A safety signal represents information that raises a hypothesis about a potential risk associated with an investigational or marketed product, warranting further investigation to determine whether a true causal relationship exists. Signals may emerge from various sources, including disproportionate adverse event reporting in clinical trials, statistical patterns identified through data mining of safety databases, published case reports or epidemiological studies, or pharmacological considerations suggesting biological plausibility for an adverse effect.

Signal detection in clinical development involves both prospective and retrospective approaches. Prospective methods include prespecified safety monitoring plans that define thresholds for adverse event frequencies and stopping rules for unacceptable safety findings. Retrospective approaches analyze accumulating safety data using statistical techniques such as disproportionality analysis, which compares the observed frequency of drug-event combinations against expected frequencies. The Data Safety Monitoring Board plays a critical role in signal evaluation, providing independent expert assessment of emerging safety information.

Not every potential signal represents a true risk. Signal validation involves comprehensive evaluation to distinguish genuine safety concerns from statistical noise, confounding, or reporting artifacts. This evaluation considers factors such as the strength of the association, consistency across different data sources, temporal relationship, biological plausibility, and the quality of the underlying data. Validated signals proceed to signal prioritization and assessment, ultimately informing risk management decisions that may include protocol amendments, labeling changes, or in severe cases, trial termination or product withdrawal.