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Table of Contents
EDITORIAL
Year : 2021  |  Volume : 9  |  Issue : 2  |  Page : 47-48

Importance of artificial intelligence techniques to combat COVID-19 pandemic


Department of Pharmacy, Sumandeep Vidyapeeth, Vadodara, Gujarat, India

Date of Submission12-Feb-2022
Date of Decision18-Feb-2022
Date of Acceptance20-Feb-2022
Date of Web Publication15-Mar-2022

Correspondence Address:
Dr. Ashish Shah
Department of Pharmacy, Sumandeep Vidyapeeth, Vadodara, Gujarat
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jihs.jihs_2_22

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How to cite this article:
Shah A. Importance of artificial intelligence techniques to combat COVID-19 pandemic. J Integr Health Sci 2021;9:47-8

How to cite this URL:
Shah A. Importance of artificial intelligence techniques to combat COVID-19 pandemic. J Integr Health Sci [serial online] 2021 [cited 2022 May 24];9:47-8. Available from: https://www.jihs.in/text.asp?2021/9/2/47/339647



Worldwide, 26 million peoples are affected and 5 million deaths occur since December 2019. Over the last 2 years, different variants evolved due to mutation in the virus. The lacks of specificity of approved drugs and effectiveness of vaccines[1] are the challenges against the treatment of this disease. Until now, only a few drug molecules have been used for the treatment or undergone clinical trial, and these molecules are mostly repurposed approved drugs.[2] Artificial intelligence used in various computational techniques can help to predict biological activities and toxicity of drug molecules. Computational methods are helpful to minimize the time and cost of drug discovery process. Structure-based and ligand-based drug designs are the two major categories used for the discovery of novel drug molecules. Various computational like homology modeling, molecular docking studies, molecular dynamics study, quantitative structure-activity relationship (QSAR), and prediction of ADME/T properties have been extensively used in the search of potential candidates against the virus. Both ligand-based and structure-based drug design methods have been useful to find out best leads that are effective against the virus.[3] Researchers have worked extensively using different databases to find out potential candidates which may be effective against COVID-19.[4] An extensive study on various plants and its constituents have been also done to find out effective natural products against COVID-19.[5] Besides the advantages of computational methods, there are certain limitations related to computational method as lead molecules derived using computational methods need to be validated through preclinical and clinical studies before market approval.

There are a number of examples reported, especially in the case of infectious disease where medical, paramedical, or cleaning staff gets infected as they are directly or indirectly involved with patients. After outbreak of Ebola 2015, it was discussed in the workshop organized by the White House Office of Science and Technology Policy and the National Science Foundation that there are three major areas where robotic technology can provide an efficient solution in pandemic disease which includes clinical care, logistics, and quarantines. Development of robotic technology in the above area may provide benefits in the current situation of COVID-19. For the control of disease, disinfection of noncontact ultraviolet surfaces by robotic technology[6] can be very useful because COVID-19 spreads not only through person to person via close contact or respiratory droplets but also via contaminated surfaces. The contaminated surface includes metals, glass, or plastic where this pathogen can survive up to some days. New robotic technology can be useful for identification of high-risk areas and to sterilize surfaces where contamination may occur. For the diagnosis purpose like temperature measurement in public areas, in-out hospital patient development of thermal robotic system can be useful.[7] For the diagnosis of COVID-19, sample collection is done by nasopharyngeal and oropharyngeal swabs. This test requires skilled staff for collection of samples, handling, and testing. In this whole procedure, robotic technology may speed up the process and reduce the risk of the infection. Some people do not have symptoms, but they are vectors to spread this infection. In this case, blood test is important to identify infection. Automated blood collection and testing can reduce the risk of infection. In a nutshell, COVID-19 disease can be a catalyst for the development of robotic technology. However, this task is challenging as robotic system development requires social gathering of experts to develop such complex models.[8]



 
  References Top

1.
Hwang W, Lei W, Katritsis NM, MacMahon M, Chapman K, Han N. Current and prospective computational approaches and challenges for developing COVID-19 vaccines. Adv Drug Deliv Rev 2021;172:249-74.  Back to cited text no. 1
    
2.
Galindez G, Matschinske J, Rose TD, Sadegh S, Salgado-Albarrán M, Späth J, et al. Lessons from the COVID-19 pandemic for advancing computational drug repurposing strategies. Nat Comput Sci 2021;1:33-41.  Back to cited text no. 2
    
3.
Gurung AB, Ali MA, Lee J, Farah MA, Al-Anazi KM. An updated review of computer-aided drug design and its application to COVID-19. Biomed Res Int 2021;2021:8853056.  Back to cited text no. 3
    
4.
Cuesta SA, Mora JR, Márquez EA. In silico screening of the DrugBank database to search for possible drugs against SARS-CoV-2. Molecules 2021;26:1100.  Back to cited text no. 4
    
5.
Shah A, Patel V, Parmar B. Discovery of some antiviral natural products to fight against novel coronavirus (SARS-CoV-2) using an in silico approach. Comb Chem High Throughput Screen 2021;24:1271-80.  Back to cited text no. 5
    
6.
Kovach CR, Taneli Y, Neiman T, Dyer EM, Arzaga AJ, Kelber ST. Evaluation of an ultraviolet room disinfection protocol to decrease nursing home microbial burden, infection and hospitalization rates. BMC Infect Dis 2017;17:186.  Back to cited text no. 6
    
7.
Leipheimer JM, Balter ML, Chen AI, Pantin EJ, Davidovich AE, Labazzo KS, et al. First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws. Technology (Singap World Sci) 2019;7:98-107.  Back to cited text no. 7
    
8.
Yang GZ, Nelson BJ, Murphy RR, Choset H, Christensen H, Collins SH, et al. Combating COVID-19 – The role of robotics in managing public health and infectious diseases. Sci Robot 2020;5:eabb5589.  Back to cited text no. 8
    




 

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