Pharmacovigilance in the Digital Age: Using Big Data and Artificial Intelligence to Improve Drug Safety

Authors

Pharmacovigilance, Big Data, Artificial Intelligence, Drug Safety, Adverse Drug Reactions, Machine Learning, Predictive Modeling

Pharmacovigilance is the science and activities related to the detection, assessment,

understanding, and prevention of adverse effects or any other drug-related problems. The

advancement of digital technologies, particularly Big Data and Artificial Intelligence (AI),

has introduced new opportunities to enhance pharmacovigilance activities. This paper

examines the role of Big Data and AI in improving drug safety by enabling more efficient

and accurate detection of adverse drug reactions (ADRs), predictive modeling, and real-time

monitoring. The integration of these technologies into pharmacovigilance systems has the

potential to revolutionize the way drug safety is managed, enhancing both the safety of

patients and the efficiency of regulatory agencies. The paper also addresses challenges such

as data privacy concerns, the need for standardization, and the ethical implications of using

AI in pharmacovigilance.