Terrainbiosciences

This startup offers next-day plasmid sequencing services with integrated bioinformatics analysis, enabling faster and more cost-effective bioscience research. Their machine learning-driven platform provides high-throughput sequencing and robust data analysis for researchers.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Developing RNA medicines is a complex process, with the nucleotide sequence significantly impacting therapeutic performance, manufacturability, stability, expression, and immunogenicity. Traditional codon optimization tools often isolate the open reading frame (ORF), neglecting the interplay between different mRNA regions and their collective impact on therapeutic outcomes.

Solution

Terrain Bio offers an AI-driven platform for comprehensive mRNA sequence design and optimization, enabling faster and more predictable development of RNA therapeutics. Their approach considers the entire mRNA molecule, including the 5' UTR, coding sequence, 3' UTR, and poly(A) tail, to optimize for manufacturability, stability, expression quality, immunogenicity, durability, and targetability. By leveraging physics-based modeling and active learning, Terrain Bio helps researchers navigate RNA sequence space, identify promising candidates, and fine-tune sequences to meet specific therapeutic objectives. The platform integrates sequence design with rapid, innovative manufacturing, delivering high-quality mRNA at microgram to gram scale.

Target Audience

Terrain Bio serves biopharma companies and researchers involved in developing RNA therapeutics, including vaccines, gene therapies, and protein replacement therapies.

Features

AI/ML design suite that optimizes mRNA sequences for manufacturability, stability, expression quality, immunogenicity, durability, and targetability
Comprehensive Design Review process to align sequence design with specific therapeutic goals and biological context
Physics-based modeling to simulate and improve sequences, even with limited functional data
Active learning to intelligently nominate new sequences for testing based on real-world performance data
Design for both therapeutic performance and manufacturability, avoiding elements that can create manufacturing challenges
Rapid mRNA manufacturing capabilities, delivering high-performing sequences in weeks
Catalog mRNA standards for quick experimentation