Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design

Area of Science:

• * Infectious Diseases and Virology
• * Computational Biology and Bioinformatics
• * Artificial Intelligence and Machine Learning

Background:

• * The COVID-19 pandemic, caused by SARS-CoV-2, has resulted in significant global mortality.
• * Developing effective drugs and vaccines for SARS-CoV-2 is a time-consuming process.
• * Artificial intelligence (AI) and machine learning (ML) present potential avenues to expedite antiviral development.

Purpose of the Study:

• * To provide a comprehensive survey of AI and ML applications in combating COVID-19.
• * To analyze the challenges and future directions of AI/ML-driven solutions against the pandemic.
• * To offer insights for researchers on the role of AI and ML in fighting the COVID-19 outbreak.

Main Methods:

• * Extensive literature review of AI and ML applications for COVID-19.
• * Analysis of existing research on AI/ML in drug discovery and optimization for novel viruses.
• * Identification of current challenges and future research trajectories in the field.

Main Results:

• * AI and ML are being increasingly applied to accelerate the discovery and optimization of antiviral treatments for COVID-19.
• * Various AI/ML methodologies show promise in identifying potential drug candidates and understanding viral mechanisms.
• * The survey highlights the critical role of AI and ML in addressing the urgent need for effective COVID-19 therapeutics.

Conclusions:

• * AI and ML offer powerful tools to accelerate the fight against the COVID-19 pandemic.
• * Continued research and development in AI/ML are crucial for overcoming challenges in antiviral discovery.
• * This review provides a roadmap for leveraging AI and ML to combat current and future viral outbreaks.