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Monitoring and Quantification of Omeprazole Synthesis Reaction by In-line Raman Spectroscopy and Characterization of the Reaction Components Damir Šahni#, Ernest Mestrovic, Tomislav Jedna#ak, Iva Habinovec, Jelena Parlov-Vukovi#, and Predrag Novak Org. Process Res. Dev., Just Accepted Manuscript • DOI: 10.1021/acs.oprd.6b00323 • Publication Date (Web): 30 Nov 2016 Downloaded from http://pubs.acs.org on December 5, 2016

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Organic Process Research & Development

Monitoring and Quantification of Omeprazole Synthesis Reaction by In-line Raman Spectroscopy and Characterization of the Reaction Components Damir Šahnić a,*, Ernest Meštrovića, Tomislav Jednačakb, Iva Habinovecb, Jelena Parlov Vukovićc and Predrag Novak b a

PLIVA Croatia Ltd. (member of TEVA group), Prilaz baruna Filipovića 25, 10000 Zagreb,

Croatia b

University of Zagreb, Faculty of Science, Department of Chemistry, Horvatovac 102a, 10000

Zagreb, Croatia c

INA-Industrija Nafte d.d., Refining and Marketing Business Division, Lovinčićeva bb, 10002

Zagreb, Croatia

ACS Paragon Plus Environment

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Table of Contents Graphic

100 90 80 70

Percent area

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O O

O

60

S

N

50

N

S

MeOH, AHM, H2O2 (6%)

N NH

N NH

STS, HOAc (20%)

O

+ O

O

40 O N

30

O S

N NH

O

20 10 0 25

35

45

55

65

75

85

95

105

Reaction time [min]


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ABSTRACT

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 FT 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. Owning to its higher sensitivity, dispersive Raman spectroscopy was further employed for quantification purposes. The spectroscopic measurements and the complimentary HPLC analyses, used in the calibration development, were gathered from a set of experiments, performed at a 1 L scale. Based on the data set obtained from the calibration experiments, a predictive partial least square (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 potential to be used as part of a feed-back control loop in the production plant.

KEYWORDS:

in-line

Raman

spectroscopy,

multivariate


analysis,

omeprazole,

PAT.

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1. INTRODUCTION

Over the past few decades, process analytical technology (PAT) has become one of the key tools to entirely implement accurate, versatile and reliable in-line sensors for monitoring and understanding of production processes1–3. The PAT initiative proposed by Food and Drug Administration4, aimed at encouraging the adoption of new technological advances by the pharmaceutical industry, has led to increased focus on the applications of in-line analysis in all phases of active pharmaceutical ingredient (API) and final dosage form (FDF) development and production. Traditional off-line monitoring procedures, such as chromatography, usually include the measurements of samples taken out from the process and are thus unable to provide results in real time. In-line analytical techniques represent attractive alternatives for the traditional monitoring procedures, as they enable in situ observation of physical or chemical transformations using immersion or non-contact probes designed for continuous remote measurements at different segments of the process equipment. This approach can substantially enhance manufacturing efficiency and safety, aid in process understanding, minimize the probability of sample degradation or contamination, reduce process costs and analysis time, avoid sampling issues including non-representative sampling and ensure the desired product quality. Still, application of this technology in the production of APIs did not reach the level predicted at the time of introduction and promotion of this concept at the beginning of 1990s. There are still open issues which need to be solved and some of them are addressed in this work. In most cases these are connected to the insufficient method robustness with respect to process variations like quality of reagents used, variations in solvent and reagent quantities in-between batches, volume change during the reaction and generally an insufficient amount of calibration data used during method development3. An important class of in-line techniques is based on


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vibrational (infrared and Raman) spectroscopy. In the pharmaceutical industry, in-line vibrational spectroscopy has emerged as a powerful tool for real-time monitoring and control of chemical reactions5–12, bioprocesses13,14, polymorphic transformations15,16, lyophilization17, crystallization16,18,19,20,21, hot-melt exstrusion22,23, powder blending24 and wet granulation processes25. Raman spectroscopy in particular was shown to be a very useful tool to gain valuable process understanding about the rate and extent of chemical reactions during scaleup10,12. Due to the inherent complexity of vibrational spectra especially when analyzing complex chemical mixtures, experimental results are usually further processed by applying one or more multivariate analysis methods to obtain qualitative and quantitative information about the measured system. In our recent studies, we have demonstrated that Raman spectroscopy together with multivariate methods can successfully be employed for in-line monitoring of condensation reactions7,8 and active pharmaceutical ingredient (API) crystallization process19. In this study we combined in-line Raman spectroscopy with multivariate analysis to monitor the oxidation of sulfide 3, being the final step in the synthesis of the API omeprazole 4, as shown in

Scheme

1.

Omeprazole

4,

5-methoxy-2-{[(4-methoxy-3,5-dimethylpyridin-2-

yl)methyl]sulfinyl}-1H-benzimidazole, is a potent, non-reversible inhibitor of the gastric parietal cell proton pump (H+/K+-ATPase) used in the treatment of gastroesophageal reflux disease, peptic ulcer disease and Zollinger-Ellison syndrome26,27. To monitor this reaction we used dispersive and FT Raman instruments with different excitation wavelengths (785 and 1064 nm) in order to explore their potential in developing a quantitative in-line method for process monitoring. Apart from the oxidation of sulfide 3 to omeprazole 4, a consecutive oxidation of omeprazole 4 to sulfone 5 occurs. Sulfone 5 is considered here as an impurity. The levels of sulfide 3 and sulfone 5 at the end of the reaction have been deemed a critical quality attribute


5


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(CQA) since they directly influence the purity of isolated omeprazole 4. Therefore, it is important to develop a reliable approach for monitoring and control of the process parameters that influence the reaction outcome. There are only few published studies in the literature which describe in-line reaction monitoring by Raman spectroscopy7-12. However, those studies were only focused on the reactions undergoing straightforward reactant to product transformations ending in stable reaction mixtures. Furthermore, to the best of our knowledge, no data has been published so far on the implementation of a predictive 3-component PLS regression model for reaction monitoring. Hence, the aim of this work was to combine in-line Raman spectroscopy with multivariate analysis to determine the reaction end point and the exact percentage of compounds 3, 4 and 5 at any given time during the reaction. This methodology could enableaccurate in-line monitoring and optimization of the omeprazole production process and could thus replace a time consuming off-line HPLC analysis which is used in-process control. Also the aim was to see if there is potential in application of this methodology to other systems.

Scheme 1. Omeprazole 4 route of synthesis with atom numbering. For the sake of comparison we also applied an LC-SPE/NMR methodology during the course of the oxidation reaction to analyze reaction aliquots off-line. Prior to the reaction monitoring the


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reaction products were isolated, identified and structurally characterized by means of NMR and Raman spectroscopy in solution and solid state.

2. EXPERIMENTAL 2.1. Equipment Two different types of Raman spectrometers were used during the screening part of this study. FT-Raman spectroscopy was performed on a Bruker (Bruker Optics, GmbH, Ettlingen, Germany) Equinox 55 FT-interferometer equipped with a FRA 160/S apparatus providing Nd:YAG laser (liquid nitrogen cooled) excitation at 1064 nm. Spectra acquisition was done by averaging 128 scans in the range of 3500–100 cm–1 with a resolution of 4 cm–1. Laser power for off-line and in-line measurements was 103 and 500 mW, respectively. In-line measurements were performed every 3.7 min during H2O2addition. Dispersive Raman spectroscopy was performed on a KOSI (Kaiser Optical Systems, Inc., Ann Arbor, USA) Rxn1 Raman analyzer equipped with an Invictus laser diode (excitation at 785 nm), Peltier cooled charge coupled device (CCD) camera and a MR Filtered Probe Head. Measurements were single acquisitions in the range of 3500–100 cm–1with an exposure time of 50 s. Laser power during both off-line and in-line measurements was 400 mW. In-line measurements were performed every 5 min during H2O2 addition using a WetHead™ Hastelloy probe (1.27 cm diameter, 40 cm length) with a sapphire window. Off-line measurements of solid samples were performed using a non-contact PhAT sampling device having a coherent beam of 3 mm and a working distance of around 120 mm. Experiments monitored with the FT-Raman spectrometer were performed in a custom 1 L jacketed glass reactor equipped with a Raman immersion probe, pH and temperature probe,


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overhead mechanical agitator and a circulating thermostatic bath. Experiments monitored with the dispersive Raman spectrometer were carried out in the Optimax (Metler Toledo) 1 L glass reactor equipped with a Raman immersion probe, pH and temperature probe, overhead mechanical agitator and a Peltier cooling device. In both cases, the reactor parts exposed to the surrounding light were covered with aluminum foil. Off-line HPLC analyses were performed on an Agilent 1100 series instrument using an in-house omeprazole end of reaction monitoring method. LC-SPE/NMR measurements were performed on Agilent 1260 Infinity series instrument and SPE Prospekt2 system (Spark Holland, Netherlands). HySphere Resin GP cartridges (10 mm x 2 mm) and the multitrapping mode were used. NMR spectra were recorded on Bruker Avance III HD spectrometer operating at 400 MHz. More experimental data is given in Supporting Information.

2.2. Materials Hydrogen peroxide (H2O2, min. 30%), methanol (min. 99.8%), sodium thiosulfate pentahydrate (STS, min. 99.5%), acetic acid (HOAc, min 99.5%) and ammonium heptamolybdatetetrahydrate (AHM, min. 99%) were obtained from Kemika (Zagreb, Croatia). Sodium hydroxide (min. 99%) was purchased from Riedel-de Haën (Seelze, Germany). 5methoxy-1H-benzimidazole-2-thiol

(MTX

1)

and

2-(chloromethyl)-4-methoxy-3,5-

dimethylpyridine hydrochloride salt (OMP-Cl 2) were obtained from various commercial suppliers. benzimidazole

5-methoxy-2-{[(4-methoxy-3,5-dimethylpyridin-2-yl)methyl]sulfanyl}-1H(sulfide

3)

and

5-methoxy-2-{[(4-methoxy-3,5-dimethylpyridin-2-

yl)methyl]sulfonyl}-1H-benzimidazole (sulfone 5) were synthesized in-house.


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2.3. Omeprazole synthesis procedure NaOH (25.90 g, 647.50 mmol) was dissolved in a mixture of methanol (325 mL) and water (26 mL) followed by addition of MTX 1 (52.20 g, 289.63 mmol). After complete dissolution of MTX 1, OMP-Cl 2 (64.00 g, 288.14 mmol) was added and the mixture was heated to reflux temperature. After 60 minutes of agitation at reflux temperature, the mixture was cooled to 20°C. AHM (1.78 g, 1.44 mmol) solution in water (40 mL) was added to the suspension of the product, sulfide 3. The agitation was set to 400 rpm. By using a dropping funnel, a 6 % (w/w) aqueous H2O2 solution (172 mL, 303.44 mmol) was added dropwise into the mixture over 90 min while keeping the temperature between 20–25°C. During the addition, the pH value of the mixture was maintained at 9.3 using a 40 % (w/w) aqueous NaOH solution. 5 minutes after addition of H2O2 was finished, STS (1.42 g, 5.72 mmol) was added to quench the reaction. The pH was set to 9.1 using a 20 % aqueous HOAc solution in order to crystallize the product, omeprazole 4. The mixture was agitated for the next 3 h while maintaining the pH at 9.1 and the temperature between 20–25°C. After this period, the suspension was filtered over a Büchner funnel. The product was washed two times with water (100 mL) and dried in a vacuum tray dryer at 30°C until constant mass. Yield: 76.19 g (76.6%).

2.4. Multivariate analysis and calibration Owning to its higher sensitivity, we applied dispersive Raman spectroscopy for quantitative calibration method development. Given the complexity of the reaction mixture and observed severe band overlap, it was not possible to unambiguously assign all Raman bands, determine the mixture content and assess the reaction end point simply from the analysis of in-line spectra. Hence, the recorded spectra were further processed by multivariate methods in order to analyze


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the data and extract quantitative information. Due to the fact that the system was never in a constant volume phase and similar ratios of 3, 4 and 5 could be observed in different methanolwater (v/v) mixtures, it was difficult to generate accurate ternary blends that would correlate well with the real reaction mixtures. Thus, Raman spectra acquired during in-line measurements combined with off-line HPLC analyses were used for calibration and model validation purposes. An in-house omeprazole end of reaction (EOR) monitoring HPLC method was used to determine the ratio of the three compounds. Samples were taken parallel to spectral acquisition. The ratio was expressed as relative percent area (% area), as described in the HPLC method (see Supporting Information). A set of six experiments was performed in order to generate a sufficiently large calibration and validation data set. Different batches from two current suppliers of MTX 1 were used since it was found that this material is the main source of variable fluorescence background. In experiments 1, 2 and 3 one vendor was used and another one in experiments 4, 5 and 6. In experiments 1, 4 and 5, the amounts of H2O2 were 0.9, 1.4 and 1.5 molar equivalents, respectively, in order to obtain mixtures with low and high concentrations of sulfone 5. The robustness of calibration was further improved by employing variable addition rates of H2O2 in all experiments, which resulted with similar compound ratios at different MeOH-water (v/v) mixtures. All spectra preprocessing and multivariate analyses were done with The Unscrambler X, version 10.4 (Camo Software) and OPUS Spectroscopy Suite version 7.2 (BRUKER).


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3. RESULTS AND DISCUSSION 3.1. Off-line identification of the isolated reaction products 3.1.1. NMR spectroscopy The reaction components were isolated, identified and structurally characterized by means of the standard one- and two-dimensional NMR techniques and their proton and carbon chemical shifts assigned in DMSO-d6 according to the literature reference28,29 (Table S1,Supporting Information). Isolated reaction components were further analyzed by solid state NMR using

13

C CP-MAS

technique. Carbon atoms were assigned based on the comparison with NMR data obtained in solution (Table S1). As can be seen in Figure 1, compound 3 exhibited signals at 13.41, 18.18, 39.91, 56.76 and 62.95 ppm, corresponding to carbon atoms at positions 15, 17, 9, 18 and 16, respectively. Broad signals in the region 115–155 ppm were attributed to aromatic carbons of 3. The most deshielded peaks, observed at 158.05 and 165.94 ppm, were assigned to carbon atoms directly bound to methoxy groups at positions 3 and 12, respectively. In the spectrum of 4, the signals of atoms C-9, C-16 and C-18 were overlapped and showed a broad peak at 60.15 ppm. Similar was observed for the atoms at positions 1, 6, 8, 11, 13 and 14. In comparison to 3, the signals of atoms C-2, C-15 and C-17 were significantly shifted upfield. On the other hand, aromatic carbons at positions 4, 5, 3 and 12 resonated at higher frequencies and can be used to distinguish between two compounds (Figure 1b). CP MAS spectrum of 5 could not be straightforwardly assigned due to line broadening.


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Figure 1. 13C CP-MAS spectra of (a) 3 and (b) 4. 3.1.2 Raman spectroscopy Prior to applying in-line Raman measurements, the off-line spectra of the isolated crystals of 3–5 were primarily recorded and assigned. The most pronounced differences between 3, 4 and 5 were observed in the spectral region 1800–700 cm−1, as shown in Figure 2. The prominent feature in the Raman spectrum of 3 was a strong vibrational band at 1262 cm−1, attributed to inplane deformation of the heteroaromatic ring. In the spectra of 4 and 5, this band was shifted to 1271 and 1269 cm–1, respectively (Figure 2). Furthermore, in-plane deformation bands at ≈1230 and ≈1190 cm–1 in the spectra of 3–5 had similar positions, but different intensities. On the other hand, out-of-plane deformation bands of 4 were shifted to lower wavenumbers (960, 760 and 730 cm–1) as compared to that of 3 (965, 799 and 752 cm–1) and 5 (970, 768 and 748 cm–1). A very weak band at 1076 cm–1 present in the spectra of 4 and 5 was assigned to the S=O stretching vibration26. Additional signal observed at 1210 cm–1 in the spectrum of 5 corresponded to


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asymmetric SO2 stretching mode. Several bands occurring in the spectral region 1650–1340 cm−1 were attributed to the C=C stretching vibrations of heteroaromatic rings, while a weak band at ≈1590 cm–1 is characteristic of the benzimidazoleimino group30,31. Some ofthese bands might serve as indicators of the reaction progress and could further be applied to identify the reaction components in real time.

Figure 2. Off-line Raman spectra of the isolated crystals of (a) 3, (b) 4 and (c) 5. Laser excitation wavelength was 785 nm.


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3.2. In-line reaction monitoring The in-line Raman spectra were collected in real time during the oxidation reaction by applying dispersive and FT spectrometers with laser excitations at 785 and 1064 nm, respectively. Representative in-line Raman spectra of the oxidation reaction obtained by two different instrumental setups are displayed in Figure 3. New bands, which appeared in Raman spectra during the course of the reaction, indicated the reaction product formation (Figure 3). The appearance of a vibrational band at ≈730 cm−1 can be attributed to the out-of-plane ring deformation characteristic of 4. Simultaneously, the corresponding band of 3 at ≈752 cm–1 clearly decreased in intensity, pointing towards the reactant consumption. The two bands form an isobestic point at ≈ 740 cm-1. However, due to the fact that the immersion probe used contains a sapphire window, sapphire bands32,33 appear at 419, 578 and 751 cm-1 caused by specular reflection and the band at 751 cm-1 overlaps with the sulfide 3 band at 752 cm-1. The O-O stretching bond of H2O2 is also present at 875 cm-1 and it does not overlap with any other bands. Due to the fact that the reaction is carried out by H2O2 addition and the consumption of H2O2 in the reaction is fast meaning no accumulation of the oxidant is present, the band intensity remains roughly the same during the course of the reaction making it of little use for calibration development. The strong band at 1024 cm-1, together with bands at 1118, 1155 and 1450 cm-1 are attributed to methanol34.


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Figure 3. Representative in-line Raman spectra of the oxidation reaction in methanol recorded by using (a) dispersive spectrometer, laser excitation at 785 nm and (b) FT-interferometer, laser excitation at 1064 nm. Additional Raman bands observed around 1590 and 1360 cm−1, whose intensities increase as the reaction progresses, might correspond to the ring stretching modes of 4. Strong bands, which occurred at ≈1272 and 1228cm–1, could be assigned to the in-plane deformations of


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heteroaromatic rings. A weak band appearing at 1567 cm–1, attributed to C=N stretching mode of 4, further confirmed the product formation. The major advantage of the spectrometer with laser excitation at 785 nm was a higher signalto-noise ratio which facilitated the straightforward spectral assignment. The largest drawback of this setup was a broad background signal as the result of fluorescent emission (Figure 3a). Significant reduction of the background signal was achieved by employing the FT-interferometer operating at 1064 nm (Figure 3b). However, the resulting spectra had lower signal-to-noise ratio and thus were less useful for quantitative analysis. For that reason, spectra collection during the calibration experiments was performed using the dispersive Raman spectrometer.

3.3. LC-SPE/NMR analysis of the reaction progress Oxidation of omeprazole sulfide 3 was also monitored off-line by using the LC-SPE/NMR setup in order to compare the results with those obtained by in-line Raman spectroscopy. LCSPE/NMR is a hyphenated system comprising of high performance liquid chromatography with diode array detection (HPLC-DAD), solid phase extraction (SPE) and nuclear magnetic resonance spectroscopy (NMR) which represents a state-of-the-art technology for rapid and accurate compound mixture analysis. It has also proven useful for monitoring chemical reactions34-36. Reaction aliquots were collected at the beginning of the reaction and during the reaction progress (after 20, 40, 60, 80 and 100 minutes). After separation on the chromatographic column, chromatographic peaks of the reaction mixture aliquots were sent to the post column SPE trapping for pre-concentration prior to NMR analysis in order to achieve a better signal-to-noise ratio. Multitrapping option was used. The recorded proton NMR spectra clearly showed the


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progress of the reaction and formation of the reaction products. Figure 4 displays proton spectra recorded at the end of the reaction. Spectral analysis reveals three components present in the mixture corresponding to 3, 4 and 5 (see Figure 4.) which was in line with the results obtained previously by Raman spectroscopy.

Figure 4. An expanded region of 1H NMR spectra of (a) sulfide 3, (b) omeprazole 4 and (c) sulfone 5 obtained in the LC-SPE/NMR mode of the aliquot taken at the end of the reaction.

3.4. Development of the PLS model A total of 105 in-line Raman spectra were collected from 6 discrete experiments together with the complementary percentage area of 3, 4 and 5 determined by off-line HPLC analysis. Spectra collected before the level of 3 dropped below 75 area % were not used since the material was not completely dissolved at levels above due to its limited solubility in the reaction mixture at the reaction pH. This caused a discrepancy between the expected Raman band intensities and the


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cumulative amount measured by HPLC (sampling for HPLC was done by taking a homogenous sample of the entire reaction mixture). The collected spectra were initially truncated between 400 and 1600 cm–1 leaving only the spectral region rich in bands and with observed changes in real time. This entire region was used later on for model development. The spectra were normalized using the vector method and the baseline was corrected using the concave rubber band method with 256 baseline points in 5 iterations (performed in OPUS). The data was further truncated to remove the sapphire bands before performing multivariate analysis leaving the regions 425-571 cm-1, 588-741 cm-1 and 758-1600 cm-1. The preprocessed data was analyzed by principal component analysis (performed in The Unscrambler) to assess the quality of the data set and to try to determine the main influence of variability in the data among experiments. As can be seen from the PC1 vs PC2 score plots in Figure 5, PC1 describes 93 % of the variance and there is a clear difference in the scores of experiments 1, 2 and 3 with respect to experiments 4, 5 and 6 as they form two separate clusters. This was attributed to the higher amount of the background fluorescence caused by increased impurity levels present in the MTX 1 used in experiments 4, 5 and 6. PC2 then describes the changes in each chemical reaction. Variations like using materials with different lot numbers from the same vendor of MTX 1 and varying the total H2O2 amount and its addition rate during the reaction account for 5 % of spectral variation in the data set showing the overshadowing effect the different background fluorescence from MTX 1 has on the data set.


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Figure 5. PC1 vs PC2 score plots of the normalized and baseline-corrected spectra.

PC-2 (11%)

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Figure 6. PC1 vs PC2 score plots of the additional MSC preprocessed spectra (showing the calibration and test set used for PLS regression).


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Owing to the scatter effect plot obtained using the descriptive statistics method available in The Unscrambler and shown in Figure S1, it was observed that the spectra also needed correction for multiplicative scatter effects. These effects have also been observed in other in-line measurements performed in-house using the KOSI Rxn1 Raman analyzer. The multiplicative scatter correction (MSC) was performed in OPUS prior to the PLS regression and it significantly improved the regression results also partially due to further removing the effect that the amount of the background fluorescence carried in the data set. This can be seen in Figure 6, by the decrease in the variance explained by PC1, making changes within each chemical reaction more prominent. In terms of PC1 and PC2 loadings (shown in Figure S2 and S3), the highest amount of spectral variation is seen in regions where new bands appear and present bands decrease in intensity as already described in Section 3.2. After several regression iterations with different test set selection, calibration experiments 3 and 4 were finally used as the test set for the PLS model validation. A single method was obtained for compounds 3, 4 and 5 with ranks 3, 4 and 4 and RMSEP values of 1.2 % area, 1.2 % are and 0.7 % area respectively (Figures S4-9). Optimization in specific spectral regions with high influence regression coefficients for each component determined from the weighted regression coefficients plot and/or application of different preprocessing methods like 1st and 2nd derivatives neither yielded better RMSEP values nor reduced the recommended ranks. The same was observed when developing separate methods for each of the components and applying different preprocessing techniques.

3.5. Use of the PLS model for prediction To test the ability of the model to accurately predict the area percent value of the compound during the reaction, an experiment was performed using standard conditions as described in


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Section 2.3. Raman spectra were collected every 5 min during H2O2 addition up to 5 minutes of agitation time upon quenching with STS (100 min of total reaction time). Parallel samples for off-line HPLC analyses were taken to compare the predicted and HPLC-measured percentage area. The results are shown in Figure 7. The measured vs. predicted area percent values for compounds 3, 4 and 5, 5 minutes after quenching with STS were 3.7/4.1 % area, 88.5/89.5 % area and 7.8/8.2 % area respectively. The complete list of the measured and predicted values together with the complementary Mahalanobis distances is given in Table S2. These results show once again that the oxidation reaction needs to be stopped at a specific point in order to obtain both maximum yield and satisfactory purity of the isolated product. Prolonging the reaction would lead to a further increase in the amount of sulfone 5. 100 90 80 70

Percent area

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Sulfide 3 predicted

60

Omeprazole 4 predicted 50

Sulfone 5 predicted Sulfide 3 measured

40

Omeprazole 4 measured Sulfone 5 measured

30 20 10 0 25

35

45

55

65

75

85

95

105

Reaction time [min]

Figure 7. Reaction progress of the model testing experiment with predicted and measured area percent values of all reaction components.


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After obtaining satisfactory results in the prediction test experiment, the method was further applied in a scale-up batch. The process was scaled-up to a 10 L scale in our kilo-lab and performed in a Büchi automated hastelloy reactor (Figure S10). It is important to state that just the chemistry was scaled-up and not the model so no calibration transfer protocols were employed. In-line Raman spectra were collected in the same fashion as the previous test experiment. The reaction progress expressed as PLS predicted percent area change over time is shown in Figure 8. A sample of the reaction mixture at the end of H2O2 addition (90 minutes) was taken for off-line HPLC analysis to confirm the PLS predicted values.The measured vs. predicted percent area values at this point for compounds 3, 4 and 5 were 14.4/14.1 % area, 81.3/81.3 % area and 4.3/3.7 % area respectively. 100 Sulfide 3 predicted HPLC: 81.3 % area PLS: 81.3 % area

Omeprazole 4 predicted

90

Sulfone 5 predicted Sulfide 3 measured

80

Omeprazole 4 measured 70

Sulfone 5 measured

60

Percent area

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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50 40 30 HPLC: 14.4 % area PLS: 14.1 % area

20

HPLC: 4.3 % area PLS: 3.7 % area

10 0 25

35

45

55

65

75

85

95

105

Reaction time [min]

Figure 8. Reaction progress of the kilo-lab experiment with predicted percent area values of all reaction components. Area percent values measured by HPLC, in a sample taken after H2O2 addition was complete, are also shown.


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The results showed satisfactory correlation between the HPLC-measured and PLS-predicted percentage values. Examining the reaction progress in the kilo-lab batch, it can be observed that the reaction progresses slower and that the percentage values of sulfide 3, omeprazole 4 and sulfone 5 at the quenching time of the reaction did not reach the value needed for obtaining omeprazole with satisfactory purity. This means that a larger amount of H2O2 would be needed to reach the same percentage values of 3, 4 and 5 within the same addition time. It is known from the literature that peroxomolybdate species present in the catalytic system of this reaction, undergo spontaneous decomposition in basic media37. By calculating the hydrodynamic parameters for both reactors (performed in VisiMix Turbulent 2014(11)) and taking into account the total volume of the reaction mixture in each, a threefold increase in the macromixing time for the kilo-lab batch was observed. Since the reaction is performed in a semi-batch mode by continuous H2O2 addition, such behavior in the kilo-lab batch could be explained by this difference in the macromixing time. Nevertheless, the PLS model proved to be a reliable approach for the monitoring of the oxidation reaction and can be used for further process optimization. It could also be potentially used in a feed-back control loop in a production environment to automatically control the addition of STS when the reaction termination criteria are met.

4. CONCLUSION This study has demonstrated that the synthetic reaction of the API omeprazole can be quantitatively monitored in situ by in-line Raman spectroscopy combined with a predictive 3component PLS model. The initial in-line experiments were monitored using dispersive and FT Raman spectrometers showing both the benefits and drawbacks of each in this specific case. It


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has been shown that dispersive Raman spectrometer is advantageous over FT one for omeprazole reaction monitoring. PCA of the Raman spectra from the calibration experiments has shown that the vendor of the starting material can be unambiguously distinguished and that it represents the biggest contributor to spectral variations. The PLS method has also been found applicable to a kilo-lab scale. A good correlation has been found between the chromatographic and PLSpredicted values even though the reaction mixture was neither in a constant volume phase nor was the addition rate constant since no dosing pump was used for H2O2 addition. The method is robust and could further be used in process parameter optimization experiments as well as an IPC method in the production scale batches.

ASSOCIATED CONTENT Supporting Information Additional experimental details, NMR data, PC loadings, PLS regression lines. AUTHOR INFORMATION Corresponding Author *D. Šahnić, PLIVA Croatia Ltd., Prilaz baruna Filipovića 25, 10000 Zagreb, Croatia. Tel.: +385 1 3722584; fax: +3851 372 2802 E-mail address: [email protected] (D. Šahnić) Notes The authors declare no competing financial interest. ACKNOWLEDGMENT


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The authors would like to thank the following colleagues from PLIVA for their support of this work, Dr. Martina Hrkovac for performing the VisiMix calculations, Mislav Runje for his aid and helpful comments regarding the HPLC analysis, Dražen Čavužić for his helpful comments regarding the PLS method development, and the laboratory team, Biljana Blažinović and Vedran Barbarić. Part of this work was supported by European Regional Development Fund and Croatia state budget as a part of the Met4Pharm project.

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Monitoring and Quantification of Omeprazole ... - ACS Publications

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