Abstract LB113: Accelerating CAR T-cell therapy research with two AI-driven tools for literature and patent landscape review

Abstract AI-based tools not only expedite translational research but also enable real-time comparison of developed therapies and published datasets. These analytical modules aid researchers in formulating translational frameworks and navigating Intellectual Property (IP) protection. In this study, we leverage 23Strands' BiblioEngine and Neural Hinge’s Cool.AF solutions to analyze the clinical literature and patent landscape of Multiple Myeloma CAR-T therapies. Cool.AF's dynamic IP mapping is vital for identifying trends, IP conflicts, and whitespace opportunities, providing a competitive edge in translational research. The primary objective was to compare key biomarkers, identify emerging trends, and project clinical adoption trajectories to aid in structuring clinical trials and filing patents. By integrating these tools, we efficiently processed and interpreted vast scholarly articles and patents, with a focus on navigating the complex IP landscape. This enabled us to safeguard against IP infringement while uncovering innovative opportunities. Schematic outputs from BiblioEngine and Cool.AF facilitate faster and more advanced textual analytics, allowing us to extract meaningful patterns from publicly available data. BiblioEngine and Cool.AF’s AI-driven algorithms enabled us to assimilate data on CAR-T constructs, manufacturing processes, and therapeutic applications within hours. By identifying critical IP relationships and emerging trends it allows researchers to make informed, data-backed decisions with precision. Methodology: Using an interactive search engine interface, the integrated AI tools enabled the following analyses: Emerging Therapeutic Approaches: We identified novel strategies and gaps in Myeloma CAR-T therapies, highlighting areas for innovation without IP risks. Collaborative Research Networks: We uncovered significant collaboration among researchers and identified synergies for interdisciplinary cooperation. Intellectual Property Landscape: Our patent analysis revealed previously patented therapeutic applications and specifications, offering insights into IP protection and success factors. By integrating Cool.AF with BiblioEngine, our research teams accessed real-time global patent data from USPTO, the European Union, and India, scaling analysis from individual researchers to large institutions. This integration provided actionable insights, enabling a comprehensive view of the CAR T-cell therapy landscape. Combining patent intelligence with bibliometric analysis, we not only navigated the existing patent landscape but also created new pathways for innovation, ensuring faster and more accurate insights into IP and safeguarding current and future research. Citation Format: Chirantan Bose, Suraj Chiraniya, Mark Grosser, Rahul Bose, Lin Hua, Jesus Shreshtha, Victoria Bicknell, Ashish Joshi, Vashistha Maniar, Smitaa Srivastava, Manisha Kohli. Accelerating CAR T-cell therapy research with two AI-driven tools for literature and patent landscape review [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB113.