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 80 of 314Insel Gruppe AG, University Hospital Bern
Background and Project Rationale: Degenerative aortic valve stenosis affects 2% of the elderly population aged 70 years or older and progresses insidiously with advancing age [1] before manifesting with symptoms such as decreased exercise tolerance, shortness of breath, chest pain and syncope on exertion. Without aortic valve replacement, the survival prognosis of patients with symptomatic aortic stenosis is poor. In the PARTNER 1B trial, all-cause mortality among 179 inoperable patients with severe symptomatic aortic stenosis allocated to conservative management amounted to 51% at one year [2]. Consistently, prospective registry data reported a mortality rate of 55% at 1 year in 78 patients with severe aortic stenosis undergoing conservative management [3]. The rapid spread of the SARS-CoV-2 pandemic represents an unprecedented challenge for healthcare systems. A limited number of ventilators and ICU beds call for a careful allocation of healthcare resources. On March 20 2020, the Federal Council prohibited elective interventions in all hospitals in Switzerland. Patients with untreated severe aortic stenosis are particularly vulnerable to SARS-CoV-2 infection [4] and face the dual risk of cardiac death from aortic stenosis on one side, and death from acute respiratory distress syndrome secondary to SARS-CoV-2 infection on the other. While the balance between the two risks is a matter of clinical judgement, the investigators established an algorithm for the management of patients with severe aortic stenosis during the SARS-CoV-2 pandemic. Patients with aortic stenosis deemed critical will undergo valvular replacement in spite of the ongoing pandemic while patients with severe but not critical aortic stenosis will undergo deferred intervention once the number of new SARS-CoV-2 infections flattens. In the current situation, aortic valve replacement in patients with severe, non-critical aortic stenosis will be deferred in order to give priority to SARS-CoV-2 patients. This unique situation allows the investigators to study the effect of deferral of aortic valve replacement in patients with severe aortic stenosis. The study is an amendment to the Swiss-TAVI registry. In contrast to the Swiss-TAVI registry, patients are not enrolled at the time of aortic valve replacement, but already at the time of referral for aortic valve replacement. Primary Objective: The aim of the present observational study is to explore the effect of deferral of valvular replacement in patients with severe but not critical aortic stenosis on morbidity and mortality. The primary objective is to describe rates of morbidity and mortality among patients with severe but not critical aortic stenosis in the interval from referral/indication for valvular replacement to intervention. Project Design: The study is a prospective cohort study of patients with severe aortic stenosis referred for aortic valve replacement. All referrals for aortic valve replacement will be allocated to either "transcatheter aortic valve replacement (TAVR)/ surgical aortic valve replacement (SAVR) (standard of care)" or "deferred intervention" based on prespecified criteria. Patients with critical aortic stenosis as defined by an aortic valve area (AVA) 60 mmHg or a history of cardiac decompensation during the previous 3 months or clinical symptoms on minimal exertion (NYHA III) will be allocated to TAVR or SAVR. All other patients with severe aortic stenosis defined by an AVA
Weprom
A coronavirus pandemic began on 12/31/2020 with the first Chinese patient. As of 3/16/2020, the epidemic affects more than 100 countries with 169,000 official infections and 6,500 deaths. This virus causes a pathology ranging from simple flu symptoms in 80% of cases to acute respiratory distress syndromes requiring resuscitation in 5% of cases and a death rate of 1.4 to 4% of cases. The arrival in France on 02/25/2020 with an exponential development of the infection (more than 5,000 cases on 03/15/2020) was accompanied by an unprecedented number of calls to the French emergency service call number (15) of worried patients with overload and sometimes saturation of the service that can impact calls and the care of patients really recovering from an emergency. We previously developed a Moovcare® web application which showed a 7 months survival benefit by early detection of relapsed lung cancer based on the reporting of patient symptoms analyzed by a validated algorithm in 300 patients and 1 trial randomized. Another application for detecting and monitoring chemo-induced febrile aplasia appears to show a reduction in the number of hospitalizations for sepsis. Finally, Smokecheck, a self-assessment application for symptoms by smokers, has shown that it improves the detection of symptomatic operable bronchial cancers (9 to 24%, p = 0.04). The web application https://www.maladiecoronavirus.fr/ was developed with a group of physicians from the Institut Pasteur, Hospitals group of Paris, Hospitals of Lille and Rennes and the ILC Jean Bernard in Le Mans. It makes it possible to guide symptomatic patients and patients who wishing to know what to do (call their general practitioner, teleconsultation, or call emergency service) based on symptoms and predictive factors of severity. Following the availability of this new tool, we want to assess the impact of the application on the number and relevance of calls to emergency service.
Mayo Clinic
The purpose of the study is to develop a clinical test based on breath analysis that can be used for disease diagnosis or prognosis.
University of Colorado, Denver
The current COVID-19 pandemic is providing healthcare organizations with considerable challenges and opportunities for rapid cycle improvement efforts, in diagnostic and patient management arenas. Healthcare providers are tasked with limiting the use of personal protective equipment while minimizing unnecessary exposures to the virus. Results from real-time PCR tests to detect active COVID-19 infections may not be available in a timely fashion during emergent trauma assessments. Since the start of the COVID-19 pandemic, a rapidly expanding body of literature has identified a pattern of imaged lung abnormalities with CT and ultrasound (US) characteristic of an active viral infection. US evaluation provides a reliable, portable, and reproducible way of evaluating acute patients in a real time setting. During initial trauma evaluations, patients may also receive adjunct imaging modalities like the Focused Assessment with Sonography in Trauma (FAST) exam designed to discover life threatening findings that may require urgent interventions. We therefore propose a study expanding on the current FAST adjunct evaluation in the trauma bay that may include lung parenchyma imaging at the initial assessment to help stratify patients into low or high-risk groups for active COVID-19 infections. We believe the use of point of care US in the initial assessment of the trauma patient may help identify potentially infected individuals and aid ED providers to best directing subsequent laboratory and imaging evaluations for these patients, while further directing the necessary protective measures for additional team members involved in the care of the injured patient.
University of Brasilia
The use of nanomaterials in semi-facial respirators could decrease the permeability of particles and promote a biocidal effect compared to conventional respirators (N95) and, therefore, to enhance the filtering power, aiming to mitigate harmful effects of bacteria and viruses. Chitosan is a natural cationic polymer derived from chitin, with characteristics such as being biodegradable, biocompatible, non-toxic, and presenting antimicrobial activity. This polymer has virucidal activity in several types of viruses, including other coronaviruses, given the attractive factor of its cationic charge for negative charges. The effectiveness of a novel individual protection semi-facial respirator (called VESTA) will be investigated, compared to a conventional N95 respirator. The respirators will be tested in healthcare professionals working in hospital environments and the effectiveness will be attributed to the lower incidence rate of infection by the SARS-CoV-2, and to the ability to filter these viruses after use by healthcare professionals exposed to potentially contaminated environments. The study will be carried out in two stages: i) Randomized Controlled Trial with reduced sample to confirm the sample size calculation (pilot trial), and ii) Randomized Controlled Trial (RCT). The RCT will be conducted with healthcare professionals who have contact with environments/patients infected by SARS-CoV-2 in hospital sectors with greater vulnerability to infection (urgency, emergency and intensive care units). The RCT will be conducted initially with a group of sixty participants (n = 30 in each group) for initial investigation of the potential for efficacy with the use of the respirators (VESTA and conventional N95) in two sectors (emergency and ICU) in a reference Hospital for COVID-19. The RCT will consist of two parallel groups: (1) Experimental Group (GExp) that will use the novel respirator (VESTA) and (2) Control Group (CG) that will use the standard respirator (N95). Participants will be recruited from participating hospitals and will be accompanied by 21 days in approximately eight consecutive shifts (ranging from shifts lasting 6 to 12 hours each, followed by approximately 36 hours of rest). Participants will be assessed at baseline (T0), at the end of the 10th day (T1), and at the end of the 21st day (T2).
University Hospital, Basel, Switzerland
The study is to investigate the antibody response in the blood and saliva of people with a known COVID-19 infection in the canton of Baselland.
Ministerio de Salud de Ciudad Autónoma de Buenos Aires
The pandemic of a new coronavirus SARS-COV-2, which causes COVID-19 disease, has spread rapidly and is a major public health challenge. While the focus is primarily on containing the number of cases and finding alternative therapies, information is still lacking to elucidate the dynamics of viral circulation and to understand the distribution of the infection in the population. The cases reported in Argentina and worldwide could plausibly represent only a small proportion of the number of asymptomatic or poorly symptomatic cases that exist in society. However, the magnitude of this dissociation between symptomatic cases and asymptomatic persons is unknown. Knowing this information is of strategic importance as it will allow the estimation of a community prevalence and the evaluation of the best containment strategy. In fact, although all social distancing measures are now indispensable, the feasibility of prolonging the measure over time is a complex issue and in any case will require population-based information. The best way to approach the estimation of a true population prevalence is to take representative samples from the population and test them periodically. These experiences were carried out in other contexts showing heterogeneous results within the community studied. In Spain, for example, the range of antibodies present in the population varied from 1.1% to 14.2%, also showing that an important part of the population had had contact with the virus without symptoms. Studies in Switzerland and the United States also show similar findings. However, these estimates are not automatically transferable to other settings. The city of Buenos Aires has a particular demographic composition with an important group of the population living in shantytowns (it is estimated that between 7% and 10% of the population lives in shantytowns) and with much heterogeneity among the different communes of the city. In the villas, the incidence rates of COVID-19 infection differ significantly from those present in the group "outside the village". However, there is also an important difference in the incidence rates by commune, even without considering the villas. Thus, it is important to know the sero-epidemiology of antibodies against SARS-COV2 in a representative sample of the city of Buenos Aires. For this purpose, a nationally produced test (COVIDAR IgG) developed by professionals from CONICET and Instituto Leloir will be used. The aim of this initiative is to estimate the true dimension of the COVID-19 epidemic in the City of Buenos Aires, by studying the immunological status of the Buenos Aires population in relation to SARS-Cov2, as well as to observe the evolution of the infection among the population, since this information is essential to guide future public health measures related to the control of COVID-19. To achieve this objective, a comprehensive sero-epidemiological study will be carried out to provide estimates of past SARS-Cov2 infection with sufficient precision to be representative of the sero-epidemiological status of the Buenos Aires city population.
Presidency of Health Institute Turkey (TUSEB)
COVID-19 is an infectious disease caused by a newly discovered Coronavirus which was first identified in Wuhan, China in December 2019. Then the novel coronavirus outbreak was described and announced as a pandemic by World Health Organization (WHO) on March 11, 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard test for diagnosis of COVID-19. Nevertheless, due to its high false-negative rates (%10-50), diagnosis and treatment decisions do not depend on RT-PCR alone. Clinical presentation of patient and radiological findings are also important. However, neither clinical presentation nor computed tomography (CT) findings are specific for COVID-19. As a consequence of these challenges, the diagnosis of the disease and the protection of the community health become more difficult. The investigators of this study hypothesized that deep learning-based decision support system may help for definitive diagnosis of COVID-19. The aim is to develop a deep learning-based decision support system algorithm based on clinical presentation of patient, laboratory and CT findings and RT-PCR data. Previously, deep learning algorithms with the use of widely known deep neural network architectures such as Inception, UNet, ResNet were developed. However all of these studies were based on CT findings. There are not any deep learning study in literature combining the clinical, radiological, and laboratory findings of patients. The project is based on the available data of COVID-19 patients that will be obtained from the Ministry of Health. Then the data will be evaluated for relevance and reliability and labeled for the training of machine. Following the anonymization of data, data will be processed according to the predetermined inclusion-exclusion criteria. Thorax CT data will be labeled as typical / indeterminate / atypical / negative for COVID-19 pneumonia. Also, CT images of patients with known non-COVID-19 diseases will be labeled for the training of machine. Then, fever, lymphocyte count, neutrophil to lymphocyte ratio, contact information, RT-PCR findings will be labeled. Subsequently, the patients will be labeled and the machine will be trained with deep learning method with the help of this grouped and labeled data. Following the training phase, the algorithm will be tested and if the machine reaches the target specificity and sensitivity, the prototype will be tested. And then, the prototype will be embedded into the hospital software system. This software and algorithm will serve as an early warning system for clinicians and provide a better diagnostic rate especially with decreasing false-negative results. The effects of a pandemic cannot be measured by only the number of people diagnosed and isolated, or treatment provided. A pandemic affects not only community health but also individuals' psychological status, education, teaching methods, working models, daily lifestyles, producer/consumer behaviors, supply/demand balance; in other words every single area of life. On top of that, a pandemic causes long-term damages hard to reverse. The software will increase the diagnostic success rates, help to control the pandemic and minimize the collateral damages mentioned above. The investigators believe that, the product that will be produced at the end of this project will be of great benefit in controlling the secondary wave of COVID-19 expected to occur.
Hopital Foch
The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is complicated by pneumonia (15 to 20% of cases) requiring hospitalization with oxygen therapy. Almost 20 to 25% of hospitalized patients require intensive care and resuscitation; half die. The main cause of death is acute respiratory distress syndrome (ARDS). However, some deaths have been linked to pulmonary embolism (PE). Recognition of PE is important because there is specific treatment to limit its own mortality. The identification of biological parameters of hemostasis predictive of thromboembolic disease is crucial in these patients. To evaluate the frequency of PE in the patients having to be hospitalized is to practice of a systematic thoracic angiography scanner in the patients having no contra-indication for its realization, as well as during hospitalization in patients deteriorating without any other obvious cause. The thromboembolic events and disturbances of the coagulation system described in patients with SARS-CoV-2 pneumonitis suggest that this viral infection is associated with an increase in the activation of coagulation contributing to the occurrence of thrombosis and especially from PE.
Assiut University
Novel coronavirus disease 19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this pneumonia was first emerged in December 2019 in Wuhan, China and rapidly spread around the world . Coagulopathy is one of the most significant prognostic factors in patients with COVID-19 and is associated with increased mortality and admission to critical care. Most observed coagulopathy in patients hospitalized with COVID-19 (COVID-19-associated coagulopathy) is characterized by increased D-dimer and fibrinogen levels. 71% of patients who did not survive hospitalization reported to have developed disseminated intravascular coagulation