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      A real-time dashboard of clinical trials for COVID-19

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          Abstract

          In response to the global coronavirus disease 2019 (COVID-19) emergency, clinical trial research assessing the efficacy and safety of clinical candidate interventions to treat COVID-19 are emerging at an unprecedented rate. As of April 21, 2020, well over 500 clinical trials have been registered at the various international and national clinical trial registry sites. Findings from randomised clinical trials that have been published as of April 21, 2020, have investigated the efficacy of lopinavir–ritonavir compared with standard of care, 1 hydroxychloroquine compared with best supportive care, 2 favipiravir compared with arbidol, 3 and lopinavir–ritonavir compared with arbidol. 4 Other non-randomised trials have investigated hydroxychloroquine versus hydroxychloroquine combined with azithromycin. 5 Over 300 trials are enrolling participants and cover further investigations of the above drugs and promising therapies such as remdesivir, IL-6 inhibitors (tocilizumab and sarilumab), convalescent plasma therapy, stem-cell transfusion, vaccine candidates, several other well known direct acting antiv irals, and traditional Chinese medicines. Most of these trials will offer comparative efficacy data versus standard of care according to local COVID-19 treatment guidelines, but a handful of randomised controlled trials will also provide head-to-head evidence between high profile interventions. The figure shows the network of completed, ongoing, and planned COVID-19 interventional clinical trials of these interventions or intervention groups that are being explored in at least two trials. Figure Evidence network of COVID-19 clinical trials of top 15 interventions Circles (node) represent interventions or intervention groups (categories). Lines between two circles indicate comparisons in clinical trials. The numbers on the lines are the number of clinical trials making the specific comparison. Circular arrows and numbers indicate the number of non-comparative clinical trials in which that intervention is included. A few trials examining combination therapies are excluded from the figure due to space limitations. COVID-19=coronavirus disease 2019. LPV/r (lopinivir–ritonavir). *Includes trials on hydroxychloroquine and chloroquine. Given the accelerated rate at which trial information and findings are emerging, an urgent need exists to track clinical trials, avoid unnecessary duplication of efforts, and understand what trials are being done and where. In response, we have developed a COVID-19 clinical trials registry to collate all trials. Data are pulled from the International Clinical Trials Registry Platform, including those from the Chinese Clinical Trial Registry, ClinicalTrials.gov, Clinical Research Information Service - Republic of Korea, EU Clinical Trials Register, ISRCTN, Iranian Registry of Clinical Trials, Japan Primary Registries Network, and German Clinical Trials Register. Both automated and manual searches are done to ensure minimisation of duplicated entries and for appropriateness to the research questions. Identified studies are then manually reviewed by two separate reviewers before being entered into the registry. Concurrently, we have developed artificial intelligence (AI)-based methods for data searches to identify potential clinical studies not captured in trial registries. These methods provide estimates of the likelihood of importance of a study being included in our database, such that the study can then be reviewed manually for inclusion. Use of AI-based methods saves 50–80% of the time required to manually review all entries without loss of accuracy. Finally, we will use content aggregator services, such as LitCovid, to ensure our data acquisition strategy is complete. With this three-step process, the probability of missing important publications is greatly diminished and so the resulting data are representative of global COVID-19 research efforts. Trials for COVID-19 are then mapped according to geographical, trial, patient, and intervention characteristics, when these data are available. These data are stored securely in a backend database and outputs are visualised on a front-end feature. As trial findings are communicated, these data must be centralised and meta-analysed in real-time. Syntheses of these trials are urgently needed to assist clinicians, researchers, and policy makers to make evidence-informed decisions to minimise the morbidity and mortality due to COVID-19.

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          Most cited references5

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          A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19

          Abstract Background No therapeutics have yet been proven effective for the treatment of severe illness caused by SARS-CoV-2. Methods We conducted a randomized, controlled, open-label trial involving hospitalized adult patients with confirmed SARS-CoV-2 infection, which causes the respiratory illness Covid-19, and an oxygen saturation (Sao 2) of 94% or less while they were breathing ambient air or a ratio of the partial pressure of oxygen (Pao 2) to the fraction of inspired oxygen (Fio 2) of less than 300 mm Hg. Patients were randomly assigned in a 1:1 ratio to receive either lopinavir–ritonavir (400 mg and 100 mg, respectively) twice a day for 14 days, in addition to standard care, or standard care alone. The primary end point was the time to clinical improvement, defined as the time from randomization to either an improvement of two points on a seven-category ordinal scale or discharge from the hospital, whichever came first. Results A total of 199 patients with laboratory-confirmed SARS-CoV-2 infection underwent randomization; 99 were assigned to the lopinavir–ritonavir group, and 100 to the standard-care group. Treatment with lopinavir–ritonavir was not associated with a difference from standard care in the time to clinical improvement (hazard ratio for clinical improvement, 1.24; 95% confidence interval [CI], 0.90 to 1.72). Mortality at 28 days was similar in the lopinavir–ritonavir group and the standard-care group (19.2% vs. 25.0%; difference, −5.8 percentage points; 95% CI, −17.3 to 5.7). The percentages of patients with detectable viral RNA at various time points were similar. In a modified intention-to-treat analysis, lopinavir–ritonavir led to a median time to clinical improvement that was shorter by 1 day than that observed with standard care (hazard ratio, 1.39; 95% CI, 1.00 to 1.91). Gastrointestinal adverse events were more common in the lopinavir–ritonavir group, but serious adverse events were more common in the standard-care group. Lopinavir–ritonavir treatment was stopped early in 13 patients (13.8%) because of adverse events. Conclusions In hospitalized adult patients with severe Covid-19, no benefit was observed with lopinavir–ritonavir treatment beyond standard care. Future trials in patients with severe illness may help to confirm or exclude the possibility of a treatment benefit. (Funded by Major Projects of National Science and Technology on New Drug Creation and Development and others; Chinese Clinical Trial Register number, ChiCTR2000029308.)
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            Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial

            Background Chloroquine and hydroxychloroquine have been found to be efficient on SARS-CoV-2, and reported to be efficient in Chinese COV-19 patients. We evaluate the role of hydroxychloroquine on respiratory viral loads. Patients and methods French Confirmed COVID-19 patients were included in a single arm protocol from early March to March 16th, to receive 600mg of hydroxychloroquine daily and their viral load in nasopharyngeal swabs was tested daily in a hospital setting. Depending on their clinical presentation, azithromycin was added to the treatment. Untreated patients from another center and cases refusing the protocol were included as negative controls. Presence and absence of virus at Day6-post inclusion was considered the end point. Results Six patients were asymptomatic, 22 had upper respiratory tract infection symptoms and eight had lower respiratory tract infection symptoms. Twenty cases were treated in this study and showed a significant reduction of the viral carriage at D6-post inclusion compared to controls, and much lower average carrying duration than reported of untreated patients in the literature. Azithromycin added to hydroxychloroquine was significantly more efficient for virus elimination. Conclusion Despite its small sample size our survey shows that hydroxychloroquine treatment is significantly associated with viral load reduction/disappearance in COVID-19 patients and its effect is reinforced by azithromycin.
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              Is Open Access

              In Vitro Antiviral Activity and Projection of Optimized Dosing Design of Hydroxychloroquine for the Treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

              Abstract Background The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) first broke out in Wuhan (China) and subsequently spread worldwide. Chloroquine has been sporadically used in treating SARS-CoV-2 infection. Hydroxychloroquine shares the same mechanism of action as chloroquine, but its more tolerable safety profile makes it the preferred drug to treat malaria and autoimmune conditions. We propose that the immunomodulatory effect of hydroxychloroquine also may be useful in controlling the cytokine storm that occurs late-phase in critically ill SARS-CoV-2 infected patients. Currently, there is no evidence to support the use of hydroxychloroquine in SARS-CoV-2 infection. Methods The pharmacological activity of chloroquine and hydroxychloroquine was tested using SARS-CoV-2 infected Vero cells. Physiologically-based pharmacokinetic models (PBPK) were implemented for both drugs separately by integrating their in vitro data. Using the PBPK models, hydroxychloroquine concentrations in lung fluid were simulated under 5 different dosing regimens to explore the most effective regimen whilst considering the drug’s safety profile. Results Hydroxychloroquine (EC50=0.72 μM) was found to be more potent than chloroquine (EC50=5.47 μM) in vitro. Based on PBPK models results, a loading dose of 400 mg twice daily of hydroxychloroquine sulfate given orally, followed by a maintenance dose of 200 mg given twice daily for 4 days is recommended for SARS-CoV-2 infection, as it reached three times the potency of chloroquine phosphate when given 500 mg twice daily 5 days in advance. Conclusions Hydroxychloroquine was found to be more potent than chloroquine to inhibit SARS-CoV-2 in vitro.
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                Author and article information

                Contributors
                Journal
                Lancet Digit Health
                Lancet Digit Health
                The Lancet. Digital Health
                The Author(s). Published by Elsevier Ltd.
                2589-7500
                24 April 2020
                24 April 2020
                Affiliations
                [a ]McMaster University, Hamilton, V5Z 1J5 ON, Canada
                [b ]University of British Columbia, Vancouver, BC, Canada
                Article
                S2589-7500(20)30086-8
                10.1016/S2589-7500(20)30086-8
                7195288
                32363333
                98a542e1-736a-4f3e-8228-d61cc36f4f99
                © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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