Introduction

As we reach the end of 2025, we are looking back at some of the major moments in RNA science and innovation throughout the year. From breakthroughs in clinical trials, to the rise of AI models for RNA research, to the first successful personalized gene editing treatment, 2025 was a stellar year for RNA. We are excited to share some of the year’s most notable highlights in this eBlog. 

Continued advancements in RNA medicines and therapeutics

This year saw numerous advancements in developing RNA medicines and therapeutics. Here are just a few of these exciting advancements. 

• Moderna: The FDA approved Moderna’s RSV vaccine, mRESVIA, for adults 18–59 who are at increased risk for respiratory syncytial virus (RSV). The vaccine became available to this group, alongside those 60 years and over, this respiratory viral season. 
• HDT-Bio: The FDA cleared HDT-Bio's Investigational New Drug application for the company’s HDT-321 vaccine against Crimean-Congo Hemorrhagic Fever. This is a significant step towards protecting public health from tick-borne illness. 
• Baby KJ: The first successful personalized gene editing treatment occurred at the Children’s Hospital of Philadelphia. Over several months, physicians gave the infant KJ, who was diagnosed with severe CPS1 deficiency, base editing therapy via lipid nanoparticles. Under close watch, baby KJ has not faced any major side effects and is healthily growing. 

Improvements in the stability of mRNA

One of the biggest challenges of mRNA drugs is keeping the drug substance stable from synthesis to protein production. Fortunately, there was a lot of research this year into the issue. 

• Ma et al. explored how optimizing mRNA sequences can improve stability, finding that adding AU-rich elements to the 3’ UTR made mRNA more stable. 
• Snell et al. discovered that the RNA-binding proteins (RBPs) ZC3H7A and ZC3H7B preferentially bind to non-optimal A/U3 codons, which makes the mRNA less stable. Depleting these RBPs reduces the expression of non-optimal codons, improving stability. 
• In their review, O’Leary et al. explained that circular RNA (circRNA) is more stable and has a longer half-life than linear mRNA. These characteristics mean that circRNA-encoded antigens could have a longer and more pronounced protein expression in vaccines. 
• Cao et al. reviewed many chemical modifications and delivery options for mRNA stability. One consideration was that scientists may be able to use less self-amplifying RNA (saRNA) than the required amount of mRNA to achieve the same or even more protein expression. 
• Wang et al. discussed how chemical modifications can make different types of RNA more stable. They proposed that alterations to the backbone and sugar of small RNAs, base changes to mRNA and other translatable RNAs, and backbone modifications to guide RNA can help improve RNA stability. 

Increased prominence of AI in RNA research

The use and accessibility of AI models for RNA therapeutics expanded throughout the year. From locating where miRNAs bind at a single-nucleotide scale to determining RNA secondary structures, AI can be used in almost every aspect of creating RNA medicines. 

• Li et al. developed mRNA-LM, a small language model that sequences the entire mRNA sequence, including UTRs and CDS. They used three separate models for UTRs and coding sequences, leading to an effective model for predicting translation and stability. 
• Qu et al. developed CRISPR-GPT, a large language model to automate and improve every step of CRISPR gene editing, from experiment designing to data analysis. 
• Kanuparthi et al. developed REPRESS, a deep learning model that can identify non-canonical miRNA binding sites and predict mRNA degradation. They trained REPRESS with miRNA binding data from miR-eCLIP. 

Innovation highlights at Eclipsebio

• This year we launched eVERSE, the first comprehensive portfolio of multidimensional RNA datasets for AI model training. Using Eclipsebio sequencing services, eVERSE offers high-quality datasets to better develop RNA therapeutics and train AI models. 
• We began offering nanopore sequencing this year, providing our partners with long-read data of their RNAs to measure the length of poly(A) tails and characterize RNA fragments. 

Looking forward to 2026

As the field of RNA therapeutics and medicines continues to advance, here are some research topics we predict to grow. 

• The use of AI in RNA drug development will continue to increase. As RNA datasets to train AI, such as eVERSE, become more accessible, researchers will be able to fine tune gene editing therapies and RNA therapeutics.  
• Personalized cancer vaccines will become more common. Combined with a rise in AI models, RNA research is in a prime position to rapidly advance gene editing technologies to develop personalized cancer treatments. 
• More scientists will study the “dark genome,” or sections of DNA that do not code for traditional proteins. Preliminary research suggests that small proteins, such as micropeptides, in these DNA sections impact health more than previously thought. Assays that can code for these molecules, such as eRibo Pro, will be vital for exploring the dark genome. 

From everyone at Eclipsebio, thank you to our partners and the larger RNA community for an incredible 2025. We look forward to supporting you in 2026.