In silico construct design with integrated immunogenicity profiling.
Our platform enables rational design of vaccine constructs by modeling epitope orientation, antigen folding, and T-cell response potential. Immunogenicity scoring is powered by models trained on in vivo datasets, achieving >5× improvement in predictive accuracy. Reduce in vivo experiments through structure-aware design and AI-guided construct prioritization.
Structure-based protein redesign for functional optimization.
We provide a computational pipeline for predicting 3D structure, evaluating stability and binding, and iteratively redesigning sequences to meet functional targets. Our models reduce the need for brute-force screening by >100-fold, enabling rapid convergence on high-performing variants with desirable biophysical and pharmacokinetic properties.
AI-guided manufacturing analytics for T-cell and stem cell therapies.
Our system analyzes multivariate CQAs, including image-based metrics, bioreactor parameters (pH, DO, temp), and donor-specific variables to optimize harvest timing and upstream process controls. Designed to reduce batch failure rates and COGS in both autologous and allogeneic workflows. Fully compatible with your existing manufacturing data streams.
