A new industry analysis reframed the CAR-T manufacturing bottleneck as a transition from reactive batch execution to predictive process control. The report argues that scalable access is constrained by donor-to-donor variability, patient-specific manufacturing, and complex multi-step workflows under GMP requirements. It also highlights gaps in real-time analytics: existing inline sensors often measure what a cell has already done rather than what it can become, limiting early intervention opportunities when runs start drifting. The piece positions predictive platforms as a route to earlier cellular-state recognition. As CAR-T scales to larger patient populations and broader indications, the report suggests companies will need technologies capable of revealing cellular states earlier in manufacturing—enabling proactive decisions rather than retrospective test-and-learn cycles. The editorial also points to dielectric signature approaches used by Cytomos’ AuraCyt platform as an example of how biophysical measurement could support more robust batch outcomes.