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                    <title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title"
                           schemename="dnet:dataCite_title">Digital Twins for Continuous mRNA Production
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                    <dateofacceptance>2021-11-04</dateofacceptance>
                    <description>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.
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                             schemename="dnet:subject_classification_typologies">Coronavirus
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                             schemename="dnet:subject_classification_typologies">Continuous production
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                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
                             schemeid="dnet:subject_classification_typologies"
                             schemename="dnet:subject_classification_typologies">Messenger RNA
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                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
                             schemeid="dnet:subject_classification_typologies"
                             schemename="dnet:subject_classification_typologies">Continuous stirred-tank reactor
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                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
                             schemeid="dnet:subject_classification_typologies"
                             schemename="dnet:subject_classification_typologies">Plug flow reactor model
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                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
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                             schemename="dnet:subject_classification_typologies">Mathematics
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                             schemeid="dnet:subject_classification_typologies"
                             schemename="dnet:subject_classification_typologies">In vitro transcription
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                             schemename="dnet:subject_classification_typologies">Yield (chemistry)
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                             schemename="dnet:subject_classification_typologies">Public life
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                             inferenceprovenance="update" provenanceaction="subject:fos">030104 Developmental Biology
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                             inferenceprovenance="update" provenanceaction="subject:fos">0303 health sciences
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                             inferenceprovenance="update" provenanceaction="subject:fos">0210 nano-technology
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                             inferenceprovenance="update" provenanceaction="subject:fos">021001 Nanoscience &amp;
                        Nanotechnology
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                             inferenceprovenance="update" provenanceaction="subject:fos">010405 Organic Chemistry
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                    <journal issn="2227-9717">Processes</journal>
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