| Summary: | The pathogen SARS-CoV-2 has emerged and taken the shape of a global pandemic by causing COVID-19. SARS-CoV-2 has a very novel and unique set of genetic makeup that has created a puzzle in biological research. Therefore, the scientific community has not yet discovered a very effective new treatment or preventive solution. By using various bioinformatics techniques and tools, the decoding of the genomic structure of the virus has been possible. In COVID-19 research methodologies, next-gene sequencing and computer-aided drug design have been implemented to decode this new structure of the SARS-CoV-2. Implementing in silico studies for COVID-19 has analyzed various evolutionary relationships, sequencing errors, and for determining potential candidates against the SARS-CoV-2 genes, and that too in a short span. The information derived using various bioinformatics techniques would fast forward the research speed on the SARS-CoV-2 and provide essential information for vaccine development, which is essential to ensure the overall betterment of public health. The application of artificial intelligence (AI) and Machine learning (ML) has provided an attractive niche for the bio-therapeutics development for COVID-19. This review article describes the application of AI and ML for the therapeutic management of COVID-19.
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