As the RNA therapeutics landscape grows, the need for efficient and effective development has never been greater. Timely, high-quality development pairs effective therapeutic design with thorough analytics, creating a Design, Make, Test cycle that can simultaneously develop therapeutics and improve AI data. Using this method, developers can leverage knowledge and insights throughout the cycle to quickly propel RNA therapeutics from bench to bedside. 

Step 1: Design 

Designing a sequence is the first step of developing any RNA therapeutic, and prioritizing a high-quality design at the beginning of therapeutic development will make the rest of the process easier. Developers can design RNA sequences based on data from previous designs using advanced learning models. 

Terrain Bio, now part of Eclipsebio, has developed advanced learning models to design high-quality RNA sequences. The pairing of these learning models with Eclipsebio’s eVERSE AI-ready datasets, enables biopharmas and biotechs to obtain RNA designs that outperform existing approaches for both potency and stability.

Step 2: Make 

After designing the RNA sequence, it still needs to be tested in the real world. With our rapid prototyping capabilities, we can quickly manufacture the novel RNA sequences for robust validation with our eMERGE analytics platform. Our proprietary manufacturing protocols enable the the synthesis of technically challenging RNAs, including linear mRNAs longer than 5 kb.

In addition to our own manufacturing capabilities for preclinical prototyping, we can also help you identify the ideal scale-up vendor from our global network of manufacturing partners.

Step 3: Test 

After manufacturing the initial RNA prototypes, they then need to be tested to identify the optimal candidate to move forward with IND filings.  We pair our AI-powered designs with empirical, sequencing-based analytics to provide comprehensive evaluations of each drug candidate through our eMERGE platform. Example insights from our platform include the determination of dsRNA sources, assessment of RNA secondary structure,  and measurements of ribosome dynamics. Included with each candidate validation is a comprehensive insights report to help you interpret the data and make actionable decisions for how to proceed.

Repeating the cycle to teach AI 

Designing, prototyping, and validating RNA are all important processes in themselves, but they are most powerful when used together. Our unified approach enables us to gather data for every step of the Design, Make, Test cycle enabling an active lab-in-the-loop approach for improving initial RNA sequence designs. 

For example, imagine a developer has designed an RNA sequence based on available AI data, which they then prototype and validate. During analysis, they find that the RNA is prone to hydrolysis and the RNA’s secondary structure allows for dsRNA formation in several regions. We feed this data back to our partner-specific AI models to guide improvements to increase therapeutic efficacy.

Design, Make, Test cycle at Eclipsebio 

At Eclipsebio, we complete this entire process in-house enabling the development of clinic-ready drugs in less than a year. Our AI-guided design capabilities create RNA sequences optimized for manufacturing and efficacy, and our sequencing-based analytics validate manufactured sequences.

Ready to discover how our unified platform can accelerate and derisk your drug development programs? Contact Eclipsebio to get started. 

Want to learn more about Eclipsebio’s acquisition of Terrain Bio? Read the press release.