Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery.

Journal: BioMed research international
Published Date:

Abstract

Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare including research and chemical discoveries. Using large amounts of aggregated data, the AI can discover and learn further transforming these data into "usable" knowledge. Being well aware of this, the world's leading pharmaceutical companies have already begun to use artificial intelligence to improve their research regarding new drugs. The goal is to exploit modern computational biology and machine learning systems to predict the molecular behaviour and the likelihood of getting a useful drug, thus saving time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources to aid drug development. Pharmaceutical and medical researchers have extensive data sets that can be analyzed by strong AI systems. This review focused on how computational biology and artificial intelligence technologies can be implemented by integrating the knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in the cancer precision drug discovery.

Authors

  • Nagasundaram Nagarajan
    School of Humanities, Nanyang Technological University, 14 Nanyang Dr, Singapore 637332.
  • Edward K Y Yapp
    Singapore Institute of Manufacturing Technology, 2 Fusionopolis Way, Singapore 138634.
  • Nguyen Quoc Khanh Le
    In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; AIBioMed Research Group, Taipei Medical University, Taipei 110, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan. Electronic address: khanhlee@tmu.edu.tw.
  • Balu Kamaraj
    Department of Neuroscience Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Jubail 35816, Saudi Arabia.
  • Abeer Mohammed Al-Subaie
    Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
  • Hui-Yuan Yeh
    School of Humanities, Nanyang Technological University, 14 Nanyang Dr, Singapore 637332.