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. Preparing concentration conversion factors (CCFs) using linear regression models is highlighted as an external referencing quantitative NMR (qNMR) method. The qNMR method is then applied to monitor a pharmaceutically relevant model chemical reaction, with key process information successfully obtained.image

Automated summary

Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique that provides quantitative and structural information about multiple components in a sample. This study describes a simple and robust method to determine concentration conversion factors using linear regression models in NMR systems, and applies this method to monitor a pharmaceutically relevant amide coupling reaction.