Platform 04 · Making cell therapy as reliable as semiconductor fabrication.
Robotics, Automation & AI
We're building closed-loop, AI-integrated biomanufacturing infrastructure where robotic systems handle iPSC reprogramming, differentiation, and QC — eliminating batch-to-batch variability.
Overview
Cell therapy manufacturing suffers from the same manual variability that plagued semiconductor fabrication before automation. We're solving this by building fully integrated robotic systems that execute iPSC reprogramming, colony picking, passaging, differentiation, and quality control — all within controlled cleanroom environments.
Machine learning models trained on our manufacturing datasets score iPSC colony morphology, predict deviation events, and optimize bioprocess parameters in real time. Digital twin infrastructure enables in silico process development and regulatory submission support.
Technology Stack
Automated Reprogramming
Robotic liquid handling and colony picking for standardized episomal reprogramming workflows.
AI Colony Scoring
Computer vision models for pluripotency and morphology scoring without manual review.
Robotic Differentiation
Automated media exchange, sampling, and feeding schedules for large-scale differentiation runs.
Real-Time CQA Monitoring
Inline sensors and automated sampling for critical quality attribute measurement.
ML Process Optimization
Bayesian optimization and reinforcement learning models for yield and purity maximization.
Digital Twins
Computational models of bioreactor processes for regulatory submissions and process scale-up.