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The potential applications of artificial intelligence in drug discovery and development
Author(s) -
Hassan Farghali,
Nikolina Kutinová Canová,
Meenakshi Arora
Publication year - 2021
Publication title -
physiological research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.647
H-Index - 70
eISSN - 1802-9973
pISSN - 0862-8408
DOI - 10.33549/physiolres.934765
Subject(s) - drug repositioning , repurposing , drug discovery , computer science , drug development , artificial intelligence , data science , process (computing) , drug , big data , medicine , pharmacology , bioinformatics , engineering , data mining , biology , operating system , waste management
Development of a new dug is a very lengthy and highly expensive process since only preclinical, pharmacokinetic, pharmacodynamic and toxicological studies include a multiple of in silico, in vitro, in vivo experimentations that traditionally last several years. In the present review, we briefly report some examples that demonstrate the power of the computer-assisted drug discovery process with some examples that are published and revealing the successful applications of artificial intelligence (AI) technology on this vivid area. Besides, we address the situation of drug repositioning (repurposing) in clinical applications. Yet few success stories in this regard that provide us with a clear evidence that AI will reveal its great potential in accelerating effective new drug finding. AI accelerates drug repurposing and AI approaches are altogether necessary and inevitable tools in new medicine development. In spite of the fact that AI in drug development is still in its infancy, the advancements in AI and machine-learning (ML) algorithms have an unprecedented potential. The AI/ML solutions driven by pharmaceutical scientists, computer scientists, statisticians, physicians and others are increasingly working together in the processes of drug development and are adopting AI-based technologies for the rapid discovery of medicines. AI approaches, coupled with big data, are expected to substantially improve the effectiveness of drug repurposing and finding new drugs for various complex human diseases.

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