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Artificial Intelligence-Based Drug Production Quality Management Data.

Authors :
Yu, Chenggong
Source :
Mathematical Problems in Engineering. 8/23/2022, p1-14. 14p.
Publication Year :
2022

Abstract

As a special commodity, medicine plays a vital role in people's healthy life. The basic effects of drugs are excitation and inhibition. Under the action of drugs, any function that can enhance or increase the function of the body's original tissues and organs is called excitement. On the contrary, any function that can weaken or reduce the function of the original tissues and organs of the body is called inhibition. The nature of action of drugs has three aspects: regulatory function; antipathogen and antitumor; and complementary therapy. If there is a problem with the quality and safety of medicines, it is tantamount to making money and killing people. Based on artificial intelligence, this paper analyzes the current situation and improvement strategies of quality management in pharmaceutical production management enterprises and proposes how to reduce the risk of drug safety with the assistance of artificial intelligence technology. The experimental results in this paper show that the sales of heparin sodium APIs were 2.099 billion yuan, accounting for 91.6% of the operating income in 2015, when company A had not conducted a drug risk assessment in 2015. After the outbreak of drug risks, the sales in 2016 were 1.743 billion yuan, accounting for 77.1% of the operating income in 2016. After the final implementation of the measures, the sales in 2019 were 4.743 billion yuan, accounting for 329.1% of the operating income in 2016. The research method in this paper can improve the hidden safety problems of drugs more efficiently, and it can improve the profit while ensuring the safety. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1024123X
Database :
Academic Search Index
Journal :
Mathematical Problems in Engineering
Publication Type :
Academic Journal
Accession number :
158676640
Full Text :
https://doi.org/10.1155/2022/4089917