Optimization of Compound Active Ingredients and Compatibility AI Simulation and Its Inhibition of Novel Coronavirus Infection | Chapter 8 | Diagnostic and Treatment Advances in COVID-19 and SARS-CoV-2

 To date, COVID-19 has infected nearly 600 million people and killed 6.45 million people worldwide. Existing antiviral drugs are almost ineffective, the efficacy of new developed drugs is uncertain, and different types of vaccines do not achieve the desired results. In the development history of more than 3,000 years, TCM has participated in the prevention and control of major epidemics more than 500 times, and has accumulated rich practical experience. However, in the current epidemic prevention and control, there are serious deficiencies in how to make the virus quickly turn Yin, reduce the infectivity, quickly improve the symptoms, reduce the severe rate of the elderly and children, eliminate social panic, the development of convincing drugs for the people and the formation of the absolute advantage of western medicine. In the preliminary work of this project, the relevant literature was analyzed and sorted out, and the TCM Characteristic Database, The Descriptive Database of Disease syndrome Group, and The Master Methods database of Traditional Chinese Medicine were established. The study on the basis of early, proposed to tonic by strengthening the body immune response to suppress COVID-19 virus of Chinese medicine treatment: 1) with artificial intelligence technology deep mining classics, systematic analysis of the theory of TCM disease prevention and prescription 2) based on big data and COVID-19 disease big data AI optimization new compatibility, new prescription 3) through in vivo and in vitro integration experimental research, verify the efficacy of tonic prescription against COVID-19 and mechanism of (4) new formula for clinical research, evaluation of its comprehensive curative effect, for TCM treatment of virus disease provide new control ideas.

Author(s) Details:

Qiang Wang,
Gansu Medical College, Pingliang 744000, China.

Siyang Zhou,
Gansu Medical College, Pingliang 744000, China.

Fenfen Zhang  ,
Gansu Medical College, Pingliang 744000, China.

Jianshe Yang,
Gansu Medical College, Pingliang 744000, China and Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai 200072, China.

Please see the link here: https://stm.bookpi.org/DTACSC/article/view/9559