Therna offers a generative AI platform that designs custom mRNA, siRNA, and antisense oligonucleotide sequences with programmable therapeutic properties. The system integrates deep regulatory RNA biology models with a lab‑in‑the‑loop workflow that synthesizes, validates, and feeds experimental results back to improve predictions, accelerating RNA therapeutic development from months to weeks.
Funding
$10M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
1OFounders
Product
Problem
Designing therapeutic RNA molecules such as mRNA, siRNA, and antisense oligonucleotides traditionally requires extensive experimental cycles and expert knowledge, leading to long development timelines and high costs. This slows progress toward treatments for diseases that are difficult to address with conventional small‑molecule or protein drugs.
Solution
Therna provides a generative AI platform that explores the RNA sequence space to create custom RNA therapeutics with desired functional properties. The system uses deep learning models trained on regulatory RNA biology to propose sequences for expression, silencing, or fine‑tuning of target genes. Proposed candidates are synthesized and experimentally validated in a closed “lab‑in‑the‑loop” workflow, and the resulting data are fed back to continuously improve the model’s predictive accuracy. By automating design and accelerating the iteration cycle, Therna enables rapid development of mRNA vaccines, protein‑replacement therapies, and gene‑silencing agents that were previously out of reach.
Target Audience
Primary customers are biotech and pharmaceutical companies developing RNA‑based therapeutics, as well as academic research groups seeking accelerated RNA design capabilities.
Features
- Generative AI engine that designs mRNA, siRNA, and antisense oligonucleotide sequences with programmable therapeutic attributes
- Integrated lab‑in‑the‑loop pipeline that validates AI‑generated candidates and retrains models on experimental results
- Predictive models informed by two decades of regulatory RNA biology research for accurate expression and silencing outcomes
- Ability to target specific regions of mRNA for optimal antisense or siRNA binding
- Scalable cloud‑based platform that accelerates design cycles from months to weeks