Advances in artificial intelligence-based technologies for increasing the quality of medical products.

Journal: Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences
Published Date: Nov 30, 2024

Abstract

Artificial intelligence (AI) is a technology that combines machine learning (ML) and deep learning. It has numerous usages in the domains of medicine and other sciences. Artificial intelligence can forecast the behavior of a drug's target protein and predict its desired physicochemical qualities. AI's potential to enhance healthcare services offerings formerly unheard-of opportunities for cost reserves, enhanced overall clinical and patient outcomes. The recent development of research in the biomedical field, encompassing fields such as genomics, computational medicine, AI, and algorithms for learning, has led to the demand for novel technology, a fresh workforce, and new standards of practice set the stage for the revolution in healthcare. By connecting these health statistics with cutting-edge AI technologies, precise insights into patient treatment can be obtained. Moreover, AI can aid in the search for new drugs by foretelling the target protein's two-dimensional structure. In the current review, an overview of the latest AI-based technologies and how they may be employed to reduce product development time to market and snowballing product quality, cost-effectiveness, as well as security throughout the manufacturing process is detailed.

Authors

  • Nidhi Srivastava
    Maharishi School of Pharmaceutical Sciences, Maharishi University of Information and Technology, Lucknow, Uttar Pradesh, India. nidhimpharm@gmail.com.
  • Sneha Verma
    School of Science and Technology, City University of London, London, EC1V 0HB, UK. sneha.verma@city.ac.uk.
  • Anupama Singh
    Maharishi School of Pharmaceutical Sciences, Maharishi University of Information and Technology, Lucknow, Uttar Pradesh, India.
  • Pranki Shukla
    Maharishi School of Pharmaceutical Sciences, Maharishi University of Information and Technology, Lucknow, Uttar Pradesh, India.
  • Yashvardhan Singh
    Maharishi School of Pharmaceutical Sciences, Maharishi University of Information and Technology, Lucknow, Uttar Pradesh, India.
  • Ankit D Oza
    Department of Mechanical Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat, India.
  • Tanvir Kaur
    Department of Biotechnology, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.
  • Sohini Chowdhury
    Chitkara Centre for Research and Development, Chitkara University, Baddi, Himachal Pradesh, India.
  • Monit Kapoor
    Centre of Research Impact and Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India.
  • Ajar Nath Yadav
    Department of Genetics, Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmour, Himachal Pradesh, India. ajarbiotech@gmail.com.

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