabolites using mass spectrometry lipidomics/ Steroid analyses | Plasma - 100µl from 600 patients - 12.06.2020 request changed to 500ul for steroid analyes, 60 severe, 60 mild, 80 unifected (unavailable) | Funding pending | Approved | 06/04/2020 | 13/04/2020 | |||||||||||||||||
17 | University of Liverpool | Simon Abrams | Validate the multivariable prognostic model established in Chinese cohorts. Compare prognostic variable with circulating histones. | Plasma - 500µl from 200 patients | Internal funding | Approved | 06/04/2020 | 13/04/2020 | |||||||||||||||||
18 | University of Liverpool | James Stewart | Development and selection of antigens for diagnostics and vaccine candidates. Establish ELISAs using antigen proteins | 2ml convalescent serum. 6+ patients. | Core BBSRC funds. University of Kent funds. | Approved for diagnostic evaluation platform | 07/04/2020 | 13/04/2020 | |||||||||||||||||
19 | University of Liverpool | Qingging Zhang | Super-neutralising antibodies pull-down using Spike protein conjugated beads | Serum – 10ml from 20 patients | NHS R&D grant | Approved | 08/04/2020 | 13/04/2020 | |||||||||||||||||
21 | University of Edinburgh | Damian Mole | Stratification of COVID-19 patients using 2 established metabolic pathway panels. | N=500 X 100uL of plasma or serum | MRC fellowship and existing industry collaborations | Approved | 13/04/2020 | 28/04/2020 | |||||||||||||||||
22 | British HIV Association Group | Sophie Kelly | Investigate infection rate and disease course of COVID-19 in HIV patients. | Periodic reports of HIV positive patients. Access to immunology, serology and PCR results. Every 1-3 months. Samples: Serum/plasma 500ul from as many HIV-positive patients as possible. | Internally funded | Approved | 13/04/2020 | 28/04/2020 | 10.1093/cid/ciaa1605 | ||||||||||||||||
23 | Imperial College London | Roya E Haghihat-Khah | RNA seq to investigate differential gene expression between patient groups (eg age, sex, hypertension treatment and recovery) | RNA from Oracol or viral throat swabs. RNA or materials from 300 patietns. | UKRI funding in process | Approved | 14/04/2020 | 28/04/2020 | |||||||||||||||||
24 | University College London | Benny Chain | Machine learning to identify T-cell receptor signature that predicts clinical outcomes. | Blood RNA (600ng extracted from tempus tubes) Day 1,3,9 and 28. 300 longitudinal patients. | UKRI funding application depending on sample access | Approved | 14/04/2020 | 28/04/2020 | |||||||||||||||||
25 | University of Oxford | Susie Dunachie | Phenotypic and functional T-cell responses to COVID-19 vaccine targets and identify metabolism differences in Type 2 diabetes patients. | 4 million PBMCs from 50 COVID-19 patients with and without Type 2 diabetes at Day 1 and Day 28 (where available). Linked patient metadata including age, gender, disease severity, supportive care received, trial treatments and outcome. Matched for age, gender and disease severity at Day 1. | Salary and lab running costs covered by existing grants. Applying for Diabetes UK COVID-19 Rapid Response for further funding. | Approved | 20/04/2020 | 28/04/2020 | PITCH Study protocol | ||||||||||||||||
27 | University of Liverpool and Liverppol University Hospitals NHS Foundation Trust | Douglas B Kell (PI) Andrew S Davison | Untargeted metabolomics of serum samples during COVID-19. Longitudinal sampling to asses relationships between metabolites and infection, disease progression, severity and outcome. Samples will be analysed using high-resolution mass spectrometry. | Surplus serum and anonymised metadata (age, sex, disease status and other clinical information) collected in Liverpool Clinical Laboratories. Each sample requires a minimum volume of 150ul. | Funding pending | Approved | 21/04/2020 | 28/04/2020 | |||||||||||||||||
28 | University of Edinburgh | Yanick Crow | Measuring INF-alpha in COVID-19 patients using an ultrasensitive digital ELISA assay | Serum or plasma (100ul) | Funding in place for 100 samples. Funding pending for 1000+ samples. | Approved | 24/04/2020 | 28/04/2020 | https://doi.org/10.1101/2020.10.08.20209411 | ||||||||||||||||
29 | University of Liverpool | Jonathan Cattrall | Investigating neurological disease in COVID-19 through clinical features, risk factors and analysis of CSF and sera to understand disease mechanisms. | Data - analysis of patient data with features suggestive of neurological disease. Determine risk factors for neurological disease. If protocols and ethics allow, detailed questionnaire to be sent to research sites and contact patients for more info re outcome. Samples- CSF (2ml - min of 100ul doable) and serum (2ml). Unsure how many samples may be available. | Funding from NIHR HPRU in EZI | Approved | 24/04/2020 | 28/04/2020 | |||||||||||||||||
30 | McGill Quebec, Canada | Brent Richards | Elucidate host genetic determinants and develop predictive models for COVID-19 severity by using phenotypic data. | All phenotypic data (biochemical, hematological, immunological data), host genotype data, RNA seq data (D1,3,9 and 28). Viral sequencing data for host genetics and viral sequence. | Quebec provincial government and Fonds de recherche du Quebec - Sante. | Approve for collaboration | 29/04/2020 | 30/04/2020 | |||||||||||||||||
31 | University of Leicester | Kamlesh Khunti | Identify vulnerable groups at risk of disease. DHSC letter of support. | Clinical data collected on admission, daily and outcome forms. Differences in outcomes based on ethnicity, co-morbidities, obesity and socio-economic status. | NIHR ARC East Midlands | Approved | 30/04/2020 | 30/04/2020 | |||||||||||||||||
32 | University of Edinburgh | Gwo-Tzer Ho | Investigate DAMPs assays as prognostic marker. Drug treatments that block the action of DAMPs. Clarify role of gut ACE2 expression and transmissibility. Understanding gut microbiome and whether clinial outcome can be predicted from GI microbiome data. | Serum and plasma (5mls) - 200 patients (100 ICU vs 100 non-ICU). Stools (5-10ml) 1000 patients with associated clinical data (cluster 3 - with GI symptoms vs non-GI symptoms). Clinical data - 1000 patients stratified by disease severity and clinical phenotype - with or without diarrhea. | Helmsley Trust, ERC, Scot Government RESAS, BBSCRC, and funds form Scottish Senior Fellowship. | Approved | 01/05/2020 | 01/05/2020 | |||||||||||||||||
33 | University of Liverpool | Lance Turtle Julian Hiscox | Determining the ability of culturing SARS-CoV-2 virus using respiratory tract swabs. | 20-50 respiratory tract swabs from patients with severe COVID-19 and mild/moderate disease respectively. | Internally funded | Approved | 01/05/2020 | 04/05/2020 | |||||||||||||||||
35 | Imperial College London | Zoltan Takats James Kinross Lauren Ford *In combination with Request 47 Dumas | Ambient mass spectrometry techniques for metabolite biomarkers of COVID-19 status and host immune response and a protease assay for a rapid, point-of-care test. | Combined nose and throat swabs, otherwise a throat swab or nasopharyngeal swab alone. As many as possible. | Imperial Biomedical Research Centre. | Approved | 04/05/2020 | 04/05/2020 | |||||||||||||||||
36 | Imperial College London | Marc-Emmanuel Dumas Julian Griffin Zoltan Takats Peter Openshaw *In combination with Request 43 Takats | Metabolomic profiling of COVID-19 to improve mechanistic understanding, provide insights into secondary biological effects and further develop prognostic markers. | All 650 patients at 4 timepoints - 2600 samples. Plasma (or serum) 375ul per sample. Urine 275ul per sample. Stool 500mg per sample. Swab metabolomics - Prof Takats application (Request 43) | Imperial Biomedical Research Centre. | Approved | 04/05/2020 | 04/05/2020 | |||||||||||||||||
37 | University of Liverpool University of Sheffield University of Oxford | Lance Turtle Paul Klenerman Thusan DeSilva Susie Dunachie Ellie Barnes Alex Mentzer | Phenotypic and functional T-cell response to SARS-CoV-2 including vaccine targets. Greater capacity and samples than original ISARIC-4C aims of characterising the immune response. | 30-40 million PBMCs from all donors sampled. Final sample sizes to be determined as part of the ISARIC-4C follow up WP9. | Internally funded by University of Liverpool and University of Oxford. | Approved | 04/05/2020 | 04/05/2020 | PITCH Study protocol | ||||||||||||||||
38 | University of Oxford | Andrew Soltan | AI algorithms to rapidly identify COVID-19 illness at the front-door of hospitals. | Essential data: Admission blood tests - FBC, U&Es, LFTs, CRP, Clotting function, Microbiology, SARS-CoV-2 results, influenza results (where tested) admission observations (if available). Desirable: Single set of pre-morbid blood tests values for the same parameters. | ESPRC | Approved | 05/05/2020 | 05/05/2020 | |||||||||||||||||
39 | Imperial College London | Roberta Forlano Mark Thurz Pinelopi Manousou Benjamin Mullish | Risk factors of COVID-19 patients with non-alcoholic fatty liver disease | Clinical data - demographics, blood test results, details regarding presentation, admission and clinical outcomes. | Imperial Biomedical Research Centre. | Approved | 05/05/2020 | 05/05/2020 | |||||||||||||||||
40 | Mathworks | Peter Maloney | Development of a multifactorial RSM tool to improve outcomes and triaging of patients | Raw data used to create survival from onset plot and Symptoms on presentation to hospital bar graph. | Internally funded | Approved | 05/05/2020 | 06/05/2020 | |||||||||||||||||
41 | London School of Hygiene and Tropical Medicine | Fiona Woo Katherine Atkins Stephane Hue | Phylogenetic modeling to evaluate the role of hospital-acquired infection in sustaining UK transmission | Request for CO-CIN data. For all patients with positive SARS-CoV-2 test and viral sequence from nasal/saliva swab sample. Data variables - employed as healthcare worker, DOB/age, outer postcode, onset data, admission date, readmission?, transfer from other facility? collection date for samples, outcome and date, full lenght viral genome seq for SARS-CoV-2 | Internally funded | Approved | 06/05/2020 | 06/05/2020 | |||||||||||||||||
43 | Liverpool University Hospitals Foundation NHS trust and University of Liverpool | Sree Subramian | Link between Vit D deficiency and at risk groups for severe COVID-19 illness and death. | Plasma or serum (500ul). All patients fom Tier 1, or 500 approx. would require 0.5ml plasma or serum (they have 250 tier 0 patients of their own) | £20 000 funding in place for Vit D assays. | Approved for Tier 0 | 07/05/2020 | 08/05/2020 | |||||||||||||||||
44 | Liverpool School of Tropical Medicine | Ryan Robinson Andrea Collins | Investigate reationship between immunosuppressive treatments and mortality risk of COVID-19 patients. | Immunosuppressive therapy duration and type, demographics, requirement for HDU/ITU admission, mortality rate and duration of inpatient stay. | Internally funded | Approved | 07/05/2020 | 08/05/2020 | |||||||||||||||||
45 | Trisomy 21 Research Society | Andre Strydom Stephanie Sherman Mara Dierssen | Impact of COVID-19 on individuals with Down Syndrome. | Clinical data incl demographics, co-morbidities, medication,treatment, outcomes etc. | LuMind IDSC Foundation and other Down Syndrome organisations | Approved | 11/05/2020 | 12/05/2020 | 10.1101/2020.11.03.20225359. | ||||||||||||||||
46 | University College London | Nikhil Sharma | Investigating differences in the gut microbiome and clinical course of COVID-19 | Stool samples (<0.5g) - 1000 (different subsets) and clinical metadata | Funding pending | Approved | 12/05/2020 | 12/05/2020 | |||||||||||||||||
47 | University of Sheffield | Felipe Soares | An intelligent system for the pre-triage of COVID-19 suspected patients based on simple blood exams and data science to benefit resource-poor settings in LMICs. | Clinical data: Demographics, onset and admission, vital signs at admission, co-morbidities, daily lab results, daily treatment, pathogen testing, treatment, outcome. | Funding pending | Approved | 14/05/2020 | 15/05/2020 | |||||||||||||||||
49 | University of Miami | Manish Kuchakulla | AI tool to generate a neural network to improve diagnosis and predicting prognosis of disease. | Clincal data: demographics, symptoms, lab values and co-morbidities. | Part internally funded, part funded by philanthropy. | Approved | 15/05/2020 | 15/05/2020 | |||||||||||||||||
50 | Loughborough University | Liam Heaney | The impact of the gut microbiome for the risk/severity of COVID-19, by investigating gut microbiota-derived metabolites using mass spectrometry-based assays. | Serum (250ul) maximum number available at visit 1. Clinical data - demographics, laboratory results, and outcome data. | Funding application dependent on sample approval. | Approved | 18/05/2020 | 19/05/2020 | |||||||||||||||||
51 | University of Oxford | Emily Thornton | Gut inflammation and the microbiome and adverse patient outcomes | Stool samples (>500mg) as early in disease matched with immunophenotyping data from ISARIC, clinical phenotype and routine lab data. | Internal funding, will apply for external funding with pilot data. | Approved | 18/05/2020 | 19/05/2020 | |||||||||||||||||
52 | BG Research | Nelson Nazareth | Resubmission as per feedback - Direct RT-qPCR amplification and detection of SARS-CoV-2 from nasal swab eluates, saliva, etc. Working in Emily Adams in LSTM lab. | 40 positive combined nose and throat swabs or alone. Preferably from same individual from day 1,3,9 as per protocol or 40 from day 1. | DASA accelerator COVID research program | Approved | 19/05/2020 | 22/07/2020 | |||||||||||||||||
53 | CRN Yorkshire and Humber | Rebecca Byrne | The data is to better understand the relationship between ethnicity and both participation in COVID research as well understanding the impact on individuals from BAME communities. | Access to CRF data - specifically related to ethnicity and outcome measures | Internally funded | Approved | 19/05/2020 | 25/06/2020 | |||||||||||||||||
54 | Royal Wolverhampton NHS Trust | Srinivisan Venkatachalam | COVID Hyperinflammation study. Use of ISARIC-4C dataset for the Wolverhampton patients to support COVIDHI study. | Clinical characteristics of all COVID patients entered into ISARIC from The Royal Wolverhampton NHS Trust | Internally funded | Approved | 26/05/2020 | 22/07/2020 | |||||||||||||||||
55 | University of Edinburgh | Andrea Wilson | Data-driven now-casting & fore-casting of health-care resource requirements associated with COVID-19 in Edinburgh and South-East Scotland | CO-CIN data from Tiers 0. 1, 2 from Scotland and rest of UK. | Internally funded | Approved | 27/05/2020 | 03/06/2020 | |||||||||||||||||
58 | University of Glasgow | Miguel Pineda | Influence of human glycosylation pathways in COVID-19 clinical outcome | RNA from infected tissues, throat swabs or nasal specimens, Samples from 2 patients groups: mild and severe disease outcomes (10-15 patients per group) Days 1,3,9 and 28. Associated clinical data | Funding for pilot study. Will apply for further funding with IDAMAC support. | Approved | 02/06/2020 | 22/07/2020 | |||||||||||||||||
60 | COPD Consortium/Imperial | Paul Cullinan Chloe Bloom Brian Lipworth Thomas Drake Annemarie Docherty | Does inhaled corticosteroid use have an impact on clinical outcomes in patients with COVID-19 disease and either asthma or other chronic respiratory disease; and examindation of UK ISARIC data? | All data from CRF v9.4, all admissions to date of data access; to include relevant measurements in plasma and other biosamples. | Internal funding | Approved | 09/06/2020 | 22/07/2020 | |||||||||||||||||
61 | Medway NHS Foundation Trust | Annette Woods | Determining whether medication taken by patients are protective or limits the prorgress of disease specific to Medway NHS Trust | Site specific data from patients - demographics and all data submitted so far. | Initial review do not need funding, further funding applications if succesful. | Approved | 10/06/2020 | 22/07/2020 | |||||||||||||||||
62 | Non-academic team | Rory Dunne | Aid diagnosis and prognostic evaluation by using cytokine profiles to distinguish between concurrent outbreaks of influenza and coronavirus | Demographics, outcomes, clinical data and cytokine data | Self-funded, will apply for further funding if succesful | Approved | 11/06/2020 | 22/07/2020 | |||||||||||||||||
63 | West Hertfordshire Hospitals NHS Trust | Rama Vancheeswaran | Validation cohort for risk prediction study with longer term outcomes called PREDICT COVID. | Data from 5000 patients in population for external validation tool. | Internally funded | Approved | 11/06/2020 | 22/07/2020 | |||||||||||||||||
64 | University of Glasgow | Colin Berry Alex McConnachie John Cleland Antonia Ho | Characterise cardiac risk in COVID-19 to guide clinicians on risk stratification and therapy in high-risk groups. | Database access | Internally funded | Approved | 12/06/2020 | 22/07/2020 | |||||||||||||||||
65 | Queen's University Belfast | Ultan Power | Screen FDA-approved drugs for antiviral and anti-inflammatory activities in vitro - using viral strains for validation. | Access to 5 anonymised clinical samples (nasal/throat swabs or nasopharyngeal aspirates) from SARS-CoV-2 patients from different geographical locations. Access to 5 low passages (P4) SARS-CoV-2 strains. | UKRI/NIHR COVID-19 Rapid Response | Approved | 16/06/2020 | 22/07/2020 | |||||||||||||||||
66 | MC Diagnostics | Peter Maguire | Commercial - HLA typing | 1ug DNA per patient, capacity for over 1000 - application through GenoMICC. | Internally funded | Approved | 16/06/2020 | 22/07/2020 | |||||||||||||||||
67 | Epsom & St Helier University NHS | Rachel Wake | Investigating Trust specific nosocomial transmission to assist triaging and cohorting to prevent viral exposure to susceptible patients. | Tier 0 data collected at Epsom & St Heliers | Internally funded | Approved | 16/06/2020 | 22/07/2020 | |||||||||||||||||
68 | University College London Hospital, NHS Foundation Trust | Kevin Fong | This is a high resolution, agent based mathematical model developed with the intention of delivering improved capability to model non-pharmaceutical interventions. | These data will be used to inform epidemiological modelling and refine model assumptions. | NHS England | Approved | 19/06/2020 | 18/12/2020 | |||||||||||||||||
70 | Crick Institute | Andrew Bretherick, Markus Ralser, Kenneth Baillie | Investigate plasma proteome to inform clinical practice thourgh trajectories and associations, prognostic models of disease outcome and identify novel potential therapeutic targets | 40ul EDTA plasma - serial samples n=300. Tier 0 data - genetic data and demographic and clinical information. | Francis Crick Institute | Approved | 22/06/2020 | 22/07/2020 | |||||||||||||||||
72 | NHS Greater Glasgow & Clyde | Michael Murphy | We will produce a point of care antibody/immunoassay, building upon our recognised track record of sensitivity equivalence to ELISA demonstrated in serum and time to result <10 mins. We will translate this novel approach for use with SARS-nCoV-19 markers (indicating ongoing infection) and antibodies (indicating past infection). Within four months we will deliver a fully operational prototype validated with clinical COVID-19 samples. Importantly, we have engaged both industrial and clinical collaborators to unlock immediate validation and mass manufacture in Scotland, UK. | 15 x 1ml saliva samples from COVID-19 patients. Corresponding data if possible. | CSO grant | Approved | 26/06/2020 | 22/07/2020 | |||||||||||||||||
73 | University of Leeds | Jim Robinson | Locus specific genotyping of the Fc Gamma locus | Genomic DNA or cell pellets. Minimum of 300ng DNA required. Associated ISARIC clinical data | MRC CIC | Approved | 01/07/2020 | 22/07/2020 | |||||||||||||||||
76 | University Hospitals North Midlands NHS Trust | Jenny Wright | Can quantitative (real-time) polymerase chain reaction (PCR) cycle threshold (Ct) values be used to predict poor outcomes for patients infected with SARS-CoV-2? | Compare Ct value from local laboratory database for each patient in local ISARIC-4C dataset | Internally funded | Approved | 13/07/2020 | 25/08/2020 | |||||||||||||||||
78 | University of Sheffield Medical School | Endre Kiss-Toth | Profiling of myeloid cell sub-types, and investigating the dysregulation of their intracellular signalling networks, epigenetic changes and their functional consequences in health vs. disease to identify early markers predictive of the disease progression | 24ml whole blood from participants at their local site (Sheffield Teaching Hospitals NHS FT) | UKRI | Approved | 14/07/2020 | 25/08/2020 | |||||||||||||||||
80 | Explantlab | David Langton | Investigating variations in the major histocompatibility complex and COVID-19 | 75 COVID 19 patients who required respiratory support, no significant comorbidities, less than 65 years of age. DNA patients aged 20-50 | UKRI | Approved | 15/07/2020 | 25/08/2020 | |||||||||||||||||
82 | University of Liverpool | Anne McArdle with Ryan Thwaites | Chronic fatigue in COVID-19 survivors and role that pre-existing or newly developed cardiovascular and/or respiratory dysfunction plays and whether cytokine clusters can predict severity of fatigue | Anonymised metadata of participants including age, sex, race, and socio-economic status. Plasma samples (100ul) from up to 104 hospitalised patients for cytokine analysis using Luminex platform. These patients will be retrospectively recruited.Access to routine blood analysis if available. | UKRI funding pending. Pump-priming funds from University of Liverpool for pilot study. | Approved | 16/07/2020 | 25/08/2020 | |||||||||||||||||
83 | Imperial College London | Charis Pericleous | Autoantibodies associated with thrombosis and inflammatory vascular damage - prevalence, specificity, and persistence of the autoantibody response | 120ul of plasma from 100 ICU/HDU and 100 non-ICU/HDU COVID-19 patients from Tier 2 @ day 9 of sampling. Work can be carried out with residual samples from PO. Demographics, co-morbidities, clinical presentation, laboratory measurements, treatment outcome. | Imperial College COVID-19 FUND | Approved | 17/07/2020 | 25/08/2020 | |||||||||||||||||
86 | University of Oxford | Tom Beneke with Peter Openshaw & Alfredo Castello Palomares | Role of non-infectious SARS-CoV-2 RNA fragments in blood coagulation | Paired serum samples from 52 ISARIC-4C recruits where viral RNA was detected by qPCR (Ct < 37) - 140ul of each sample. If available, 20 paired plasma samples sets from COVID-naive recruits (1ml plasma each). | UKRI funding in process - as soon as confirmation received of sample access. | Approved | 23/07/2020 | 25/08/2020 | |||||||||||||||||
89 | Barts Health NHS Trust | Viyaasan Mahalingasivam | Investigate the long-term effects of COVID-19 on people with CKD to be undertaken at London School of Hygiene and Tropical Medicine. | Summary of how many patients from the ISARIC COVID cohort with/without CKD died and how many survived to discharge, stratified by other baseline characteristics. | Applying to NIHR | Approved | 30/07/2020 | 18/12/2020 | |||||||||||||||||
90 | Machine Learning and Biomarkers Group | Immo Weichert | Investigating predictors of COVID kidney - development of AKI, need for renal replacement therapy and long term renal impairment after becoming ill with SARS-CoV-2 infection | Access to the anonymised clinical data of the ISARIC-4C study for research purposes | Internally funded | Approved | 05/08/2020 | 25/08/2020 | |||||||||||||||||
91 | Addenbrooks Hospital | Edward Banham-Hall | Risk of death among young Caucasian patients to inform whether a controlled human infection model with COVID-19 can be safely conducted - part of due dilligence | Patients between 20-29 who died of COVID-19. Demographic data - 23 from ISARIC report | Funding pending - Wellcome Trust | Approved | 12/08/2020 | 25/08/2020 | |||||||||||||||||
93 | A Beclere-Saclay University Hospital | Roberta Raschetti | Systematic review on neonatal COVID-19 cases | Access to data by Swann et al. Data points: gestational age, birth weight, sex, c-section, 5min APGAR, comorbidities, DOL type of infection (congenital, intrapartum, postpartum) | Internally funded | Approved | 29/08/2020 | 18/12/2020 | |||||||||||||||||
97 | National Center for Biotechnology, Madrid -Spain | Juan Manuel Luque | COVID19PATGENOME https://devpost.com/software/covid19patgenome Bioinformatic analysis of genomic data from sequencing of COVID-19 patients that explains severity of this disease and to optimise treatment | Genomic data (FASTQ RNA/DNA files) from COVID-19 patients and their respective clinical data. | Grant funding requested/outstanding | Approved | 25/09/2020 | 11/12/2020 | |||||||||||||||||
98 | Department of Cardiology, Renmin Hospital of Wuhan University | Ze Chen | Test the performance of our CBC score on ISARIC 4C dataset to assess its generalisability to other cohorts, and vice versa, to test and compare ISARIC 4C Score as applied to our Hubei cohort. | Data on 35,463 patients included in the derivation dataset of 4C Score | Grants from Chinese funding bodies | Approved | 26/09/2020 | 11/12/2020 | |||||||||||||||||
99 | Medical Schooll of Athens | Eleni Karakike | Systematic review and meta-analysis of the incidence of (viral) sepsis (as defined by sepsis-3 criteria), associated with COVID-19. As part of a sepsis awareness initiative in COVID-19. Relevant protocol and design on PROSPERO database (CRD42020202018). | The following data are requested (prioritising the first bullet): Number of patients with Sequential Organ Failure Assessment (SOFA) score ≥2, consequent to COVID-19 infection Number of patients with Acute Respiratory Distress Syndrome (ARDS) Number of patients with Acute Kidney Injury Number of patients with Acute Kidney Injury Number of patients requiring vasopressors Number of patients presenting coagulopathy or Disseminated Intravascular Coagulation (DIC) Number of patients with lactate levels >2 mmol/l Number of patients with mental alterations Number of patients with bilirubin levels ≥ 1.2 mg/dl or Acute Liver Dysfunction Number of patients with SOFA score ≥2 who die within the hospital, and number of patients with SOFA score <2 who die within the hospital. | No funding is required for this work. | Approved | 27/09/2020 | 18/12/2020 | |||||||||||||||||
100 | UCL London Hospitals NHS Foundation Trust | Jessica Manson and Professor Liz Jury | Characterising the pathology underlying COV-HI for stratification of trials with immunomodulatory therapies, and potentially highlight novel therapeutic options | • Serum: 25 patients per group; 500ul serum sample from each at each time point: admission (baseline) and follow-up if available • Whole blood RNA sequencing data: from 25 patients in Cohort A vs 25 patients in Cohort B. • If RNA-seq data not available: whole blood RNA from 20 patients per group at Baseline (admission) and follow-up if available • Accompanying clinical characterisation and laboratory data associated with the samples provided. | Applying to UKRI | For collaboration | 28/09/2020 | 5/11/20 (SAMPLE) | |||||||||||||||||
102 | University of Edinburgh BHF Centre for Cardiovascular Sciences & Usher Institute | Ryan Wereski Professor Nicholas L Mills | COVIRNA project to generate a diagnostic test based on cardiovascular RNA biomarkers highly predictive of the clinical outcomes in COVID-19 | 700 unique patient samples of frozen plasma for extraction of RNA. Alternatively, access to stored, frozen and processed RNA samples for patients would also be useful. | European Commission Horizon 2020 grant | Approved | 07/10/2020 | 05/11/2020 | |||||||||||||||||
103 | Birmingham University | Nahida Choudhury | Conduct a cost of illness study | Copy of uk patient data used in https://media.tghn.org/medialibrary/2020/09/ISARIC_Data_Platform_COVID-19_Report_20AUG20.pdf | No funding required | Approved | 08/10/2020 | 11/12/2020 | |||||||||||||||||
104 | Institute of Infection and Global Health, UoL | Benedict D. Michael | Analysis of serum brain injury biomarkers (GFAP, UCHL-1, NfL, and Tau) using Quanterix Neurology 4-Plex-B plate relative to the same analysis in 50-100 patients we have already recruited into the NIHR COVID-19 BioResource with well characterised acute CNS complications of COVID-19. | We request 200uL of serum from day 1, 3, or 9 from 500 patients with severe COVID-19 (WHO ordinal scale 5-7) and 500 patients with more mild disease (WHO ordinal scale 2-3). We would intend to preferentially select those with a normal/near normal Glasgow coma score (i.e. 15/15) and compare this to those with an abnormal GCS (i.e.<15/15). | £2.3M UKRI grant to study the CNS impact of COVID-19 | Approved | 14/10/2020 | 05/11/2020 | |||||||||||||||||
105 | University of Liverpool | Stephanie Harrison | To improve understanding of factors which increase risk of stroke in adults (aged ≥18 years) with COVID-19 | 1. Anonymised data of participants (Tier Zero) including demographics, onset and admission details, vital signs at hospital admission, admission signs and symptoms, prior co-morbidities, if patient is a member of a clinically extremely vulnerable group, pre-admission medications, clinical frailty score, current medications on admission, daily treatment, daily laboratory results, pathogen testing, medications/treatment while hospitalised or on discharge, complications during hospitalisation, outcomes with dates. 2. If available, we request access to data from routine blood analysis. 3. Linked NHS COVID-19 Data Store data, including Secondary Use Services (SUS) data plus emergency care, inpatient and outpatient datasets. | Not answered | Approved | 15/10/2020 | 11/12/2020 | |||||||||||||||||
106 | University of Bradford | Muhammad Faisal | Computer-aided risk scoring systems for predicting COVID-19, sepsis, and mortality using ISARIC-4C data. | Clinical data that has been used to develop 4C risk equation. | Internal funding | Approved | 15/10/2020 | 11/12/2020 | |||||||||||||||||
107 | Gender & COVID19 | Clare Wenham & Karen Grepin | Sex-disaggregated analysis of hospital admission data to understand how this has changed over time and how NPI policies, and the increased/decreased restrictions of different sectors may have resulted in different demographic patterns of hospitalisation | Hospitalisation data - age and sex disaggregated. • Demographic Data (all collected p/1 CRF) • Onset and Admission data • Co-morbidities (for example, gendered differences such as smoking) • Interim/Final outcome data (p/5 CRF) | CIHR and Bill & Melinda Gates Foundation | Approved | 02/11/2020 | 18/12/2020 | |||||||||||||||||
108 | University Hospital of Wales | Matthew Morgan | Quality improvement project on whether we are treating patients with COVID19 correctly with steroids. | For patients only in Wales: • 1st July - present • Hospital in-patients with confirmed COVID19 • Reported per site in Wales • Use of steroid by type / time started after admission • According to ICU or non-ICU location • According to invasive ventilation / non-invasive / HFNO / normal oxygen | People already in place through the Wales Critical Care Network | Approved | 09/11/2020 | 01/07/2021 | |||||||||||||||||
109 | University College London | Sofia Morfopoulou | Metagenomics analysis to detect presence of pathogens and/or signatures of increased microbial load in the blood, that could in part explain outcome/longer-term symptoms. A more specific hypothesis is that herpesviral reactivation in the blood is more frequent in the moderately/ severely affected patients vs the mild cases and possibly plays a role in longer term symptoms, such as fatigue. | RNA-seq data from blood samples from Covid-19 patients and associated metadata (age, sex, presence of comorbities, outcome severity, day of diagnosis, day of sampling, and if follow-up is availble, presence of long-term symptoms | N/A | Approved | 10/11/2020 | 01/07/2021 | |||||||||||||||||
110 | AB 2 Bio | Laurence Goffin | Role of IL-18 to develop anti-IL-18 treatment | 2 x 0.5 mL of serum from COVID-19 patients in ICU. Data would be appropriate if available. | Commercially funded | Data access | 17/11/2020 | 06/07/2021 | |||||||||||||||||
111 | Liverpool Centre for Cardiovascular Sciences | José Miguel Rivera-Caravaca, Prof. Gregory Lip | to explore if COVID-19 patients on DOACs (at admission and/or during hospitalization) did not have a significant difference in clinical outcomes compared to patients switched to heparin. Second, we aimed to investigate if DOAC-treated patients in the context of SARS-CoV-2 infection had higher or lower risk of clinically significant outcomes compared to VKA-treated patients | to information regarding comorbidities, medications (before hospitalization and during hospitalization for COVID-19, when appropriate), procedures, and lab test results of UK patients with confirmed COVID-19 infection | funding by BMS/Pfizer alliance | Approved | 24/11/2020 | 06/07/2021 | |||||||||||||||||
112 | Kent University | Adrian Wesek | The efficacy and safety of the Leflunomide drug as moderate to severe SARS-COV-2 treatment | Data from admissions to hospital with covid-19, and patients in hospital subsequently diagnosed with covid-19. The data contained in CRFs collected at clinical trials | lifeArc | Approved | 27/11/2020 | 06/07/2021 | |||||||||||||||||
113 | PrecisionLife | Sayoni Das | Analysis of large scale, complex multi-omic and clinical data to generate combinatorial disease associations | Genetic, phenotypic and clinical data | Internally funded. Commercial | Approved | 08/12/2020 | 06/07/2021 | |||||||||||||||||
114 | Basque Center for Applied Mathematics | Ruben Armananzas | Prognostic tool for risk of death at POC by using penalised learning techniques. Cross-validate the tool with ISARIC data and local data | Anonymised clinical and laboratory parameters - demographic variables will be helpful | Active AXA Research Fund | Approved | 12/12/2020 | 29/07/2021 | |||||||||||||||||
115 | University of Alberta | Carlos Contreras | Risk -calculation for Covid-19 patients - mathematical models for the physiological response of different organs to Covid and drugs | Clinical data containing viral load, co-morbidities, and measurements for different organs for each patient | Internally funded | Approved | 19/12/2020 | 06/07/2021 | |||||||||||||||||
116 | COVID-19 MS Coalition | Claire Eyers | Use proteomics and metabolomics analyses of serum to identify markers of infection severity and potential factors influencing Long Covid. Supported by CS | Serum - longitudinal sampling stratified according non-critical care survivors and critical care. Capacity to do 1000 samples, so 300 patients assuming 3 timepoints | UKRI funded | Approved | 05/01/2021 | 01/07/2021 | |||||||||||||||||
117 | Imperial College London | Julia Ive | Stratification of patients using Natural Language Processing algorithms based on symptoms and clinical features recorded to predict best treatment pathway | Clinical data, demographic data - laboratory results, image data and patient outcomes. | Internally funded | Approved | 15/01/2021 | 08/02/2022 | |||||||||||||||||
118 | University of California | Kanika Mahajan, Xifeng Yan, Richard Beswick | Deep learning to identify features that will help in predicting patients needing more aggressive treatment and hospital stays versus those that can safely recover at home | Patient clinical data in CRF - including demographics, vital signs, medical history, signs and symptoms, medications, clinical frailty score, treatments received, outcomes | NSF Funds: Interventional COVID-19 Response Forecasting in Local Communities Using Neural Domain Adaptation Models | Approved | 11/02/2021 | 08/02/2022 | |||||||||||||||||
119 | University of Granada | Ignacio Rojas | Personalised response based on biomarkers | RNAseq from lung or upper respiratory tract tissues from COVID patients. Also requesting data behind GenOMICC Nature paper | Internal funding | Approved but requires follow-up | 16/02/2021 | 08/02/2022 | |||||||||||||||||
120 | Hong Kong Baptist University | Yang Xian | Apply computational methods to find subgroups of patients | Clnical data incl patient demographics, symptoms, comorbidities, diagnosis results, treatment methods (including medication), and related information about intensive Care and High Dependency Unit Treatments. | Internal funding | Approved | 04/03/2021 | 08/02/2022 | |||||||||||||||||
121 | Leeds University Hospitals Trust | Jane Freeman, Mark Wilcox | Potential transmission of viable virus from faeces | Longitudinal faecal samples from 10 COVID positive and 10 COVID negative participants (Days 1,3, 9 and 28). Volume needed = 2mL. Accompanying clinical data for all patients/samples. | Jon Moulton Foundation, DHSC and Enterobiotix | Approved | 12/03/2021 | ||||||||||||||||||
122 | Nottingham University Hospital | Tom Brown | Using the stroke / other neurological complications field from ISARIC would help us to improve our screening process for a study investigating the neurological effects of covid infection | Data from the ISARIC CRF form “stroke –yes/no” and “other neurological complications – yes/no” specifically for participants from Nottingham University Hospitals for screening purposes | The Covid-19 arm of COGNID is already fully funded by the MRC | Approved | 18/03/2021 | 08/02/2022 | |||||||||||||||||
123 | Wye Valley Trust | Mohamed Osman, Ingrid du Rand | Externally validate and evaluation the ISARIC proposed 4C Calculators with trust data | Clinical Data, restricted to the data required to compute the mortality and deterioration rates as predicted by the ISARIC 4C Mortality and Deterioration calculators. This would be Tier 0 Data and would only be data collected in Wye Valley NHS Trust since the pandemic until 1rst of March | No funding required | Approved | 18/03/2021 | 08/02/2022 | |||||||||||||||||
124 | University of Liverpool,RCPCH, NHSE/I, PICANet and the NCMD | Rachel Harwood | Meta-analysis on impact of variables listed(data request form) on the outcome after SARS-CoV-2 infection to guide advice about shielding and to inform vaccination roll-out in children | Data on children <18 years old who are SARS-CoV-2 PCR positive or who have been diagnosed clinically with MIS-C. I will require age (months), gender, ethnicity, co-morbidities, requirement for admission to critical care, requirement for invasive ventilation, administration of pharmacological therapy, requirement for inotropes, length of stay on critical care and survival/death | Internal funding | Approved | 06/04/2021 | 08/02/2022 | |||||||||||||||||
125 | College of Medicine, Doha, Qatar | Tawanda Chivese | Meta-analysis to establish whether HIV increases vulnerability to severe COVID-19 | Data on age group (>40, 40-60, >60 yrs) specific number of participants with (and the totals): mortality, hospitalization, ICU, mechanical ventilation and intubation for people with HIV and those without HIV | Internal funding | Approved | 12/04/2021 | 08/02/2022 | |||||||||||||||||
126 | McLean Hospital, Harvard | Carl Lin | Epistasis analysis for comorbidity diseases, substance use disorders (SUDs) | GWAS data at individual level | Internal funding | Approved | 24/04/2021 | 27/01/2022 |