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Holubovska O, Babich P, Mironenko A, Milde J, Lebed Y, Stammer H, Mueller L, te Velthuis AJW, Margitich V, Goy A. RNA Polymerase Inhibitor Enisamium for Treatment of Moderate COVID-19 Patients: A Randomized, Placebo-Controlled, Multicenter, Double-Blind Phase 3 Clinical Trial. Adv Respir Med 2024; 92:202-217. [PMID: 38804439 PMCID: PMC11130936 DOI: 10.3390/arm92030021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/14/2024] [Accepted: 04/24/2024] [Indexed: 05/29/2024]
Abstract
Enisamium is an orally available therapeutic that inhibits influenza A virus and SARS-CoV-2 replication. We evaluated the clinical efficacy of enisamium treatment combined with standard care in adult, hospitalized patients with moderate COVID-19 requiring external oxygen. Hospitalized patients with laboratory-confirmed SARS-CoV-2 infection were randomly assigned to receive either enisamium (500 mg per dose, four times a day) or a placebo. The primary outcome was an improvement of at least two points on an eight-point severity rating (SR) scale within 29 days of randomization. We initially set out to study the effect of enisamium on patients with a baseline SR of 4 or 5. However, because the study was started early in the COVID-19 pandemic, and COVID-19 had been insufficiently studied at the start of our study, an interim analysis was performed alongside a conditional power analysis in order to ensure patient safety and assess whether the treatment was likely to be beneficial for one or both groups. Following this analysis, a beneficial effect was observed for patients with an SR of 4 only, i.e., patients with moderate COVID-19 requiring supplementary oxygen. The study was continued for these COVID-19 patients. Overall, a total of 592 patients were enrolled and randomized between May 2020 and March 2021. Patients with a baseline SR of 4 were divided into two groups: 142 (49.8%) were assigned to the enisamium group and 143 (50.2%) to the placebo group. An analysis of the population showed that if patients were treated within 4 days of the onset of COVID-19 symptoms (n = 33), the median time to improvement was 8 days for the enisamium group and 13 days for the placebo group (p = 0.005). For patients treated within 10 days of the onset of COVID-19 symptoms (n = 154), the median time to improvement was 10 days for the enisamium group and 12 days for the placebo group (p = 0.002). Our findings suggest that enisamium is safe to use with COVID-19 patients, and that the observed clinical benefit of enisamium is worth reporting and studying in detail.
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Affiliation(s)
- Olga Holubovska
- Department of Infectious Diseases, O.O. Bogomolets National Medical University, T. Shevchenko Blvd. 13, 01601 Kyiv, Ukraine;
| | - Pavlo Babich
- State Expert Center, Smolenska Str. 10, 03057 Kyiv, Ukraine;
| | - Alla Mironenko
- Department of Respiratory and Other Viral Infections, L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of the NAMS of Ukraine, Amosova Str. 5a, 03083 Kyiv, Ukraine;
| | - Jens Milde
- Pharmalog Institut für Klinische Forschung GmbH, Oskar-Messter-Str. 29, 85737 Ismaning, Germany; (J.M.); (H.S.)
| | - Yuriy Lebed
- Pharmaxi LLC, Filatova Str. 10A, 01042 Kyiv, Ukraine;
| | - Holger Stammer
- Pharmalog Institut für Klinische Forschung GmbH, Oskar-Messter-Str. 29, 85737 Ismaning, Germany; (J.M.); (H.S.)
| | - Lutz Mueller
- Regenold GmbH, Zöllinplatz 4, 79410 Badenweiler, Germany;
| | - Aartjan J. W. te Velthuis
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
- Division of Virology, Department of Pathology, University of Cambridge Addenbrooke’s Hospital, Cambridge CB2 2QQ, UK
| | - Victor Margitich
- Farmak Joint Stock Company, Kyrylivska Str., 04080 Kyiv, Ukraine
| | - Andrew Goy
- Farmak Joint Stock Company, Kyrylivska Str., 04080 Kyiv, Ukraine
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Ambrosino P, Moretta P, Lanzillo A, Formisano R, Maniscalco M. Implementing Translational Research to Understand the Future of COVID-19 and Its Long-Term Consequences: A Degrowth Perspective or the Transformation of a Global Emergency? Biomedicines 2023; 11:117. [PMID: 36672625 PMCID: PMC9855765 DOI: 10.3390/biomedicines11010117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 12/27/2022] [Indexed: 01/05/2023] Open
Abstract
It has now been three years since the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first gave rise to a global health crisis [...].
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Affiliation(s)
- Pasquale Ambrosino
- Istituti Clinici Scientifici Maugeri IRCCS, Directorate of Telese Terme Institute, 82037 Telese Terme, Italy
| | - Pasquale Moretta
- Istituti Clinici Scientifici Maugeri IRCCS, Neuromotor Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy
| | - Anna Lanzillo
- Istituti Clinici Scientifici Maugeri IRCCS, Neuromotor Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy
| | - Roberto Formisano
- Istituti Clinici Scientifici Maugeri IRCCS, Cardiac Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy
| | - Mauro Maniscalco
- Istituti Clinici Scientifici Maugeri IRCCS, Pulmonary Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy
- Department of Clinical Medicine and Surgery, Federico II University, 80131 Naples, Italy
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Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022; 122:11287-11368. [PMID: 35594413 PMCID: PMC9159519 DOI: 10.1021/acs.chemrev.1c00965] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.
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Affiliation(s)
- Kaifu Gao
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Limei Cheng
- Clinical
Pharmacology and Pharmacometrics, Bristol
Myers Squibb, Princeton, New Jersey 08536, United States
| | - Jaclyn Frishcosy
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Huzumi
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuchi Qiu
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tom Schluckbier
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Xiaoqi Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan 48824, United States
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