A New Era of Machine Learning Augmenting Pharmaceutical Industry

ML's success is evident by use of ML by increasing pharmaceutical industries in their business models. Several pharmaceutical development processes utilized machine learning algorithms for de novo drug discovery and biometrics data analysis from wearable devices, pharmacovigilance, manufacturing and supply chain. The primary goal of using ML is to reduce the time and resources spent for drug discovery and development, to be specific, in the high-throughput screening (HTS) technique and also to avoid animal testing for drugs, which has garnered negative attention from public. Due to increased costs and decreased efficiency, the pharmaceutical industry faces challenges in drug discovery. Machine learning algorithm advancements have sparked greater interest from researchers and increased pharmaceutical company collaborations. In this article we have reviewed and briefly summarized various applications of machine learning in pharmaceutical industry along with some examples. At the end we have also discussed the future challenges and potential growth of ML in the different field of pharmaceutical industry for the benefit of mankind.