Chapter 5 - Artificial intelligence and data science in pharmacogenomics-based drug discovery: Future of medicines

Abstract

Despite advancements in scientific knowledge about drugs and diseases, we still cannot achieve a high degree of accuracy and safety in the management of diseases. Even with time, the number of new diseases has been evolving, which further complicates the situation and poses an extra burden on the health-care system throughout the world. Efforts have been taken to tackle this problem through scientific advancement in novel approaches such as nanotechnology, computer-aided drug designing, gene therapy, and many more, but the presence of huge data and nonavailability of data processing mechanisms have always hindered the scientist from fully exploring the science. Artificial intelligence and data science are the new approaches of the 21st century that have the potential to process a large amount of scientific data at a very fast speed and with a high degree of accuracy. Pharmacogenomics is also an unexplored science that can provide more information and data about gene diseases and drug–gene interactions. But it is very complex to identify and interpret the exact nature of these interactions, so artificial intelligence is another area that when combined with pharmacogenomics may result in an excellent therapeutic system. However, pharmacogenomics and artificial intelligence have not been explored together as an integrated system. The combination of pharmacogenomics and artificial intelligence can be utilized in different areas of the health-care system such as drug discovery, formulation development, drug therapeutics, and data processing. In drug discovery, it helps in the prediction of drug targets, suitable drug molecules for the selected target, and identification of biomarkers (diagnostic biomarkers and therapeutic biomarkers). Drug therapy can be adjusted and recalibrated based on the data obtained from the patient's genotype and drug interaction. Similarly, a large amount of data can be easily processed from different phases of study, and an effective conclusion can be obtained. However, there is a need for the investment of more resources like time and money to get fruitful results.