Abstract Summary (Max 250 words)
Transient gene expression (TGE) has evolved from a laboratory-scale tool for candidate screening to a rapid platform for preclinical manufacture of recombinant proteins and viral vectors. In TGE, plasmid DNA is complexed with a cationic transfection reagent to form nanoscale DNA-polymer aggregates (i.e., polyplexes). Polyplex formation is governed by a temporal incubation window during which size, charge, and colloidal stability are established prior to introduction into the bioreactor, where cellular uptake and expression occur. While reported titres at laboratory scale have increased from mg/L to g/L over the past decade via biological optimizations (e.g., host cell lines, vector and promoter design, and DNA-to-reagent ratios) (1), industry reports document losses in titre and specific productivity when scaling up from 7 L stirred-tank reactors (STRs) and 22 L rocking bioreactors to 50 L and 200 L STRs (2). This study addresses the hypothesis that transient transfection performance is governed by mixing-controlled exposure histories during and immediately following DNA-polymer complex addition and the finite stability window of polyplexes. Therefore, an engineering characterization was performed in two representative scale-down systems: an ambr® 250 STR and a 2 L rocking bioreactor (CultiBag®). Volumetric power input (P/V), power number, Reynolds number (Re), flow regime, mixing time, and mixing number were quantified across a wide range of operating conditions relevant to industrial TGE. In the STR, mixing time measurements were extended beyond conventional dual-indicator system methodologies by employing transfection-representative addition volumes (> 1 % compared with traditional tracer injections of 0.05 % in < 1 L systems). In parallel, rocking bioreactor hydrodynamics were characterized to resolve free-surface-driven mixing, volume-dependent flow transitions intrinsic to wave-induced systems, and to develop a novel Re formulation appropriate for motion-driven flow. The results demonstrate that matching global metrics such (e.g., P/V) is insufficient for TGE scale-up. Instead, mechanistic scaling criteria must explicitly account for addition-driven mixing dynamics, bioreactor geometries, and transient exposure histories.
