Causality assessment represents a critical analytical process in pharmacovigilance, requiring investigators and sponsors to evaluate whether observed adverse events are attributable to the investigational product, underlying disease, concomitant medications, or other factors. This determination influences regulatory reporting obligations, risk-benefit evaluations, and ultimately the decisions made about product development and labeling. While establishing definitive causality is often impossible, standardized approaches enable consistent and defensible assessments.

Several factors inform causality assessment, including temporal relationship between drug exposure and event onset, biological plausibility based on known pharmacological mechanisms, the presence of alternative explanations, results of dechallenge and rechallenge when available, and the pattern of similar events across the trial population. Some assessment systems use categorical ratings such as "definite," "probable," "possible," "unlikely," and "unrelated," while others employ numerical algorithms. The choice of assessment methodology should be prespecified in the protocol or pharmacovigilance plan to ensure consistency.

The investigator bears primary responsibility for providing a causality assessment for each adverse event, drawing upon their clinical expertise and knowledge of the participant's medical history. However, the sponsor also independently evaluates causality, particularly for serious events, and may reach a different conclusion than the investigator. Regulatory guidelines specify that if either the investigator or sponsor considers an event possibly related to the investigational product, it should be treated as such for reporting purposes. This conservative approach ensures that potential safety signals are not missed due to overly restrictive causality judgments.