Short-Term Effects vs. Sustained Response
Immediate killing and long-term function must be evaluated together
CAR-T Cell Functional Optimization
Predict gene perturbation responses in virtual cells to help screen engineering strategies
Applicable Areas
Autologous CAR-T
Allogeneic (Universal) CAR-T
In Vivo CAR-T
The Challenge
Engineering Effects Depend on Context
Donor, CAR design, and antigen conditions all affect outcomes
Limited Resources for Combinatorial Screening
As candidate combinations grow, evidence-based prioritization is needed
Core Architecture
Use the CellOS foundation model to assess cell state changes from candidate perturbations and set experimental priorities for functional engineering
R&D Deliverables
Assess how cells may change before engineering them in the lab
01
Candidate Genes and Perturbation Modalities
Screen potential functional optimization targets and identify which genes and perturbation strategies to validate first
02
Predicted Responses and Ranking Rationale
Show the cell state changes induced by candidate perturbations and explain the basis for prioritization
03
Experimental Validation and Model Feedback
Design in vitro functional validation plans and use experimental results to evaluate prediction performance and calibrate the model
Core Value
Narrow the Candidate Pool
Up-Front Engineering Assessment
Support Multi-Objective Trade-Offs
Faster R&D Iteration
