KAIJU Bio is a software-enabled biotechnology company developing an AI-guided platform for discovering programmable nucleic acid-based targeting systems and precision molecular delivery technologies. The platform integrates model-guided sequence design, scalable synthesis, human cell functional screening, and experimental feedback loops to optimize recognition, delivery, and biological context in tandem. Its delivery work applies AI-enabled screening at massive scale to explore peptide nanoparticle designs for complex in vivo environments.
Funding
Funding not disclosed
Founders
Product
Problem
Conventional therapeutic modalities struggle to address biological targets that require precise molecular recognition and delivery in complex in vivo environments. Existing approaches often optimize single components in isolation, failing to account for how targeting, formulation, biodistribution, and biological context interact, which limits the development of effective in vivo medicines.
Solution
KAIJU Bio is building a software-enabled biotechnology platform for discovering programmable nucleic acid-based targeting systems and precision molecular delivery technologies. The platform operates on a closed-loop design-build-screen-learn cycle, connecting model-guided sequence design with experimental feedback so recognition, delivery, and biological context can be optimized together. It generates sequence-defined targeting systems across vast design spaces, connects nucleic acid design with scalable synthesis workflows, and measures targeting and delivery behavior in disease-relevant human cellular contexts through parallelized multiplexed readouts. Functional data is then used to refine candidate selection and improve subsequent design cycles, enabling the development of next-generation in vivo medicines.
Target Audience
Primary customers are biotechnology and pharmaceutical companies developing in vivo nucleic acid therapeutics, as well as research organizations focused on precision molecular delivery and programmable targeting systems for difficult biological targets.
Features
- Model-guided generation of sequence-defined targeting systems across vast design spaces exploring recognition, delivery, and biological context in physiologically relevant systems
- Scalable design and synthesis workflows connecting nucleic acid design with ultra-large experimental search spaces informed by human biology
- Human cell functional screening that measures targeting and delivery behavior in disease-relevant contexts through parallelized multiplexed readouts
- Experimental feedback loops that use functional data to refine candidate selection and improve subsequent design cycles
- AI-enabled screening at massive scale to explore broad distributions of peptide nanoparticle designs and molecular delivery behaviors
- Distributional approach designed to evaluate how targeting, formulation, biodistribution, and biological context interact across multiplexed experimental systems