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10.1080/17460441.2020.1811676

http://scihub22266oqcxt.onion/10.1080/17460441.2020.1811676
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32877233!?!32877233

suck abstract from ncbi

pmid32877233      Expert+Opin+Drug+Discov 2021 ; 16 (1): 23-38
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  • A public-private partnership for the express development of antiviral leads: a perspective view #MMPMID32877233
  • Mayburd A
  • Expert Opin Drug Discov 2021[Jan]; 16 (1): 23-38 PMID32877233show ga
  • INTRODUCTION: The COVID-19 pandemic raises the question of strategic readiness for emergent pathogens. The current case illustrates that the cost of inaction can be higher in the future. The perspective article proposes a dedicated, government-sponsored agency developing anti-viral leads against all potentially dangerous pathogen species. AREAS COVERED: The author explores the methods of computational drug screening and in-silico synthesis and proposes a specialized government-sponsored agency focusing on leads and functioning in collaboration with a network of labs, pharma, biotech firms, and academia, in order to test each lead against multiple viral species. The agency will employ artificial intelligence and machine learning tools to cut the costs further. The algorithms are expected to receive continuous feedback from the network of partners conducting the tests. EXPERT OPINION: The author proposes a bionic principle, emulating antibody response by producing a combinatorial diversity of high q uality generic antiviral leads, suitable for multiple potentially emerging species. The availability of multiple pre-tested agents and an even greater number of combinations would reduce the impact of the next outbreak. The methodologies developed in this effort are likely to find utility in the design of chronic disease therapeutics.
  • |*COVID-19 Drug Treatment[MESH]
  • |*Drug Industry[MESH]
  • |*SARS-CoV-2[MESH]
  • |Algorithms[MESH]
  • |Antiviral Agents/*therapeutic use[MESH]
  • |Drug Development/economics/*methods[MESH]
  • |Drug Evaluation, Preclinical[MESH]
  • |Humans[MESH]
  • |Internationality[MESH]
  • |Machine Learning[MESH]
  • |Public-Private Sector Partnerships/economics/*organization & administration[MESH]


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