Sanofi needed to speed and improve early biologics and mRNA vaccine discovery, where scientists must search enormous candidate spaces, design complex multi-target molecules, improve oral biologic stability, and predict vaccine performance and patient responses earlier in R&D.
Reported impact
Sanofi reports faster and more precise biologics and vaccine discovery, broader use of AI across its portfolio, improved ability to optimize efficacy and manufacturing efficiency, and shorter R&D cycles that help move treatments and vaccines toward patients sooner.
Sanofi describes an in-house AI stack embedded across early R&D for biologics and mRNA vaccines. In biologics discovery, teams use AI and machine learning to screen large virtual panels, refine molecule designs in silico, and support target selection and engineering of complex trispecific antibodies for HIV and cancer. For mRNA work, Sanofi built CodonBERT, a large language model trained on millions of sequences, and mRNA-LM for full-length mRNA sequence modeling, to explore the vast design space and select promising vaccine sequences. RiboNN adds a deep-learning layer that predicts how efficiently ribosomes translate mRNA into protein. The company says these models are backed by deliberate experimental data generation and internal data infrastructure so the right biological data is produced, made available, and reused for model building. Scientists consume the model outputs to optimize efficacy, manufacturability, oral stability, and early response prediction, while the BioAIM program industrializes AI usage across the biologics portfolio.
Sanofi feeds large mRNA sequence collections, experimental data, and early biological signals into in-house models including CodonBERT, mRNA-LM, and RiboNN. These models score, generate, and refine candidate biologics and vaccine sequences in silico, and scientists use the outputs to choose targets, optimize molecule properties, improve manufacturability, and predict responses earlier in development.
"AI helps optimize both vaccine efficacy and manufacturing efficiency and can even predict human responses to vaccines by analyzing early biological signals after vaccination."
"At Sanofi, we are embedding AI to supercharge every stage of our R&D efforts."
"By empowering our scientists with AI-driven insights, we're pushing scientific boundaries, transforming weeks of research into hours, and ensuring faster delivery of life-changing treatments to patients."
"CodonBERT: A large language model for mRNA, trained on millions of sequences."
"RiboNN: A deep learning model that predicts how efficiently ribosomes will translate an mRNA sequence into a protein."
"The target selection and design of these highly engineered and very complex antibodies are now enabled by AI."
"screening large panels of candidates virtually and refining their design in silico."
"the number of biologics and vaccines using AI in their development at Sanofi has nearly doubled since 2019."
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