The timeline problem is brutal: traditional vaccine development takes 10–30 years from concept to deployment. When a new pathogen emerges—Ebola, Mpox, the next unknown threat—waiting a decade isn't an option. People die while we design.

There's a better way, and it's ready to use.

From Decades to Months

Computational vaccinology uses algorithms to predict which parts of a pathogen's genetic code will trigger the strongest human immune responses. This isn't theoretical anymore. Over the past two decades, validated tools have compressed vaccine design from years to months—and they work across diverse pathogens and manufacturing platforms.

For example, wwhen SARS-CoV-2 emerged, computational methods identified protective T-cell epitopes (immune-activating sequences) within 24 hours of the genome being published. Those epitopes (identified and validated by my group) remained 95% conserved across “variants of concern” until Omicron emerged, suggesting a blueprint for vaccines that could evolve with the virus rather than chase after it.

The same approach created:

• Pan-coronavirus vaccines effective against multiple       species, with 90% survival rates in animal challenge studies

• Universal flu vaccine candidates spanning 13 different influenza subtypes

• Mpox vaccines that provided 100% protection against challenge in pre-clinical models.

  
  

Why This Matters for Equitable Access

Computational design democratizes vaccine development. It works with any manufacturing platform: mRNA, peptides, viral vectors, outer membrane vesicles. That flexibility is crucial for low- and middle-income countries (LMICs) that may lack mRNA infrastructure but have capacity for protein production. Even better, new mRNA manufacturing sites have been built in LMIC, thanks to the collaboration of the Gates foundation, WHO and mRNA vaccine experts.

This technology is ready. We don’t need to wait for “AI models to mature”. These human-informed algorithms have already been validated in multiple collaborative, NIH-funded studies. And while we are “platform agnostic”, the development of LMIC mRNA manufacturing means that novel, computationally designed vaccines can be manufactured, tested, and deployed rapidly where they are needed most. Like the Mpox vaccine that we are developing with Afrigen. That's the promise of equitable pandemic response.

The Challenge: Integration

Our vaccine design tools are ready. They have been validated across multiple pathogens and human immune systems. What's missing isn't the capability—it's the integration into pandemic preparedness systems. We’ve been pushing these concepts for more than a decade.  

The barriers? Yes, regulatory agencies haven't yet established standard pathways for evaluating multi-epitope vaccines. But more important, pandemic response frameworks haven't yet woven computational design into their protocols.

These are solvable problems. But they require action now, not after the next crisis. And partnership with fearless scientists that want to make more safer, more effective vaccines.

The Opportunity

At EVA Tx, we currently have the capacity to predict epitopes that work, and we are ready to collaborate with like-minded groups to synthesize test, and manufacture vaccines within months. We have proof: SARS-CoV-2, influenza, Mpox—are vaccines that we designed that showed protective efficacy in preclinical models.

The question is whether the infrastructure—regulatory, manufacturing, policy—can catch up to the science.

For a world facing more pandemic threats than ever, the answer needs to be yes. And it needs to be now.

Advancing The Solution

The tools that we have access to —EpiMatrix, JanusMatrix, ClustiMer, and the iVAX platform—were developed over the past 28 years through research at EpiVax. At EVA Therapeutics, we're building on that foundation to accelerate vaccine design for pathogens threatening low- and middle-income countries and pandemic preparedness.

We're using these validated computational approaches to collaborate with partners across the globe—designing vaccines for emerging threats, supporting LMIC-focused pathogen research, and demonstrating that rational, computationally-guided vaccine development can deliver equitable solutions faster.

This isn't about replacing human expertise with AI. It's about using tools that have already demonstrated that they can compress timelines, so that the next emerging pathogen doesn't get a 30-year head start.

Now is the time: Reach out to us!

If you work on pandemic preparedness, outbreak response, neglected disease vaccines, or global health equity, we'd welcome a conversation about how computational vaccinology can accelerate your work. Contact us now.