www.ijcrt.org © 2020 IJCRT | Volume 8, Issue 8 August 2020 | ISSN: 2320-2882 IJCRT2008092 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt.org 727 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY 1 Sukhvinder Singh Sudan, 2 Urvi Marhatta, 3 Gurvinder Singh Sudan 1 B.tech, 2 B.Tech, 3 B.Tech student 1 Department of Biotechnology, 1 Graphic Era deemed to be University, Dehradun, India Abstract: The rapid advancements in the field of Artificial intelligence have opened new gateways to revolutionize the process of drug development. The use of AI tools and techniques by the pharmaceutical industry has called for its collaboration with the IT space. AI can help the pharmaceutical industry by reducing R&D costs and time thereby reducing the escalating costs of the drug development process. In this review we discuss the major possibilities and uses of artificial intelligence in the drug development process. Index Terms – Drug designing, artificial intelligence, machine learning, Pharmaceuticals, IT. I. INTRODUCTION Artificial Intelligence is the simulation or imitations of human intelligence by machines enabling them with the ability to think and function like humans. Artificial intelligence has become an influential and crucial part of the 21 st century due to its capability and potential in managing complex and large amounts of data efficiently which has proved it to be a boon for the technology industry. The basic goals of Artificial intelligence include reasoning, data sorting, learning, natural language processing and the ability to wield objects using approaches such as statistical methods, traditional symbolic AI, computational methods, economics, psychology and many other relevant methodologies [1]. Many major subjects are employed in AI research and development including computer science, information technology, mathematics, statistics, philosophy, linguistics and many other fields. Though AI has helped improving many industries it also poses many ethical issues that are a cause of concern for the scientific community. Many believe that creating machines with human intelligence could threaten our very existence if it goes unabated where as others believe that AI will encourage mass unemployment across sectors. Though these risks are a matter of concern Artificial Intelligence has proven to be a virtue for the healthcare industry specifically in expediting the process of drug discovery. In this review the possible advantages of AI in drug development process are being discussed. II. The Process and attrition rate of Drug Development Every year several numbers of drugs are approved for use and launched in the market for different diseases. Thousands of potential drug candidates are screened and trialed to discover one potential drug for the treatment of a particular disease which costs more than a billion dollars in funds and takes around 10 years to reach the market. The journey starts at a university or a research institution funded by various agencies and pharmaceutical groups where basic research on understanding the cellular and molecular aspects of a disease starts. It is through this understanding of the pathways and processes of a disease that leads to the identification of potential targets for the new treatments. These targets may include but not limited to genes, some proteins that are instrumental to the disease for a new treatment. After this researchers look for potential compounds with biological activity which might be chemically or artificially synthesized, plant derived, fungi or marine organisms based as well as new compounds created using computers employing knowledge of proteins and genetics. As many as 10000 compounds could be considered for a single target which is further narrowed down to 10 to 20 after they show theoretical interference in the disease process. The compound that shows activity against the selected target is called a hit [2]. Several numbers of hits are discovered while screening different compounds in the drug discovery process. The next step in the process is the identification of a lead compound. A lead compound is the one that shows the most promising activity against the selected target and can be used to develop a potential drug for the disease. Once a lead compound has been identified, its chemical structure is modified for pertaining maximum efficacy, selectivity and activity while reducing toxicity or any kind of negative effects that might prevail. Despite the presence of an efficient system of drug likeness guidelines for drug development, pharmaceutical companies have to face rigorous challenges in improving R&D efficiency and keeping the process economically viable. R&D efficiency is simply defined as the total number of drugs approved by the US FDA per billion US$ spent on R&D alone. Since 2001 the cost of developing a new treatment has increased from US$ 800 million to approximately US$ 3 billion currently. These increasing R&D costs and increasing attrition rate are a cause of great concern for the pharmaceutical companies [3]. The major underlying reason is that out of all the chemical compounds those are in phase IIB and phase III trials, 62% of them never make it to the clinics. The major reason for these late stage failures are attributed to clinical safety and efficacy, pharmacokinetics, toxicology and bioavailability. These late stage