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How Artificial Intelligence is Transforming Medicine: The Future of Pharmaceutical Research

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Industry 4.0 and Healthcare

Part of the book series: Advanced Technologies and Societal Change ((ATSC))

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Abstract

For pharmaceutical businesses and biochemical experts, drug design and development is a critical field of study. Low effectiveness, off-target delivery, consumption of time, and increased price, on the other hand, provide a barrier and hurdles for medication design and development. Furthermore, the drug development process is hampered by complicated and large data from genomes, proteomics, microarray information, and clinical trials. In drug research and development, artificial intelligence and machine learning algorithms are critical. In other terms, deep learning algorithms and artificial neural networks have revolutionized the field. To analyse medications and their different uses, machine learning (ML) approaches are being used to anticipate substances with pharmacological properties, particular pharmacodynamic, absorption, distribution, metabolism, excretion, and toxicity (ADMET) features. Peptide formulation, edifice virtual testing, ligand-based silico, toxicity prognostication, drug tracking and release, pharmacophore modelling, quantifiable structure–activity connection, drug realigning, polypharmacology, and physical and chemical action have all used machine learning and data mining algorithms. The use of artificial intelligence and deep learning in this discipline is bolstered by historical evidence. Furthermore, fresh data mining, curation, and administration strategies aided newly built modelling algorithms significantly. Advanced artificial intelligence (AI) seems to have the potential to greatly improve the statistical methodology's involvement in drug development. AI's use in drug research, medicinal chemistry, pharmaceutical efficiency, and clinical trials will undoubtedly minimize human burden while also allowing for the achievement of goals in a short amount of time. The intersection of machine learning approaches, computational tools, and the prospects of AI in the pharma industry is explored in this chapter.

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Author information

Authors and Affiliations

  1. Department of Pharmaceutics, ShriRam College of Pharmacy, Morena, MP, India

    Pankaj Sharma

  2. Department of Pharmacognosy, ShriRam College of Pharmacy, Morena, MP, India

    Vinay Jain

  3. School of Studies in Pharmaceutical Sciences, Jiwaji University, Gwalior, MP, India

    Mukul Tailang

Authors
  1. Pankaj Sharma
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  2. Vinay Jain
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  3. Mukul Tailang
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Corresponding author

Correspondence to Pankaj Sharma .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Gyan Ganga Institute of Technology and Sciences, Jabalpur, India

    Ashish Mishra

  2. Western Norway University of Applied Science, Bergen, Norway

    Jerry Chun-Wei Lin

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Sharma, P., Jain, V., Tailang, M. (2023). How Artificial Intelligence is Transforming Medicine: The Future of Pharmaceutical Research. In: Mishra, A., Lin, J.CW. (eds) Industry 4.0 and Healthcare . Advanced Technologies and Societal Change. Springer, Singapore. https://doi.org/10.1007/978-981-99-1949-9_7

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