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Machine learning-guided ligation fragment design for efficient siRNA synthesis
Featured at TIDES US 2025
The rising demand for siRNA therapeutics highlights the need for scalable and efficient manufacturing solutions. Engineered dsRNA ligases enable high-yield assembly of siRNA from short RNA fragments, with performance influenced by both ligase selection and fragment design. We introduce an AI/ML-guided approach to optimize fragment design, significantly improving ligation efficiency and enabling one-pot assembly with over 90% success. This strategy minimizes the need for extensive ligase screening, streamlining the path to scalable siRNA production.
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