The call for program‐level reviews of accumulating safety data, including from ongoing studies, provides an opportunity to leverage the scientific expertise and medical judgment of safety management teams. A multidisciplinary team, regularly reviewing aggregate safety data throughout the development program, is vital not only for early signal detection but also for generating a better understanding of the accumulating data and context needed for decreasing false alarms.
Ascertainment of a causal association employs evaluation of factors beyond quantitative analysis to which clinicians can best contribute; however, statistical methods impart objectivity to the exercise. While medical experts can identify the most important clinical questions, statisticians are needed to frame the context of the analyses. Consequently, safety monitoring during clinical development requires a partnership between clinical and statistical scientists
- A thorough understanding of existing safety data, the target population and relevant subpopulations, and risk factors for particular events, as well as the product’s mechanism of action, concomitant medications, and preclinical findings
- A meta-analytic review should routinely be part of the process in order to more readily detect differences in event rates
A special challenge is applying appropriate statistical techniques with a safety mindset, medical judgment within a quantitative framework (learning and decision-making), as opposed to strict statistical inference (testing and confirming). Safety data scientists should facilitate development of quantitative frameworks for safety topics of interest, so that the multi-disciplinary Safety Management Team (SMT) can assess the available evidence and gain clinical as well as statistical understanding of the safety profile.