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Published on: November 12, 2019
Tracing the Technological Trajectory of CAR-T Cell Therapy in Cancer Treatment through Patent Analysis
Yilan Guan1, Yunting Liu1, Yuxuan Sun1
1School of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.
Introduction:
CAR-T technology represents a state-of-the-art approach in cancer treatment. This study constructs a multi-dimensional framework for analyzing the technological trajectory to comprehensively clarify the evolution trend of CAR-T technology in cancer treatment.
Methods:
Based on relevant patent data, three methodologies were applied: MPA (to identify dominant technological pathways), Word2Vec (to convert textual content into semantic vectors), and PCA-Kmeans (for dimensionality reduction and clustering). These methods facilitated the construction of one comprehensive technological trajectory and three supplementary trajectories.
Results:
The comprehensive technological trajectory exhibits a linear evolutionary trend. In its early stages, the focus was primarily on optimizing the CAR signal transduction domain. Recently, patent technologies have predominantly focused on T-cell modification and expansion, as well as the identification of multiple target antigens. Future research is expected to emphasize the co-expression of antigen targets with immune checkpoint inhibitors. Additionally, the supplementary technology trajectories suggest that refining the CAR-T regulatory mechanism, coexpressing GPX4 to enhance cellular anti-apoptotic capabilities, and expanding investigations into NKG2D targets may represent critical strategies for addressing the high costs and limited long-term persistence associated with CAR-T technology.
Discussion:
Systematic guidance is provided for formulating CAR-T technology patent strategies, and limitations in the current multi-dimensional analysis framework-such as data sources, indication analysis, and modeling methods-are highlighted, necessitating further optimization through integration with clinical data and advanced algorithms.
Conclusion:
A systematic technical synthesis is provided for both academic investigations and enterprise R&D, revealing the intrinsic patterns and potential advancements in the technological evolution of the field.
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