Continuous evaluation of drug safety is needed following approval to determine adverse
events (AEs) in patient populations with diverse backgrounds. Spontaneous reporting …

Data science is an interdisciplinary field that extracts knowledge and insights from many
structural and unstructured data, using scientific methods, data mining techniques, machine …

Clinical data describing the phenotypes and treatment of patients represents an underused
data source that has much greater research potential than is currently realized. Mining of …

Adverse drug events remain a leading cause of morbidity and mortality around the world.
Many adverse events are not detected during clinical trials before a drug receives approval …

The growing healthcare industry is generating a large volume of useful data on patient
demographics, treatment plans, payment, and insurance coverage—attracting the attention …

Abstract The US Food and Drug Administration (FDA) Adverse Event Reporting System
(FAERS, formerly AERS) is a database that contains information on adverse event and …

An important goal of the health system is to identify new adverse drug events (ADEs) in the
postapproval period. Data‐mining methods that can transform data into meaningful …

Objective Adverse drug reaction (ADR) is one of the major causes of failure in drug
development. Severe ADRs that go undetected until the post-marketing phase of a drug …

The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance,
which provides effective and safe co-prescriptions of multiple drugs. Since laboratory …

Therapeutic activities of drugs are often influenced by co-administration of drugs that may
cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and …