Background While clinical trials are considered the gold standard for detecting adverse
events, often these trials are not sufficiently powered to detect difficult to observe adverse …

We improved a previous pharmacological target adverse‐event (TAE) profile model to
predict adverse events (AEs) on US Food and Drug Administration (FDA) drug labels at the …

Motivation: Unexpected drug activities derived from off-targets are usually undesired and
harmful; however, they can occasionally be beneficial for different therapeutic indications …

Objective Currently, 90% of clinical drug development fails, where 30% of these failures are
due to clinical toxicity. The current extensive animal toxicity studies are not predictive of …

The rapid evolution of large biological, pharmacological, and chemical databases has led to
optimism that such data resources can be leveraged for prediction of drug action based on …

Background Studies of toxicity and unintended side effects can lead to improved drug safety
and efficacy. One promising form of study comes from molecular systems biology in the form …

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to
the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the …

Clinical trials can fail to detect rare adverse events (AEs). We assessed the ability of
pharmacological target adverse‐event (TAE) profiles to predict AEs on US Food and Drug …

Safety assessment and monitoring are critical throughout the life cycle of drug development.
The evaluation of safety information, specifically adverse events, from clinical trials has …

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 …