A soft sensor based on pH for real-time monitoring of mRNA medicine production

Abstract

Real-time monitoring of in vitro transcription (IVT) reactions is critical for enabling continuous manufacturing of high-quality mRNA vaccines and therapeutics for a wide spectrum of diseases. Compared to traditional batch manufacturing, continuous IVT production offers higher throughput, improved consistency, and reduced costs, but requires timely process monitoring to detect deviations and maintain product quality. Since pH is routinely measured in bioreactors, it can serve as a convenient, non-invasive input for real-time monitoring. We present the first IVT soft sensor based on H⁺ release during NTP incorporation, using in-line pH data to infer up to 40 otherwise predominantly unobservable species in real time, without requiring additional sensors. Validated against a separate set of offline measurements (not used for model fitting), it delivers updates every 25 milliseconds via two complementary models. The first couples a mechanistic IVT model with an Unscented Kalman Filter (UKF) to dynamically infer ≈40 key indicators, including mRNA yield (R² = 0.95) and NTP depletion (R² = 0.84). The second applies the semi-empirical Henderson–Hasselbalch correlation to reconstruct mRNA yield (R² = 0.93) and NTP depletion (R² = 0.76) from buffer capacity and pH change alone. This soft sensor enables continuous, real-time process monitoring by generating ≈1600 concentration estimates per second, supporting quality-by-digital-design and advanced control for continuous, disease-agnostic mRNA medicine manufacturing.