Title |
Antiviral Approaches against Influenza Virus
|
---|---|
Published in |
Clinical Microbiology Reviews, January 2023
|
DOI | 10.1128/cmr.00040-22 |
Pubmed ID | |
Authors |
Rashmi Kumari, Suresh D. Sharma, Amrita Kumar, Zachary Ende, Margarita Mishina, Yuanyuan Wang, Zackary Falls, Ram Samudrala, Jan Pohl, Paul R. Knight, Suryaprakash Sambhara |
Abstract |
Preventing and controlling influenza virus infection remains a global public health challenge, as it causes seasonal epidemics to unexpected pandemics. These infections are responsible for high morbidity, mortality, and substantial economic impact. Vaccines are the prophylaxis mainstay in the fight against influenza. However, vaccination fails to confer complete protection due to inadequate vaccination coverages, vaccine shortages, and mismatches with circulating strains. Antivirals represent an important prophylactic and therapeutic measure to reduce influenza-associated morbidity and mortality, particularly in high-risk populations. Here, we review current FDA-approved influenza antivirals with their mechanisms of action, and different viral- and host-directed influenza antiviral approaches, including immunomodulatory interventions in clinical development. Furthermore, we also illustrate the potential utility of machine learning in developing next-generation antivirals against influenza. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 14 | 17% |
Mexico | 4 | 5% |
India | 4 | 5% |
Colombia | 4 | 5% |
Chile | 2 | 2% |
France | 2 | 2% |
Niger | 1 | 1% |
Bosnia and Herzegovina | 1 | 1% |
Israel | 1 | 1% |
Other | 10 | 12% |
Unknown | 38 | 47% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 63 | 78% |
Scientists | 11 | 14% |
Practitioners (doctors, other healthcare professionals) | 7 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 11% |
Student > Bachelor | 3 | 8% |
Lecturer | 2 | 5% |
Other | 2 | 5% |
Student > Master | 2 | 5% |
Other | 5 | 14% |
Unknown | 19 | 51% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 11% |
Biochemistry, Genetics and Molecular Biology | 4 | 11% |
Nursing and Health Professions | 3 | 8% |
Immunology and Microbiology | 3 | 8% |
Medicine and Dentistry | 2 | 5% |
Other | 1 | 3% |
Unknown | 20 | 54% |