Around the world, researchers are working extremely hard to develop new treatments and interventions for COVID-19 with new clinical trials opening nearly every day. This directory provides you with information, including enrollment detail, about these trials. In some cases, researchers are able to offer expanded access (sometimes called compassionate use) to an investigational drug when a patient cannot participate in a clinical trial.
The information provided here is drawn from ClinicalTrials.gov. If you do not find a satisfactory expanded access program here, please search in our COVID Company Directory. Some companies consider expanded access requests for single patients, even if they do not show an active expanded access listing in this database. Please contact the company directly to explore the possibility of expanded access.
Emergency INDs
To learn how to apply for expanded access, please visit our Guides designed to walk healthcare providers, patients and/or caregivers through the process of applying for expanded access. Please note that given the situation with COVID-19 and the need to move as fast as possible, many physicians are requesting expanded access for emergency use. In these cases, FDA will authorize treatment by telephone and treatment can start immediately. For more details, consult FDA guidance. Emergency IND is the common route that patients are receiving convalescent plasma.
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Displaying 280 of 289Imperial College London
Coronavirus Disease 2019 (COVID-19) has been widespread worldwide since December 2019. It is highly contagious, and severe cases can lead to acute respiratory distress or multiple organ failure. On 11 March 2020, the WHO made the assessment that COVID-19 can be characterised as a pandemic. With the development of machine learning, deep learning based artificial intelligence (AI) technology has demonstrated tremendous success in the field of medical data analysis due to its capacity of extracting rich features from imaging and complex clinical datasets. In this study, we aim to use clinical data collected as part of routine clinical care (heart tracings, X-rays and CT scans) to train artificial intelligence and machine learning algorithms, to accurately predict the course of disease in patients with Covid-19 infection, using these datasets.
Amazon Web Services (AWS) Canada
The VOICE-COVID study will evaluate the concordance of screening for symptoms of COVID-19 using a voice based device (Amazon Alexa) compared to manual screening by a study coordinator for individuals entering the Cardiology/Heart Failure clinic at the McGill University Health Centre.
University of California, Irvine
The investigators are enrolling 100 healthcare Provider volunteers (n=100) from across the United States to help to evaluate and document the financial impact of COVID-19 on Physicians and other healthcare Providers. This investigation will compare individual Physician revenues before and after the advent of the COVID-19 pandemic. The investigators expect to be able to differentiate between revenues lost due to the COVID-19-driven business recession and revenues lost due to the manipulation of reimbursement processes by insurance companies. The inextricable linkage between Payer and Physician revenues suggests that Payer revenues are higher at the direct expense of Physicians, since both streams come from the same sources of funding. The secondary objective is aimed at revealing the methods Payers use to retain more money.
Fondazione Don Carlo Gnocchi Onlus
The outbreak of coronavirus disease 2019 (COVID-19), caused by infection of SARS-CoV-2, has rapidly spread to become a worldwide pandemic. Global research focused on the understanding of the biochemical infective mechanism and on the discovery of a fast, sensitive and cheap diagnostic tool, able to discriminate the current and past SARS-CoV-2 infections from a minimal invasive biofluid. The fast diagnosis of COVID-19 is fundamental in order to limit and isolate the positive cases, decreasing with a prompt intervention the infection spreading. The aim of the project is to characterize and validate the salivary Raman fingerprint of COVID-19, understanding the principal biomolecules involved in the differences between the three experimental groups: 1) healthy subjects, 2) COVID-19 patients and 3) subjects with a past infection by COVID-19. The large amount of Raman data will be used to create a salivary Raman database, associating each data with the relative clinical data collected. Starting from the preliminary results and protocols of the Laboratory of Nanomedicine and Clinical Biophotonics (LABION) - IRCCS Fondazione Don Gnocchi Milano, the saliva collected from each experimental group will be analysed using Raman spectroscopy. All the data will be processed for the baseline, shift and normalization in order to homogenize the signals collected and creating in this way the Raman database. The average spectrum calculated from each group will be characterized, identifying the principal families of biological molecules responsible for the spectral differences. EXPECTED RESULTS: Verify the possibility to use Raman spectroscopy on saliva samples for the identification of subjects affected by COVID-19. The principal aim of the project is to create a classification model able to: discriminate COVID-19 current and past infection, identify the principal biological molecules altered in saliva during the infection, predict the clinical course of newly diagnosed COVID-19 patients, translation and application of the classification model to a portable Raman for the test of a point of care.
University Hospital Tuebingen
This is a prospective, longitudinal study to determine the incidence of SARS-COV-2 infection in children and adolescents by measuring specific antibodies in non-invasive saliva sampled in kindergartens and schools in a defined city area. The study includes an additional arm to validate the ELISA for anti-SARS-COV-2 reactive antibody measurements in saliva compared against blood collected in adult volunteers in a bimonthly follow-up period for 12 months.
Patient-Centered Outcomes Research Institute
The clinical guidance for 90 percent of infected COVID-19 adult patients who do not meet eligibility for inpatient admission is to self-isolate. To support these patients, alternatives to in-person care are needed to manage an unpredictable clinical course; identify and intercept patients rapidly deteriorating at home, prevent viral spread during in-person visits; and minimize future surges in emergency departments (EDs). In addition, fingertip pulse oximeters have been proposed to improve in-home early detection of respiratory deteriorations but are untested and the operational infrastructure to support large-scale monitoring is limited. While telemedicine has been widely adopted during the pandemic as an alternative to conventional outpatient care, limited telemedicine access may be exacerbating observed disparities for Black and Latino patients. In our health system, Black and Latino patients used video-visits 15 percent less often than white patients. Text messaging and phone calls may improve healthcare access for communities of color, but the evidence for these telecommunication modalities to be effective and improve equity are limited. The University of Pennsylvania Health System (UPHS) developed and deployed COVID Watch to improve access to health care for COVID-19 patients who are self-isolating at home. COVID Watch sends twice-daily, scheduled text messages to assess patients for shortness of breath using a clinical algorithm to determine whether patients need an urgent escalation to a team of dedicated, on-call nurses within one hour. These nurses are supported by an on-call team of clinicians who can conduct urgent phone or video assessments. Patients can also trigger the algorithmic assessment independent of the scheduled messages. As of May 21, 2020, COVID Watch has managed 3,628 COVID-19 patients at home, of which 1,295 are confirmed COVID-19 positive; of these, 61 percent are Black or Latino, higher than the proportion of all UPHS COVID-19 positive patients that are Black or Latino (55 percent).
Imperial College London
The Multi-arm trial of Inflammatory Signal Inhibitors for COVID-19 (MATIS) study is a two-stage, open-label, randomised controlled trial assessing the efficacy of ruxolitinib (RUX) and fostamatinib (FOS) individually, compared to standard of care in the treatment of COVID-19 pneumonia. The primary outcome is the proportion of hospitalised patients progressing from mild or moderate to severe COVID-19 pneumonia. Patients are treated for 14 days and will receive follow-up assessment at 7, 14 and 28 days after the first study dose. Patients with mild or moderate COVID-19 pneumonia will be recruited. Initially, n=171 (57 per arm) patients will be recruited in Stage 1. Following interim analysis to assess the efficacy and safety of the treatments, approximately n=285 (95 per arm) will be recruited during Stage 2.
Tourcoing Hospital
The non-essential and non-urgent follow-up consultations of patients living with HIV were postponed or transformed into "teleconsultation" or exchanges of e-mails between practitioners and patients during COVID-19 epidemic. This change in care can have an impact on follow-up and access to treatment for PVVIH.
Hill-Rom
A Pilot Study of the Use of Oscillation and Lung Expansion (OLE) Therapy in Patients Hospitalized with COVID-19
Assiut University
To compare myocardial injury in COVID 19 patients presented with myocardial infarction and non COVID Patients presented with myocardial infarction evaluated with CMR