A REVIEW ON ARTIFICIAL INTELLIGENCE IN ANTICANCER DRUG DEVELOPMENT

Pasam Jyothirmayi*, A. Anusha, Dr. N. Srinivasarao, Ch. Nagadeepthi, M. Sreelasya and P. Nagakusuma

Artificial intelligence is progressively spreading through the world of health, particularly in the field of oncology. AI offers new, exciting perspectives in drug development as toxicity and efficacy can be predicted from computer-designed active molecular structures. Their wider use is eagerly awaited as they should markedly reduce durations and costs. Health authorities cannot neglect this new paradigm in drug development and should take the requisite measures to include AI as a new pillar in conducting clinical research in oncology. Artificial intelligence (AI) has strong logical reasoning ability and independent learning ability, which can simulate the thinking process of the human brain. AI technologies such as machine learning can profoundly optimize the existing mode of anticancer drug research. But at present AI also has its relative limitation. Artificial intelligence based on big data can extract the hidden patterns, important information, and corresponding knowledge behind the enormous amount of data. Anti-cancer drug design has been acknowledged as a complicated, expensive, time-consuming, and challenging task. How to reduce the research costs and speed up the development process of anti-cancer drug designs has become a challenging. Computer-aided drug design methods have played a major role in the development of cancer treatments for over three decades. Recently, artificial intelligence has emerged as a powerful and promising technology for faster, cheaper, and more effective anti-cancer drug designs.