Opportunities and challenges in application of artificial intelligence in pharmacology.

Journal: Pharmacological reports : PR
Published Date:

Abstract

Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a huge amount of medical data every day. Therefore, we need an automated and reliable evaluation tool that can make decisions more accurately and faster. Machine learning has the potential to learn, understand and analyse the data used in healthcare systems. In the last few years, AI is known to be employed in various fields in pharmaceutical science especially in pharmacological research. It helps in the analysis of preclinical (laboratory animals) and clinical (in human) trial data. AI also plays important role in various processes such as drug discovery/manufacturing, diagnosis of big data for disease identification, personalized treatment, clinical trial research, radiotherapy, surgical robotics, smart electronic health records, and epidemic outbreak prediction. Moreover, AI has been used in the evaluation of biomarkers and diseases. In this review, we explain various models and general processes of machine learning and their role in pharmacological science. Therefore, AI with deep learning and machine learning could be relevant in pharmacological research.

Authors

  • Mandeep Kumar
    Department of Pharmacy, Unit of Pharmacology and Toxicology, University of Genoa, Genoa, Italy.
  • T P Nhung Nguyen
    Department of Pharmacy, Unit of Pharmacology and Toxicology, University of Genoa, Genoa, Italy.
  • Jasleen Kaur
    School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.
  • Thakur Gurjeet Singh
    Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India.
  • Divya Soni
    Department of Pharmacology, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India.
  • Randhir Singh
    Department of Pharmacology, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India.
  • Puneet Kumar
    Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, India. Electronic address: pkumar99@cs.iitr.ac.in.