Monitoring and Quantification of Omeprazole Synthesis Reaction by In-Line Raman Spectroscopy and Characterization of the Reaction Components

• Published in: Organic process research & development Vol. 20; no. 12; pp. 2092 - 2099
• Main Authors: Šahnić, Damir, Meštrović, Ernest, Jednačak, Tomislav, Habinovec, Iva, Parlov Vuković, Jelena, Novak, Predrag
• Format: Journal Article
• Language: English
• Published: WASHINGTON American Chemical Society 16.12.2016; Amer Chemical Soc
• Subjects: Chemistry; Chemistry, Applied; Chemistry, Organic; Physical Sciences; Science & Technology; in-line Raman spectroscopy; omeprazole; process analytical technology; multivariate analysis; CRYSTALLIZATION; FEEDBACK-CONTROL; ACID; CHEMOMETRICS; REACTION-PRODUCTS; HOT-MELT EXTRUSION; SOLID-STATE CHARACTERIZATION
• ISSN: 1083-6160; 1520-586X
• DOI: 10.1021/acs.oprd.6b00323

The development of a quantitative in-line Raman spectroscopic method for the monitoring of the active pharmaceutical ingredient, omeprazole synthesis reaction, and characterization of the reaction components is described. In-line monitoring was performed both with Fourier transform and dispersive Raman spectrometers. Prior to reaction monitoring, the reaction components were characterized off-line by means of Raman and NMR spectroscopy, both in solution and in solid state. To unequivocally confirm the presence of each component in the reaction mixture, a state of the art LC-SPE/NMR methodology was also used. Owing to its higher sensitivity, dispersive Raman spectroscopy was further employed for quantification purposes. The spectroscopic measurements and the complementary HPLC analyses, used in the calibration development, were gathered from a set of experiments, performed at a 1 L scale. On the basis of the data set obtained from the calibration experiments, a predictive partial least-squares (PLS) regression model was developed for all three reaction components, enabling an accurate determination of the percentage of each component present in the reaction mixture, at any time after the point when 25% of the starting material has been consumed. The model was successfully used to monitor the reaction progress in a kilo-lab scale experiment and can further be used as a fast response analytical tool in process optimization. It also has the potential to be used as part of a feedback control loop in the production plant.