Introduction Drug discovery is the process of identifying potential novel pharmaceuticals. It touches on a number of scientific domains, such as pharmacology, chemistry, and biology. Flemming (2018) asserts that drug discovery is a process through which new medications against diseases are discovered. It involves the use of a wide variety of technologies and expertise. In general, discovering and developing a drug takes US$2.8 billion and 15 years on average. According to Bali and Bali (2022), reports of drug design using artificial intelligence (AI) and computational techniques have increased recently. The reason behind this is because big data, or data sets derived by contemporary biological procedures, have grown to be enormous, complicated, and multidimensional, and traditional computing methods are unable to handle them accurately enough. The role of AI in Vaccine Development These days, artificial intelligence is a strong tool that permeates almost every aspect of our life. It uses a computer to conduct research, pick up patterns from the available dataset, “think,” and apply what it has learned to generate specific predictions. Today AI has profoundly advanced the field of healthcare through the introduction of a greater degree of automation, convenience and higher accuracy and precision in diagnostic and therapeutic care (Davenport & Kalakota, 2019). Bali and Bali (2022) assert that “with the introduction of robotic technologies, medical personnel are being relieved of usual routine tasks, thus allowing them to concentrate more on more crucial aspects of patient care, but the robots are actually assisting surgeons during surgical procedures. In some cases, computer algorithms are actually outmatching the capabilities of radiologists in the detection of malignancy in tumors”. They explain that “machine learning can accurately predict several compound properties like target binding affinity, membrane transport properties, and toxicity aspects, pharmacokinetic or pharmacodynamics parameters without the need for an actual synthesis of the compounds or their evaluation”. Modern technology has grown and developed in the 21st century in a way that has never been witnessed before for the good of society. The medical and healthcare industries have benefited greatly from AI and ML technologies, which are predicted to reach a $45.2 billion industry by 2025. Medical staff may now focus more on critical parts of patient care as a result of the advent of robotic technologies, which relieve them of monotonous work. However, during surgical procedures, the robots are really helping doctors. (Alca´cerac & Cruz-Machado, 2019). In many instances, computer algorithms are genuinely surpassing radiologists’ skills in identifying malignancy within tumors. AI is being used to lessen the hazards that humans represent to patients and healthcare workers in a number of areas, including automated patient room disinfection, blood sample collection and transportation, preservation, and analysis (Oztemel & Gursev, 2020). Conclusion Artificial Intelligence (AI) is a very good development in the world of drug discovery. With the current wave of the rise of new epidemics and pandemics, it can be utilized to effectively birth drugs and medical support that will conquer the diseases. Surely the continuous advancement in technology and innovation will only motivate scientists – microbiologists and researchers to do more work in drug discovery. References Alca´cerac, V., & Cruz-Machado, V. (2019). Scanning the industry 4.0: A literature review on technologies for manufacturing systems. Engineering Science and Technology, An International Journal, 22, 899–919. Bali, A. & Bali, N. (2022). Role of artificial intelligence in fast-track drug discovery and vaccine development for COVID-19 In Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19. Elsevier Inc. Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. Fleming, N. (2018). How artificial intelligence is changing drug discovery. Nature 557, S55–S57. Oztemel, E., & Gursev, S. (2020). Literature review of industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(4), 127–182. Abdulsalam Mustapha is a Lecturer II in the Department of Microbiology at Skyline University Nigeria. He has completed his MSc in Microbiology from the University of Ilorin, Nigeria, where he specialized in Industrial and Pharmaceutical Microbiology.
