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Yoo S, Kim L, Lu M, Nagoshi K, Namchuk M. A review of clinical efficacy data supporting emergency use authorization for COVID-19 therapeutics and lessons for future pandemics. Clin Transl Sci 2022; 15:2279-2292. [PMID: 35929015 PMCID: PMC9538903 DOI: 10.1111/cts.13384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 07/08/2022] [Accepted: 07/21/2022] [Indexed: 01/25/2023] Open
Abstract
Emergency Use Authorization (EUA) allows the US Food and Drug Administration (FDA) to expedite the availability of therapeutics in the context of a public health emergency. To date, an evidentiary standard for clinical efficacy to support an EUA has not yet been established. This review examines the clinical data submitted in support of EUA for antiviral and anti-inflammatory therapeutics for coronavirus disease 2019 (COVID-19) through December of 2021 and the resilience of the authorization as new clinical data arose subsequent to the authorization. In the vast majority of cases, EUA was supported by at least one well-powered randomized controlled trial (RCT) where statistically significant efficacy was demonstrated. This included branded medications already approved for use outside of the context of COVID-19. When used, the standard of a single RCT seemed to provide adequate evidence of clinical efficacy, such that subsequent clinical studies generally supported or expanded the EUA of the therapeutic in question. The lone generic agent that was granted EUA (chloroquine/hydroxychloroquine) was not supported by a well-controlled RCT, and the EUA was withdrawn within 3 months time. This highlighted not only the ambiguity of the EUA standard, but also the need to provide avenues through which high quality clinical evidence for the efficacy of a generic medication could be obtained. Therefore, maintaining the clinical trial networks assembled during the COVID-19 pandemic could be a critical component of our preparation for future pandemics. Consideration could also be given to establishing a single successful RCT as regulatory guidance for obtaining an EUA.
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Affiliation(s)
| | - Lauren Kim
- Harvard CollegeCambridgeMassachusettsUSA
| | | | | | - Mark N. Namchuk
- Department of Biological Chemistry and Molecular PharmacologyBlavatnik Institute, Harvard Medical SchoolBostonMassachusettsUSA
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Peng H, Ding C, Jiang L, Tang W, Liu Y, Zhao L, Yi Z, Ren H, Li C, He Y, Zheng X, Tang H, Chen Z, Qi Z, Zhao P. Discovery of potential anti-SARS-CoV-2 drugs based on large-scale screening in vitro and effect evaluation in vivo. SCIENCE CHINA. LIFE SCIENCES 2022; 65:1181-1197. [PMID: 34962614 PMCID: PMC8713546 DOI: 10.1007/s11427-021-2031-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 11/17/2021] [Indexed: 12/22/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global crisis. Clinical candidates with high efficacy, ready availability, and that do not develop resistance are in urgent need. Despite that screening to repurpose clinically approved drugs has provided a variety of hits shown to be effective against SARS-CoV-2 infection in cell culture, there are few confirmed antiviral candidates in vivo. In this study, 94 compounds showing high antiviral activity against SARS-CoV-2 in Vero E6 cells were identified from 2,580 FDA-approved small-molecule drugs. Among them, 24 compounds with low cytotoxicity were selected, and of these, 17 compounds also effectively suppressed SARS-CoV-2 infection in HeLa cells transduced with human ACE2. Six compounds disturb multiple processes of the SARS-CoV-2 life cycle. Their prophylactic efficacies were determined in vivo using Syrian hamsters challenged with SARS-CoV-2 infection. Seven compounds reduced weight loss and promoted weight regain of hamsters infected not only with the original strain but also the D614G variant. Except for cisatracurium, six compounds reduced hamster pulmonary viral load, and IL-6 and TNF-α mRNA when assayed at 4 d postinfection. In particular, sertraline, salinomycin, and gilteritinib showed similar protective effects as remdesivir in vivo and did not induce antiviral drug resistance after 10 serial passages of SARS-CoV-2 in vitro, suggesting promising application for COVID-19 treatment.
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Affiliation(s)
- Haoran Peng
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Cuiling Ding
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Liangliang Jiang
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Wanda Tang
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Yan Liu
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Lanjuan Zhao
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Zhigang Yi
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Hao Ren
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Chong Li
- Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200000, China
| | - Yanhua He
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Xu Zheng
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Hailin Tang
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China
| | - Zhihui Chen
- Department of Infectious Disease, Changhai Hospital, Shanghai, 200433, China.
| | - Zhongtian Qi
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China.
| | - Ping Zhao
- Department of Microbiology, Second Military Medical University, Shanghai Key Laboratory of Medical Biodefense, Shanghai, 200433, China.
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MotieGhader H, Safavi E, Rezapour A, Amoodizaj FF, Iranifam RA. Drug repurposing for coronavirus (SARS-CoV-2) based on gene co-expression network analysis. Sci Rep 2021; 11:21872. [PMID: 34750486 PMCID: PMC8576023 DOI: 10.1038/s41598-021-01410-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 10/28/2021] [Indexed: 02/06/2023] Open
Abstract
Severe acute respiratory syndrome (SARS) is a highly contagious viral respiratory illness. This illness is spurred on by a coronavirus known as SARS-associated coronavirus (SARS-CoV). SARS was first detected in Asia in late February 2003. The genome of this virus is very similar to the SARS-CoV-2. Therefore, the study of SARS-CoV disease and the identification of effective drugs to treat this disease can be new clues for the treatment of SARS-Cov-2. This study aimed to discover novel potential drugs for SARS-CoV disease in order to treating SARS-Cov-2 disease based on a novel systems biology approach. To this end, gene co-expression network analysis was applied. First, the gene co-expression network was reconstructed for 1441 genes, and then two gene modules were discovered as significant modules. Next, a list of miRNAs and transcription factors that target gene co-expression modules' genes were gathered from the valid databases, and two sub-networks formed of transcription factors and miRNAs were established. Afterward, the list of the drugs targeting obtained sub-networks' genes was retrieved from the DGIDb database, and two drug-gene and drug-TF interaction networks were reconstructed. Finally, after conducting different network analyses, we proposed five drugs, including FLUOROURACIL, CISPLATIN, SIROLIMUS, CYCLOPHOSPHAMIDE, and METHYLDOPA, as candidate drugs for SARS-CoV-2 coronavirus treatment. Moreover, ten miRNAs including miR-193b, miR-192, miR-215, miR-34a, miR-16, miR-16, miR-92a, miR-30a, miR-7, and miR-26b were found to be significant miRNAs in treating SARS-CoV-2 coronavirus.
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Affiliation(s)
- Habib MotieGhader
- Department of Basic Sciences, Biotechnology Research Center, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
- Department of Biology, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
| | - Esmaeil Safavi
- Department of Basic Sciences, Biotechnology Research Center, Tabriz Branch, Islamic Azad University, Tabriz, Iran
- Department of Basic Sciences, Faculty of Veterinary Medicine, Tabriz Branch, Islamic Azad University, Tabriz, Iran
| | - Ali Rezapour
- Department of Animal Science, Faculty of Agriculture, Tabriz Branch, Islamic Azad University, Tabriz, Iran
| | - Fatemeh Firouzi Amoodizaj
- Department of Basic Sciences, Biotechnology Research Center, Tabriz Branch, Islamic Azad University, Tabriz, Iran
| | - Roya Asl Iranifam
- Department of Basic Sciences, Biotechnology Research Center, Tabriz Branch, Islamic Azad University, Tabriz, Iran
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Morselli Gysi D, do Valle Í, Zitnik M, Ameli A, Gan X, Varol O, Ghiassian SD, Patten JJ, Davey RA, Loscalzo J, Barabási AL. Network medicine framework for identifying drug-repurposing opportunities for COVID-19. Proc Natl Acad Sci U S A 2021; 118:e2025581118. [PMID: 33906951 PMCID: PMC8126852 DOI: 10.1073/pnas.2025581118] [Citation(s) in RCA: 176] [Impact Index Per Article: 58.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The COVID-19 pandemic has highlighted the need to quickly and reliably prioritize clinically approved compounds for their potential effectiveness for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. 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 experimentally screened in VeroE6 cells, as well as the list of drugs in clinical trials that capture the medical community's assessment of drugs with potential COVID-19 efficacy. We find that no single predictive algorithm offers consistently reliable outcomes across all datasets and metrics. This outcome prompted us to develop a multimodal technology that fuses the predictions of all algorithms, finding that a consensus among the different predictive methods consistently exceeds the performance of the best individual pipelines. We screened in human cells the top-ranked drugs, obtaining a 62% success rate, in contrast to the 0.8% hit rate of nonguided screenings. Of the six drugs that reduced viral infection, four could be directly repurposed to treat COVID-19, proposing novel treatments for COVID-19. We also found that 76 of the 77 drugs that successfully reduced viral infection do not bind the proteins targeted by SARS-CoV-2, indicating that these network drugs rely on network-based mechanisms 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.
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Affiliation(s)
- Deisy Morselli Gysi
- Network Science Institute, Northeastern University, Boston, MA 02115
- Department of Physics, Northeastern University, Boston, MA 02115
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115
| | - Ítalo do Valle
- Network Science Institute, Northeastern University, Boston, MA 02115
- Department of Physics, Northeastern University, Boston, MA 02115
| | - Marinka Zitnik
- Department of Biomedical Informatics, Harvard University, Boston, MA 02115
- Harvard Data Science Initiative, Harvard University, Cambridge, MA 02138
| | - Asher Ameli
- Department of Physics, Northeastern University, Boston, MA 02115
- Data Science Department, Scipher Medicine, Waltham, MA 02453
| | - Xiao Gan
- Network Science Institute, Northeastern University, Boston, MA 02115
- Department of Physics, Northeastern University, Boston, MA 02115
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115
| | - Onur Varol
- Network Science Institute, Northeastern University, Boston, MA 02115
- Department of Physics, Northeastern University, Boston, MA 02115
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey
| | | | - J J Patten
- Department of Microbiology, National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02118
| | - Robert A Davey
- Department of Microbiology, National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02118
| | - Joseph Loscalzo
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115
| | - Albert-László Barabási
- Network Science Institute, Northeastern University, Boston, MA 02115;
- Department of Physics, Northeastern University, Boston, MA 02115
- Department of Network and Data Science, Central European University, Budapest 1051, Hungary
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