AI-powered design accelerates the development of mRNA therapeutics

Zhengwei Liu; Yizhou Dong

doi:10.1038/s41589-025-02074-0

AI-powered design accelerates the development of mRNA therapeutics

Zhengwei Liu
, Yizhou Dong

Research output: Contribution to journal › Comment/debate

2 Scopus citations

Abstract

mRNA has emerged as an important class of therapeutic molecules. Now, an artificial intelligence (AI)-driven framework, which can design mRNA sequences with enhanced stability and translational efficiency, has been reported. This method for designing mRNA sequences is known as ‘generative models for RNA’ (GEMORNA) and could help to design more effective mRNA-based treatments.

Original language	English
Pages (from-to)	15-16
Number of pages	2
Journal	Nature Chemical Biology
Volume	22
Issue number	1
DOIs	https://doi.org/10.1038/s41589-025-02074-0
State	Published - Jan 2026

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title = "AI-powered design accelerates the development of mRNA therapeutics",

abstract = "mRNA has emerged as an important class of therapeutic molecules. Now, an artificial intelligence (AI)-driven framework, which can design mRNA sequences with enhanced stability and translational efficiency, has been reported. This method for designing mRNA sequences is known as {\textquoteleft}generative models for RNA{\textquoteright} (GEMORNA) and could help to design more effective mRNA-based treatments.",

author = "Zhengwei Liu and Yizhou Dong",

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year = "2026",

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AU - Dong, Yizhou

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N2 - mRNA has emerged as an important class of therapeutic molecules. Now, an artificial intelligence (AI)-driven framework, which can design mRNA sequences with enhanced stability and translational efficiency, has been reported. This method for designing mRNA sequences is known as ‘generative models for RNA’ (GEMORNA) and could help to design more effective mRNA-based treatments.

AB - mRNA has emerged as an important class of therapeutic molecules. Now, an artificial intelligence (AI)-driven framework, which can design mRNA sequences with enhanced stability and translational efficiency, has been reported. This method for designing mRNA sequences is known as ‘generative models for RNA’ (GEMORNA) and could help to design more effective mRNA-based treatments.

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DO - 10.1038/s41589-025-02074-0

M3 - Comment/debate

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SP - 15

EP - 16

JO - Nature Chemical Biology

JF - Nature Chemical Biology

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AI-powered design accelerates the development of mRNA therapeutics

Abstract

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