Evaluation and Forecasting of siRNA Delivery Technologies: An analysis of Hierarchical Decision Model based on Patent Data

Small interfering RNA (siRNA) represents a transformative modality in next-generation therapeutics, yet challenges in delivery efficiency still limit its clinical translation. Systematic evaluation tools are needed to reveal technological progress in this area. Given the innovation momentum inherent in patents, this study develops a patent-based evaluation model for siRNA delivery technologies from a technology management perspective. By integrating the Hierarchical Decision Model (HDM) with patent landscape analysis, the model incorporates 15 multidimensional criteria across technological, commercial, and legal perspectives, with the commercial perspective assigned the greatest weight (41%), followed by technical (32%) and legal (27%) perspectives. A large-scale dataset comprising 20,319 siRNA delivery-related patent documents was quantitatively assessed using this model. The results reveal that high-value patents are primarily concentrated in lipid-based carriers and ligand-siRNA conjugates, with firms such as Alnylam and Arbutus emerging as dominant innovation leaders. Furthermore, the analysis highlights that therapeutic indication, assignee's technological accumulation, technological impact, and drug delivery method are key drivers of patent value. Overall, the proposed model supports strategic decision-making in patent portfolio management and technology forecasting by identifying high-value innovations.