Application of Machine Learning and Big data Analytics in Pharmacovigilance and Drug Safety

Abstract

Machine learning technique is revolutionizing in all stages of drug discovery and developments starting from drug design, pivotal clinical trials to clinical practice. Application of machine learning techniques and big data analytics for looking upon the unintended effects of new or commonly prescribed medicines would enhance new technical approaches to generate and test ‘signals' related to drug safety. It would craft as a path finder for pharmacovigilance resources, time, and skills for transforming the efforts from a volume-based focus to a value-based focus. This article provides a comprehensive overview of the current scenario of pharmacovigilance programme, the importance of real world data, and machine learning analytics in the conduct of pharmacovigilance for better reproducibility and reliability. Precise and in-depth evaluation and prediction of drug safety database using machine learning techniques were also discussed in this paper. The utilization of these techniques in pharmacovigilance programme will improve its accuracy and reproducibility, and will boost this drug safety surveillance system's role as a pillar in patient safety.