Artificial Intelligence (AI) in Drugs and Pharmaceuticals

被引:18
|
作者
Sahu, Adarsh [1 ]
Mishra, Jyotika [1 ]
Kushwaha, Namrata [2 ]
机构
[1] Dr Hari Singh Gour Vishwavidyalaya, Dept Pharmaceut Sci, Sagar, MP, India
[2] Sri Aurobindo Inst Pharm, Indore, MP, India
关键词
Deep learning; machine learning; artificial neural network; drug design; drug discovery; pharmaceuticals; VIRTUAL SCREENING STRATEGIES; PROTEIN-PROTEIN INTERFACES; DE-NOVO DESIGN; MOLECULAR-PROPERTIES; INTERACTION NETWORKS; SECONDARY STRUCTURE; SCORING FUNCTION; NEURAL-NETWORKS; HEALTH-CARE; PREDICTION;
D O I
10.2174/1386207325666211207153943
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The advancement of computing and technology has invaded all the dimensions of science. Artificial intelligence (AI) is one core branch of Computer Science, which has percolated to all the arenas of science and technology, from core engineering to medicines. Thus, AI has found its way for application in the field of medicinal chemistry and heath care. The conventional methods of drug design have been replaced by computer-aided designs of drugs in recent times. AI is being used extensively to improve the design techniques and required time of the drugs. Additionally, the target proteins can be conveniently identified using AI, which enhances the success rate of the designed drug. The AI technology is used in each step of the drug designing procedure, which decreases the health hazards related to preclinical trials and also reduces the cost substantially. The AI is an effective tool for data mining based on the huge pharmacological data and machine learning process. Hence, AI has been used in de novo drug design, activity scoring, virtual screening and in silico evaluation in the properties (absorption, distribution, metabolism, excretion and toxicity) of a drug molecule. Various pharmaceutical companies have teamed up with AI companies for faster progress in the field of drug development, along with the healthcare system. The review covers various aspects of AI (Machine learning, Deep learning, Artificial neural networks) in drug design. It also provides a brief overview of the recent progress by the pharmaceutical companies in drug discovery by associating with different AI companies.
引用
收藏
页码:1818 / 1837
页数:20
相关论文
共 50 条
  • [21] Artificial Intelligence (AI) in the asylum system
    Memon, Amina
    Given-Wilson, Zoe
    Ozkul, Derya
    Richmond, Karen McGregor
    Muraszkiewicz, Julia
    Weldon, Ella
    Katona, Cornelius
    [J]. MEDICINE SCIENCE AND THE LAW, 2024, 64 (02) : 87 - 90
  • [22] AI (Artificial Intelligence) and Hypertension Research
    Franco B. Mueller
    [J]. Current Hypertension Reports, 2020, 22
  • [23] Survey on Artificial Intelligence (AI) in Radiology
    Lingelbach, Sabine
    [J]. RADIOLOGE, 2020, 60 (10): : 1002 - 1002
  • [24] The eye in AI: artificial intelligence in ophthalmology
    Keel, Stuart
    van Wijngaarden, Peter
    [J]. CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY, 2019, 47 (01): : 5 - 6
  • [25] Artificial Intelligence (AI) Applications in Chemistry
    Naik, Ishita
    Naik, Dishita
    Naik, Nitin
    [J]. ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS, UKCI 2023, 2024, 1453 : 545 - 557
  • [26] Artificial intelligence (AI) in diagnostic imaging
    Braunschweig, Rainer
    Kildal, Daniela
    Janka, Rolf
    [J]. ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2024, 196 (07): : 664 - 670
  • [27] ARTIFICIAL-INTELLIGENCE - AN EYE ON AI
    TATE, P
    [J]. DATAMATION, 1984, 30 (01): : 54 - &
  • [28] Lamarck, Artificial Intelligence (AI), and belief
    Wilks, Yorick
    [J]. BEHAVIORAL AND BRAIN SCIENCES, 2009, 32 (06) : 538 - +
  • [29] Risks of Artificial Intelligence (AI) in Medicine
    Siafakas, Nikolaos
    Vasarmidi, Eirini
    [J]. PNEUMON, 2024,
  • [30] AI - Implementing Artificial Intelligence Correctly
    Krome, Susanne
    [J]. ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2024, 196 (08): : 780 - 781