Artificial Intelligence in Pharmaceutical Field-A Critical Review

被引：9

作者：

Shanbhogue, Maithri H. ^{[1
]}

Thirumaleshwar, Shailesh ^{[1
]}

Kumar, T. M. Pramod ^{[1
]}

Kumar, S. Hemanth ^{[1
]}

机构：

[1] JSS Acad Higher Educat & Res, JSS Coll Pharm, Dept Pharmaceut, Sri Shivarathreeshwara Nagara, Mysuru 570015, Karnataka, India

来源：

CURRENT DRUG DELIVERY | 2021年 / 18卷 / 10期

关键词：

Artificial intelligence; pharmaceutical sciences; drug development; data management; machine learning; comput-er-aided system; NEURAL-NETWORKS; IN-SILICO; PREDICTION; DESIGN;

D O I：

10.2174/1567201818666210617100613

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Artificial intelligence is an emerging sector in almost all fields. It is not confined only to a particular category and can be used in various fields like research, technology, and health. AI mainly concentrates on how computers analyze data and mimic the human thought process. As drug development involves high R & D costs and uncertainty in time consumption, artificial intelligence can serve as one of the promising solutions to overcome all these demerits. Due to the availability of enormous data, there are chances of missing out on some crucial details. To solve these issues, algorithms like machine learning, deep learning, and other expert systems are being used. On successful implementation of AI in the pharmaceutical field, the delays in drug development, failure at the clinical and marketing level can be reduced. This review comprises information regarding the development of AI, its subfields, its overall implementation, and its application in the pharmaceutical sector and provides insights on challenges and limitations concerning AI.

引用

页码：1421 / 1431

页数：11

共 76 条

[1] QbD guided early pharmaceutical development study: Production of lipid nanoparticles by high pressure homogenization for skin cancer treatment [J].