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Ruxolitinib for COVID-19

Ruxolitinib has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Molina et al., 556. Ruxolitinib for the Management of Severe Pneumonia Caused by SARS-CoV-2. Exploring the Combination with dexamethasone, Open Forum Infectious Diseases, doi:10.1093/ofid/ofab466.754
Abstract Background Mexico is one of the top five countries with a higher mortality rate of hospitalized patients of 30.1%. Since COVID-19 has been associated with immune dysregulation and hyper inflammation, JAK-12 inhibitors have been tested to reduce IL6 production. Studies have shown improvements when using ruxolitinib (rxb) in severely hospitalized patients with COVID-19. These have included patients in combination with corticosteroids such as dexamethasone (dxm). This work aims to test the response of hospitalized patients with severe or critical COVID-19 treated with rxb with or without dxm. Methods An experimental, open, prospective study in a single third-level hospital in Mexico was performed. The primary outcome was favorable clinical response defined as withdrawal or decline of supplementary oxygen. Secondary outcomes such as mean hospital stay, improvement in systemic inflammatory response parameters, and mortality were also evaluated. Statistical differences for baseline and final measure and the use and not use of dxm were estimated. The study included adults with SARS-CoV-2 infection confirmed with polymerase chain reaction, radiological pneumonia, and oxygen saturation less than 90%. Rxb was administered 5mg/12hrs/15days, IV dxm 6mg/day/10days. Results The final sample was 108 adults with complete information and informed consent. Sixty-two patients (57%) received only rxb. There were no differences between groups for any parameter at the beginning of treatment, and all patients were receiving supplemental oxygen. After 28-day follow-up, 70% reduce supplemental oxygen requirement (74% rxb and 71% rxb+dxm; p=0.628), 18% remained, and 2% increases support (1% with rxb, and 5% rxb+dxm; p< 0.001); 87% of patients were discharged (89% rxb and 85% rxb+dxm; p=0.603). In both groups, there was a significant reduction of CRP, LDH, and Ferritin on day 15. The mortality rate was 9% (no difference in groups; p=0.453), and a higher proportion died for Pseudomonas aeruginosa superinfection in the rxb+dxm group (p< 0.001). Differences for support oxygen at baseline and discharge Final health outcomes of patients with severe or critical COVID-19 in a third-level hospital in Mexico Conclusion The use of rxb could be considered as a treatment helping clinical improvement in hospitalized patients with severe COVID-19. Combination with dxm apparently did not add clinical benefits. It should be further evaluated. Disclosures All Authors: No reported disclosures
Gordon et al., A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing, bioRxiv, doi:10.1101/2020.03.22.002386
ABSTRACTAn outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.
Gysi et al., Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19, arXiv, doi:10.48550/arXiv.2004.07229
The current pandemic has highlighted the need for methodologies that can quickly and reliably prioritize clinically approved compounds for their potential effectiveness for SARS-CoV-2 infections. In the past decade, network medicine has developed and validated multiple predictive algorithms for drug repurposing, exploiting the sub-cellular network-based relationship between a drug's targets and disease genes. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity, tasking each of them to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. To test the predictions, we used as ground truth 918 drugs that had been experimentally screened in VeroE6 cells, and the list of drugs under clinical trial, that capture the medical community's assessment of drugs with potential COVID-19 efficacy. We find that while most algorithms offer predictive power for these ground truth data, no single method offers consistently reliable outcomes across all datasets and metrics. This prompted us to develop a multimodal approach that fuses the predictions of all algorithms, showing that a consensus among the different predictive methods consistently exceeds the performance of the best individual pipelines. We find that 76 of the 77 drugs that successfully reduced viral infection do not bind the proteins targeted by SARS-CoV-2, indicating that these drugs rely on network-based actions that cannot be identified using docking-based strategies. These advances offer a methodological pathway to identify repurposable drugs for future pathogens and neglected diseases underserved by the costs and extended timeline of de novo drug development.
Schake et al., An interaction-based drug discovery screen explains known SARS-CoV-2 inhibitors and predicts new compound scaffolds, Scientific Reports, doi:10.1038/s41598-023-35671-x
AbstractThe recent outbreak of the COVID-19 pandemic caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has shown the necessity for fast and broad drug discovery methods to enable us to react quickly to novel and highly infectious diseases. A well-known SARS-CoV-2 target is the viral main 3-chymotrypsin-like cysteine protease (Mpro), known to control coronavirus replication, which is essential for the viral life cycle. Here, we applied an interaction-based drug repositioning algorithm on all protein-compound complexes available in the protein database (PDB) to identify Mpro inhibitors and potential novel compound scaffolds against SARS-CoV-2. The screen revealed a heterogeneous set of 692 potential Mpro inhibitors containing known ones such as Dasatinib, Amodiaquine, and Flavin mononucleotide, as well as so far untested chemical scaffolds. In a follow-up evaluation, we used publicly available data published almost two years after the screen to validate our results. In total, we are able to validate 17% of the top 100 predictions with publicly available data and can furthermore show that predicted compounds do cover scaffolds that are yet not associated with Mpro. Finally, we detected a potentially important binding pattern consisting of 3 hydrogen bonds with hydrogen donors of an oxyanion hole within the active side of Mpro. Overall, these results give hope that we will be better prepared for future pandemics and that drug development will become more efficient in the upcoming years.
Oliver et al., Different drug approaches to COVID-19 treatment worldwide: an update of new drugs and drugs repositioning to fight against the novel coronavirus, Therapeutic Advances in Vaccines and Immunotherapy, doi:10.1177/25151355221144845
According to the World Health Organization (WHO), in the second half of 2022, there are about 606 million confirmed cases of COVID-19 and almost 6,500,000 deaths around the world. A pandemic was declared by the WHO in March 2020 when the new coronavirus spread around the world. The short time between the first cases in Wuhan and the declaration of a pandemic initiated the search for ways to stop the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or to attempt to cure the disease COVID-19. More than ever, research groups are developing vaccines, drugs, and immunobiological compounds, and they are even trying to repurpose drugs in an increasing number of clinical trials. There are great expectations regarding the vaccine’s effectiveness for the prevention of COVID-19. However, producing sufficient doses of vaccines for the entire population and SARS-CoV-2 variants are challenges for pharmaceutical industries. On the contrary, efforts have been made to create different vaccines with different approaches so that they can be used by the entire population. Here, we summarize about 8162 clinical trials, showing a greater number of drug clinical trials in Europe and the United States and less clinical trials in low-income countries. Promising results about the use of new drugs and drug repositioning, monoclonal antibodies, convalescent plasma, and mesenchymal stem cells to control viral infection/replication or the hyper-inflammatory response to the new coronavirus bring hope to treat the disease.
Ceja-Gálvez et al., Severe COVID-19: Drugs and Clinical Trials, Journal of Clinical Medicine, doi:10.3390/jcm12082893
By January of 2023, the COVID-19 pandemic had led to a reported total of 6,700,883 deaths and 662,631,114 cases worldwide. To date, there have been no effective therapies or standardized treatment schemes for this disease; therefore, the search for effective prophylactic and therapeutic strategies is a primary goal that must be addressed. This review aims to provide an analysis of the most efficient and promising therapies and drugs for the prevention and treatment of severe COVID-19, comparing their degree of success, scope, and limitations, with the aim of providing support to health professionals in choosing the best pharmacological approach. An investigation of the most promising and effective treatments against COVID-19 that are currently available was carried out by employing search terms including “Convalescent plasma therapy in COVID-19” or “Viral polymerase inhibitors” and “COVID-19” in the Clinicaltrials.gov and PubMed databases. From the current perspective and with the information available from the various clinical trials assessing the efficacy of different therapeutic options, we conclude that it is necessary to standardize certain variables—such as the viral clearance time, biomarkers associated with severity, hospital stay, requirement of invasive mechanical ventilation, and mortality rate—in order to facilitate verification of the efficacy of such treatments and to better assess the repeatability of the most effective and promising results.
Islam et al., Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding, Scientific Reports, doi:10.1038/s41598-023-30095-z
AbstractThe search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns “ensemble embeddings” of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Vaccines and treatments are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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