It has become more common recently for some innovative drugs to be approved with little or no randomized controlled trial (RCT) evidence, such as those for rare diseases with clear unmet treatment needs. However, given the resulting evidence gaps and uncertainty without RCT evidence, this presents challenges for health technology assessment (HTA) and for payers in making initial value assessments and coverage decisions. Can these gaps be alleviated prospectively in the trial program or real-world data collection planning? If not, what other approaches might be used prior to, instead of, to help inform further evidence development, outcomes-based agreements, or similar arrangements? This plenary will explore several methodological approaches that can help inform those initial decisions. The range of potential methods includes sequential trial planning and quasi-experimental approaches, scenario and hierarchical modeling, causal inference, and value of information techniques, among others. Presentations will include actual applications of those methods.