School of Pharmaceutical Sciences, MVN University, Haryana 121102, India.
GL Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India.
Biomed Res Int. 2022 Jul 6;2022:7205241. doi: 10.1155/2022/7205241. eCollection 2022.
The global COVID-19 (coronavirus disease 2019) pandemic, which was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a significant loss of human life around the world. The SARS-CoV-2 has caused significant problems to medical systems and healthcare facilities due to its unexpected global expansion. Despite all of the efforts, developing effective treatments, diagnostic techniques, and vaccinations for this unique virus is a top priority and takes a long time. However, the foremost step in vaccine development is to identify possible antigens for a vaccine. The traditional method was time taking, but after the breakthrough technology of reverse vaccinology (RV) was introduced in 2000, it drastically lowers the time needed to detect antigens ranging from 5-15 years to 1-2 years. The different RV tools work based on machine learning (ML) and artificial intelligence (AI). Models based on AI and ML have shown promising solutions in accelerating the discovery and optimization of new antivirals or effective vaccine candidates. In the present scenario, AI has been extensively used for drug and vaccine research against SARS-COV-2 therapy discovery. This is more useful for the identification of potential existing drugs with inhibitory human coronavirus by using different datasets. The AI tools and computational approaches have led to speedy research and the development of a vaccine to fight against the coronavirus. Therefore, this paper suggests the role of artificial intelligence in the field of clinical trials of vaccines and clinical practices using different tools.
全球 COVID-19（2019 年冠状病毒病）大流行是由严重急性呼吸系统综合症冠状病毒 2（SARS-CoV-2）引起的，导致全球范围内大量人员死亡。SARS-CoV-2 的意外全球扩张给医疗系统和医疗机构带来了重大问题。尽管做出了所有努力，但开发针对这种独特病毒的有效治疗方法、诊断技术和疫苗仍然是当务之急，需要很长时间。然而，疫苗开发的首要步骤是确定疫苗的可能抗原。传统方法耗时较长，但自 2000 年反向疫苗学（RV）的突破性技术问世以来，检测抗原所需的时间从 5-15 年缩短到 1-2 年。不同的 RV 工具基于机器学习（ML）和人工智能（AI）。基于 AI 和 ML 的模型在加速发现和优化新抗病毒药物或有效疫苗候选物方面显示出了有希望的解决方案。在当前情况下，人工智能已被广泛用于针对 SARS-COV-2 治疗发现的药物和疫苗研究。这对于通过使用不同的数据集来识别具有抑制人类冠状病毒潜力的现有潜在药物更有用。人工智能工具和计算方法推动了针对冠状病毒的疫苗研究和开发。因此，本文提出了人工智能在疫苗临床试验和使用不同工具的临床实践中的作用。
