Programmable Biomanufacturing Cells with Evidence-Bounded Control over Metabolic State, Product Quality, Yield, and Process Robustness across Manufacturing Scales

Biomanufacturing cells are increasingly engineered with synthetic regulatory circuits, dynamic metabolic controls, automated design workflows, and process-aware sensing. Nevertheless, individual engineering improvements do not by themselves create manufacturing systems capable of coordinating metabolic state, recombinant-protein processing, product quality, productivity, and robustness across scales. This article proposes an evidence-bounded programmable biomanufacturing-cell architecture as an original non-empirical synthesis. The architecture separates manufacturing objectives, state sensing, limited state estimation, evidence qualification, constraint-aware policy selection, biological and process actuation, outcome monitoring, and fail-safe execution. Metabolic-state control is treated as an observability and controllability problem rather than as a single-biosensor task. Expression, folding, secretion, modification, and cellular stress are incorporated as interdependent control domains whose manipulation must remain subordinate to product-quality and biosafety constraints. Scale robustness is defined as the preservation of acceptable state estimation and intervention behavior under bioreactor gradients, process fluctuations, host adaptation, and manufacturing-domain change. Evidence thresholds determine whether an intervention may proceed, requires additional testing, should revert to a previously supported operating condition, or must be escalated for human review. The proposed architecture further distinguishes optimization evidence from validation, technical capability from manufacturing readiness, and model confidence from justified decision authority. Validation would require staged component testing, integrated perturbation studies, scale-down and scale-transfer evaluation, longitudinal genetic and phenotypic stability assessment, product-specific analytical verification, containment testing, and governance oversight. The contribution is therefore an organizing architecture and set of testable relationships rather than a validated controller, regulatory framework, or deployment-ready manufacturing system.