An Overview of the Role of Artificial Intelligence and Machine Learning in Pharmaceutical Research and Development

Abstract

During the previous decade, artificial intelligence (AI) and machine learning (ML) have become the cutting-edge technologies most likely to have a game-changing effect on Research and Development in the pharmaceutical industry. Bringing innovative pharmaceuticals to market and patients now cost more than most people can afford. Due to their automatic nature, predictive capacities and anticipated enhancement in efficiency, AI/ML technologies are interesting to the pharmaceutical industry in light of these issues. The complexity of ML approaches used to drug discovery has increased during the last 15–20 years. The most modern areas of drug development to see positive interruption from AI/ML include clinical trial design, conduct, and analysis. The COVID-19 pandemic may speed up the use of AI and ML in clinical trials as they become more reliant on digital technology. As we go forward into a future where AI/ML integration into Research and Development is rising, it is vital to cut through the accompanying buzzwords and noise. Equally important is remembering that the scientific method may still be used to evaluate evidence and make inferences. This way, one may evaluate the many AI/ML applications in the pharmaceutical business without being misled by marketing claims. This article seeks to explain key principles, provide use cases, provide insights, and provide a balanced perspective on how best to apply AI/ML technology in Research and Development.