Background: The immediate automatic systemic monitoring and reporting of
adverse drug reactions, improving the efficacy is the utmost need of the medical informatics
community. The venturing of advanced digital technologies into the health sector has
opened new avenues for rapid monitoring. In recent years, data shared through social media,
mobile apps, and other social websites has increased manifolds requiring data mining
Objective: The objective of this report is to highlight the role of advanced technologies together
with the traditional methods to proactively aid in the early detection of adverse
drug reactions concerned with drug safety and pharmacovigilance.
Methods: A thorough search was conducted on papers and patents regarding pharmacovigilance.
All articles with respect to the relevant subject were explored and mined
from public repositories such as Pubmed, Google Scholar, Springer, ScienceDirect (Elsevier),
Web of Science, etc.
Results: The European Union’s Innovative Medicines Initiative WEB-RADR project has
emphasized the development of mobile applications and social media data for reporting
adverse effects. Only relevant data has to be captured through the data mining algorithms
(DMAs) as it plays an important role in timely prediction of risk with high accuracy using
two popular approaches; the frequentist and Bayesian approach. Pharmacovigilance
at the pre-marketing stage is useful for the prediction of adverse drug reactions in the early
developmental stage of a drug. Later, post-marketing safety reports and clinical data reports
are important to be monitored through electronic health records, prescription-event
monitoring, spontaneous reporting databases, etc.
Conclusion: The advanced technologies supplemented with traditional technologies are
the need of the hour for evaluating a product’s risk profile and reducing risk in population
especially with comorbid conditions and on concomitant medications.