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COVID-19: Hard Road to Find Integrated Computational Drug and Repurposing Pipeline

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Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis

Part of the book series: Studies in Computational Intelligence ((SCI,volume 923))

Abstract

Shedding of infectious coronavirus disease (COVID-19) is affecting 215 countries and territories; quickly circulates continuously in worldwide. The vital scientific communities are rigorously looking at these public health challenges, global crisis and finding new ways to deal with this pandemic disease. Currently, there is no specific effective approved drug or vaccine available in the market to treat or prevent COVID-19. Thus, there is an urgent need for more and better research to boost up the development of effective therapeutic vaccines and drugs against this virus. Numerous solidarity clinical trial studies, high-level effort and investigations are underway. The repurposing drugs such as chloroquine and its derivatives, remdesivir, favipiravir, darunavir, umifenovir, nitazoxanide and thalidomide are being used globally for clinical trial studies to test their safety and efficacy in this pandemic virus treatment, some of which are already being tested in COVID-19 patients. The computational intelligence methods including machine learning has been useful in computer-aided drug design and drug repurposing. This chapter focus on strengthening the current understanding of the selected number of repurposing antivirals, antiretroviral, antimalarial, and anti-inflammatory drugs that can fight with COVID-19 infection. Further, we look forward to an insightful piece of drug compounds that can be used either individually or in combination.

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Acknowledgements

AS acknowledges funding from the Indian Council of Medical Research, New Delhi (Grant No. 45/17/2019-PHA/BMS) for financial assistance. SQ is supported by DST-Inspire Fellowship, Department of Science & Technology, Government of India.

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Authors and Affiliations

  1. Tumor Biology, ICMR-National Institute of Pathology, New Delhi, India

    Ankita Sahu & Saurabh Verma

  2. Department of Computer Science, Jamia Millia Islamia, New Delhi, India

    Ankita Sahu, Sahar Qazi & Khalid Raza

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  1. Ankita Sahu
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  2. Sahar Qazi
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  4. Saurabh Verma
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Correspondence to Saurabh Verma .

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  1. Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi, India

    Khalid Raza

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Sahu, A., Qazi, S., Raza, K., Verma, S. (2021). COVID-19: Hard Road to Find Integrated Computational Drug and Repurposing Pipeline. In: Raza, K. (eds) Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis. Studies in Computational Intelligence, vol 923. Springer, Singapore. https://doi.org/10.1007/978-981-15-8534-0_15

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