Abstract
The global coronavirus pandemic continues to restrict public life worldwide. An effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA) vaccines currently available on the market have proven to be a well-tolerated and effective class of vaccine against coronavirus type 2 (CoV2). Accordingly, demand is presently outstripping mRNA vaccine production. One way to increase productivity is to switch from the currently performed batch to continuous in vitro transcription, which has proven to be a crucial material-consuming step. In this article, a physico-chemical model of in vitro mRNA transcription in a tubular reactor is presented and compared to classical batch and continuous in vitro transcription in a stirred tank. The three models are validated based on a distinct and quantitative validation workflow. Statistically significant parameters are identified as part of the parameter determination concept. Monte Carlo simulations showed that the model is precise, with a deviation of less than 1%. The advantages of continuous production are pointed out compared to batchwise in vitro transcription by optimization of the space–time yield. Improvements of a factor of 56 (0.011 µM/min) in the case of the continuously stirred tank reactor (CSTR) and 68 (0.013 µM/min) in the case of the plug flow reactor (PFR) were found.
Highlights
In the past 1.5 years, Messenger ribonucleic acid (mRNA)-based vaccines have become increasingly relevant due to the COVID-19 pandemic
In vitro transcription describes an enzymatic reaction in which mRNA is produced from template deoxyribonucleic acid (DNA)
In order to increase the productivity of existing facilities, the conversion from the currently operated batch to continuous mRNA
Summary
In the past 1.5 years, mRNA-based vaccines have become increasingly relevant due to the COVID-19 pandemic. The control strategy to be developed in the context of a quality-by-design (QbD)-based process development, to ensure the quality target product profile (QTPP), requires design spaces [13]. These can be defined via validated process models in order to avoid out-of specification (OOS) batches [14,15]. The extensive studies are used to quantify the advantages in terms of space–time yield, representative of speed and capacity, of continuous production over a batchwise production These results have been incorporated into an extensive study comparing batchwise and continuous total processes in a recently published paper and could be used to determine the optimal operating points for in vitro transcription. The presented digital twins lay the foundation for future experimental validation
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