Fully Automated mRNA Mapping for MS/MS‑Based PQA Analysis

May 20, 2026

mRNA therapeutics are a rapidly expanding modality in vaccines and personalized medicine, but their large size, structural heterogeneity, and critical product quality attributes, such as poly(A) tails and 5′ cap modifications, create significant analytical challenges for accurate characterization and quality control. Reliable characterization of these features is therefore essential to ensure consistent product quality and enable scalable mRNA analysis workflows. 

This poster presents a fully automated MS‑based mapping workflow in Genedata Expressionist^®, enabling candidate generation and sequence mapping from MS1 and MS/MS data together with specialized analysis of poly(A) tail length and 5′ cap variants. You will learn how automated candidate generation and robust data processing improve detection and characterization of key mRNA product quality attributes, reduce manual review effort, and increase confidence in sequence validation. It also demonstrates how integrated, traceable workflows enable scalable mRNA analysis and provide a robust foundation for downstream machine learning and AI applications. Designed for scientists working in RNA analytics and LC‑MS characterization workflows.