Reaction monitoring via benchtop nuclear magnetic resonance spectroscopy: A practical comparison of on-line stopped-flow and continuous-flow sampling methods

The ability for nuclear magnetic resonance (NMR) spectroscopy to provide quantitative, structurally rich information makes this spectroscopic technique an attractive reaction monitoring tool. The practicality of NMR for this type of analysis has only increased in the recent years with the influx of commercially available benchtop NMR instruments and compatible flow systems. In this study, we aim to compare 19F NMR reaction profiles acquired under both on-line continuous-flow and stopped-flow sampling methods, with modern benchtop NMR instrumentation, and two reaction systems: a homogeneous imination reaction and a biphasic activation of a carboxylic acid to acyl fluoride. Reaction trends with higher data density can be acquired with on-line continuous-flow analyses, and this work highlights that representative reaction trends can be acquired without any correction when monitoring resonances with a shorter spin-lattice relaxation time (T1), and with the used flow conditions. On-line stopped-flow analyses resulted in representative reaction trends in all cases, including the monitoring of resonances with a long T1, without the need of any correction factors. The benefit of easier data analysis, however, comes with the cost of time, as the fresh reaction solution must be flowed into the NMR system, halted, and time must be provided for spins to become polarized in the instrument's external magnetic field prior to spectral measurement. Results for one of the reactions were additionally compared with the use of a high-field NMR.

Flow-NMR as a Process-Monitoring Tool for mRNA IVT Reaction

Messenger RNA (mRNA) based vaccines were instrumental in accelerating the end of the SARS-CoV-2 pandemic and are being aggressively developed as prophylaxes for a range of viral diseases. The swift adoption of mRNA-based therapeutics has also left open vast areas of opportunity for improving the development of mRNA-based drugs. One such area with immense potential focuses on the mRNA drug substance production, where mRNA is generated by a cell-free reaction called in vitro transcription (IVT). Process analytical technologies (PAT) are integral to the pharmaceutical industry and are necessary to facilitate agile process optimization and enhance process quality, control, and understanding. Due to the complexity and novelty inherent to the IVT reaction, there is a need for effective PAT that would provide in-depth, real-time insight into the reaction process to allow delivery of novel mRNA vaccines to patients faster in a more cost-effective way. Herein, we showcase the development of flow-nuclear magnetic resonance (flow-NMR) as a highly effective process-analytical tool for monitoring mRNA IVT reactions to support process development, optimization, and production.

A reliable external calibration method for reaction monitoring with benchtop NMR

Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique with the ability to acquire both quantitative and structurally insightful data for multiple components in a test sample. This makes NMR spectroscopy a desirable tool to understand, monitor, and optimize chemical transformations. While quantitative NMR (qNMR) approaches relying on internal standards are well-established, using an absolute external calibration scheme is beneficial for reaction monitoring as resonance overlap complications from an added reference material to the sample can be avoided. Particularly, this type of qNMR technique is of interest with benchtop NMR spectrometers as the likelihood of resonance overlap is only enhanced with the lower magnetic field strengths of the used permanent magnets. The included study describes a simple yet robust methodology to determine concentration conversion factors for NMR systems using single- and multi-analyte linear regression models. This approach is leveraged to investigate a pharmaceutically relevant amide coupling batch reaction. An on-line stopped-flow (i.e., interrupted-flow or paused-flow) benchtop NMR system was used to monitor both the 1,1'-carbonyldiimidazole (CDI) promoted acid activation and the amide coupling. The results highlight how quantitative measurements in benchtop NMR systems can provide valuable information and enable analysts to make decisions in real time.

Reaction Kinetics using a Chemputable Framework for Data Collection and Analysis

Automated chemistry platforms have been widely explored, but many focus on fixed tasks for chemical synthesis or analysis. However, a typical synthetic chemistry workflow utilizes both, such as kinetic measurements for reaction development and optimization. Due to their repetitive and time-consuming nature, kinetic measurements are often omitted, which limits the mechanistic investigation of reactions. Herein, we present a "Chemputer" platform with on-line analytics (UV/Vis, NMR) which automates routine kinetic measurements. The system's capabilities are showcased by exploring an inverse electron-demand Diels-Alder using initial rate measurements, a metal complexation using variable time normalization analysis (VTNA), and formation of a series of tosylamide derivatives using Hammett analysis. Over 60 individual experiments are presented which required minimal intervention, highlighting the significant time savings of automation. Owing to the modular design of the platform, which facilitates rapid integration of commercial analytical tools, our approach is widely accessible and adjustable to the reaction under investigation. The platform is operated using the chemical programming language, XDL, hence experimental procedures and results are stored in a precise, computer-readable format. We propose that widespread adoption of this reporting protocol in the chemical community could build a database of validated kinetic data beneficial for Machine Learning.

Continuous flow synthesis of pyridinium salts accelerated by multi-objective Bayesian optimization with active learning

We report a human-in-the-loop implementation of the multi-objective experimental design via a Bayesian optimization platform (EDBO+) towards the optimization of butylpyridinium bromide synthesis under continuous flow conditions. The algorithm simultaneously optimized reaction yield and production rate (or space-time yield) and generated a well defined Pareto front. The versatility of EDBO+ was demonstrated by expanding the reaction space mid-campaign by increasing the upper temperature limit. Incorporation of continuous flow techniques enabled improved control over reaction parameters compared to common batch chemistry processes, while providing a route towards future automated syntheses and improved scalability. To that end, we applied the open-source Python module, nmrglue, for semi-automated nuclear magnetic resonance (NMR) spectroscopy analysis, and compared the acquired outputs against those obtained through manual processing methods from spectra collected on both low-field (60 MHz) and high-field (400 MHz) NMR spectrometers. The EDBO+ based model was retrained with these four different datasets and the resulting Pareto front predictions provided insight into the effect of data analysis on model predictions. Finally, quaternization of poly(4-vinylpyridine) with bromobutane illustrated the extension of continuous flow chemistry to synthesize functional materials.