PURPOSE: The aim of this workshop is to introduce the audience to recent developments in cross-design synthesis of randomized and non-randomized data. Opportunities and disadvantages of conducting treatment comparisons mixing data from non-randomized and randomized trials will be highlighted and discussed in the context of timely health care decision-making. DESCRIPTION: Requirements for value-based dossiers has created demand to increase the availability of indirect pooled data of treatment comparisons in order to support reimbursement decisions. Research in meta-analysis and related techniques is ongoing to provide solutions for the increasingly complex evidence base of mixing data from multiple studies with often different designs and patient populations. However, multiple challenges remain, most prominent of which being the need to account for uncertainty when dealing with heterogeneous data across various dimensions. The wealth of complex methodologies can be confusing to the untrained eye as different types of evidence require alternative incorporation techniques. The audience will be presented with an overview of existing methods (naïve pooling techniques, design-adjusted evidence synthesis and propensity score weighting, Bayesian hierarchical models) to synthesize evidence from different data sources and study designs. The audience will be engaged to discuss opportunities and limitations of the proposed methods.