Labsent
The AI-driven research engine for scientific literature synthesis and lab protocol automation.
Accelerating precision medicine through AI-powered metagenomics and novel gene-editing systems.
Metagenomi is a precision genetic medicines company that utilizes an AI-integrated metagenomics discovery engine to identify and develop next-generation genome editing tools. By 2026, the company has solidified its position in the market by moving beyond standard CRISPR-Cas9 limitations, offering a proprietary library of billions of microbial genomes. Their technical architecture involves high-throughput screening of non-culturable organisms combined with deep learning models that predict the structural and functional properties of novel nucleases. This allows for the discovery of ultra-compact editors capable of being delivered via highly efficient vectors like AAV or LNPs. Metagenomi's platform acts as a vertically integrated R&D stack, providing partners with modular components for base editing, prime editing, and large-scale genome integration. In the 2026 landscape, Metagenomi serves as a critical infrastructure layer for pharmaceutical companies looking to bypass existing patent thickets while achieving higher specificity and lower off-target profiles in therapeutic applications.
A proprietary AI platform that mines billions of microbial genomes to find novel CRISPR-associated systems beyond Cas9/Cas12.
The AI-driven research engine for scientific literature synthesis and lab protocol automation.
Accelerating precision medicine through single-cell genomics and machine learning-driven drug discovery.
AI-driven neoantigen discovery and self-amplifying mRNA vaccines for precision oncology and infectious diseases.
AI-Powered Medical Insights Platform for Life Sciences and Medical Affairs.
Verified feedback from the global deployment network.
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Engineered nucleases (<1000 amino acids) designed for efficient delivery via Adeno-Associated Virus (AAV) vectors.
System for site-specific integration of large DNA sequences without double-strand breaks.
Deep learning models that predict and expand the Protospacer Adjacent Motif (PAM) requirements for editors.
Closed-loop system where experimental data from the wet lab retrains protein design models.
Deaminase-fused editors designed for single-nucleotide changes with zero detectable off-targets.
Predicts 3D protein structures of uncharacterized microbes to identify functional active sites.
Existing CRISPR tools are too large for standard delivery vehicles.
Registry Updated:2/7/2026
Verify knockdown efficiency
High off-target effects during CAR-T manufacturing.
Standard Cas9 is restricted by heavy IP and licensing costs.