Design Early or Your mRNA Program is Doomed from the Start

TLDR: We see lots of companies turn to mRNA design as an attempt to rescue their program. While this can work, using design early reduces risk, accelerates timelines, and unlocks better outcomes.

Bad news upfront: mRNA sequence design is still more art than science. And since most companies don't have the expert knowledge to perform sequence optimization, they turn to subpar tools for help optimizing their sequence. 

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Save My Program, Please!

We see this pattern a lot: a team is developing a new drug. They have a promising protein. They find a published sequence. They improve it slightly using off-the-shelf optimization tools. They send it to a vendor (who might optimize it further but only for manufacturability, not therapeutic performance). They cross their fingers and hope for the best. And the results? Just OK performance, not stellar, definitely not likely to make an impact on patient health or the company’s bottom line, but maybe good enough to submit to IND.

The team has spent months (and their budget) pursuing suboptimal designs before realizing they need something better. Then they’re in rescue mode. Time is ticking. The budget is evaporating. The conversation shifts from “Let’s build the best possible therapeutic.” to “Can we fix what we have?”

This reactive approach is expensive, risky, and unnecessary!

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The conversation shifts…to "can you fix what we have?" [Author’s note: Yes, we can.]

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Be Proactive: Design First

mRNA design isn't just about performance optimization—it's about risk mitigation.

As you translate from primary cells to mouse models to clinical trials, each step amplifies sequence-dependent effects. A sequence that works adequately in vitro might fail spectacularly in vivo. A sequence originally optimized for one cell type might be completely wrong for your target tissue.

When you optimize your mRNA design for expression, stability, specificity, immunogenicity, and manufacturability at the start, you reduce the risk of failure as you move your drug candidate through the development pipeline. You're not just making better molecules—you're doing smarter science.

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The Active Learning Advantage

The most successful mRNA programs don't rely on single-shot optimization. They embrace active learning: use a SOTA model to design a set of optimized sequences → test them → observe their performance and feed the data back into the model → design a new, further optimized set of sequences to test.

Each round teaches you something new about the sequence-performance relationship in your specific context. The companies and scientists willing to invest in multiple design cycles consistently achieve better outcomes than those hoping to get lucky on the first try.

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Better Late than Never

The earlier in your program, the more degrees of freedom you have. Once you've committed to GMP manufacturing, filed your IND, or locked in your clinical sequence, design changes become exponentially more expensive.

But even if you're deep in your program, it's not too late to think strategically about design. Some of our most successful partnerships have been "rescue operations" where thoughtful sequence optimization saved programs that were struggling with expression, stability, or manufacturing challenges.

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Companies that treat design as a strategic discipline…have an advantage over those still playing sequence roulette.

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Parting Thoughts

mRNA is new enough that most companies are still learning how to think about sequence design. The companies that treat design as a necessary strategic step in their drug development—not an afterthought—will have an advantage over those still playing sequence roulette.

The question isn't whether sequence design affects your program's success. It's whether you're making those design choices intentionally or leaving them to chance.

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What's Your Design Strategy?

Before you commit to your next sequence, ask yourself:

• Have you optimized for your specific therapeutic context?
• Are you designing for your target tissue and delivery method?
• Have you considered the trade-offs between different performance attributes?
• Do you have a plan for iterative optimization?

If the answer to any of these is "no," you might be considering design too late in your program.

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Ready to think strategically about mRNA design? Let’s discuss your challenges.