A comprehensive review on role of Artificial Intelligence (AI) in drug discovery and drug development

The modeling of human behavior in connection to the intellectual processes involved in problem solving is known as artificial intelligence (AI). Human cognitive science reading, observation, planning, interpretation, reasoning, correction, speech recognition, linguistics, and other sources are examples of these mechanisms. Artificial Intelligence (AI) streamlines processes by enabling computers to learn from prior experiences, map efforts and actions to outcomes, detect faults and rectify them, adapt to new and random input values, and carry out human-like jobs with ease through comprehensive scenario analysis. By evaluating, filtering, sorting, forecasting, scoping, and figuring out massive data volumes to adhere to the finest implementation practices for generating an ideal solution, artificial intelligence (AI) streamlines work. As of 2019, the main uses of AI in the pharmaceutical industry include: drug discovery and development; drug-adherence and dosage; using AI to make sense of clinical data and produce better analytics; finding more reliable patients for clinical trials more quickly; introducing automated robot pharmacies to fill prescriptions and dispensing; and marketing, logistics, and supply chain. Above all, artificial intelligence has the potential to save lives by reducing expenses and developing novel, efficient treatments. Thus, biotech businesses ought to begin utilizing AI's benefits as soon as possible. Therefore, adopting AI and machine learning solutions will benefit the sector greatly. It can be effectively applied to build a robust, long-lasting pipeline of novel medications. We would be able to develop medications more quickly and more cheaply if we could harness the power of contemporary supercomputers and machine learning. This paper provides a thorough analysis of the state of artificial intelligence in pharmaceutical sciences, with a focus on the pharmaceutical industry. In summary, human-machine cooperation is the way of the future, and as technology develops, human clinical professionals will also need to adapt, learn, and develop. It is the evolution of medicine, not its extinction, even though future experts will need to be proficient in both medicine and technology.