Model-Based Optimization of Fed-Batch In Vitro Transcription.

Recent developments in RNA vaccines and therapeutics have motivated the need for process engineering strategies to optimize the in vitro transcription (IVT) reaction for RNA synthesis. Specifically, practitioners seek to maximize the production of RNA and the incorporation of the 5-prime cap to the end of each RNA molecule while minimizing the use of expensive reagents. Fed-batch IVT is a promising technique for achieving these goals but is difficult to optimize by purely experimental means. Herein, a mechanistic model for fed-batch IVT is developed and it is used to develop optimized fed-batch protocols to maximize the formation of RNA while controlling concentrations of nucleoside triphosphates. On a model sequence that has been shown to be sensitive to salt concentrations, this approach can produce twice as much RNA as a heuristic approach. In addition, it is observed and characterized for the first time the formation of magnesium phosphate crystals during the IVT reaction. Strategies informed by thermodynamic modeling are developed to prevent this undesired crystallization during fed-batch IVT. Finally, co-transcriptional capping is incorporated into the model-based optimization approach and a strategy to maximize RNA formation is developed while maintaining a high level of 5-prime cap incorporation and minimizing the use of cap analogs.