Application of In Situ Raman Spectroscopy To Facilitate Use of

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Application of In Situ Raman Spectroscopy To Facilitate Use of Hydrogen Peroxide on Kilogram Scale Dawn Cohen, Andrew Cosbie, Robert R. Milburn,* Stephen Shaw,† and Yong Xie* Amgen Inc., One Amgen Center Drive, Thousand Oaks, California 91320, United States ABSTRACT: The safe implementation of a hydrogen-peroxide-mediated oxidation of a poorly reactive sulfide to the corresponding sulfone is described. A three-tiered approach incorporating process understanding, safety studies, and real time PAT (in situ Raman spectroscopy) was leveraged to ensure safe operation. Further investigation of an in situ Raman spectroscopy model for the reaction and its use for in-process control and end-point determination is discussed.

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significantly exothermic by 456 kJ/mol.5 A kinetic understanding of the reaction was vital for its safe implementation. The profile of the reaction is shown in Figure 1. The overall

INTRODUCTION Oxidation chemistry is generally avoided in the design of syntheses to be carried out on scale for a variety of reasons, but chief among these is the inherent hazard of mixing flammable solvents in a highly oxidizing environment.1 As such, oxidation chemistry has occupied as little as 3% of those processes carried out on scale.2 Of the oxidation chemistry at ones disposal, hydrogen peroxide (H2O2)-mediated transformations are amongst the most attractive due to the availability, low cost, and benign byproducts upon consumption of H2O2. However, its susceptibility to exothermic decomposition leading to runaway reactions and the potential for the evolution of large amounts of oxygen demand a carefully considered risk mitigation strategy.3 In spite of this, the safe use of H2O2 on scale has been achieved via process design and the use of engineering controls.4 A recent clinical candidate required tens of kilograms of a sulfone intermediate that was to be accessed via a H2O2-mediated molybdenum-catalyzed oxidation of a diaryl sulfide. The large amount of H2O2 required (>2 equiv) along with a slow reaction rate gave rise to a potential peroxide buildup that mandated tight control of the operating parameters. To safely implement this chemistry, we applied a three-tiered approach; we established a thorough understanding of the reaction kinetics and thermodynamics, carried out extensive safety studies on the reaction system to determine a safe operating space, and implemented engineering controls and real time PAT (in situ Raman spectroscopy) to guarantee the maintenance of the system within the defined operating space. The reaction of interest (Scheme 1) is a molybdenumcatalyzed H2O2-mediated oxidation of a sulfide (1) to the corresponding sulfone (3). The reaction occurs in two discrete steps passing through the sulfoxide intermediate 2 and is

Figure 1. Reaction profile of the oxidation of sulfide 1 to sulfone 3 via intermediate sulfoxide 2.

rate of reaction is slow, requiring several hours to reach completion, with the formation of 2 being rate-limiting. We also determined the initial rate of reaction to be first-order in the catalyst and independent of peroxide concentration.6 Extensive safety studies were carried out on the reaction components and mixtures to establish safe operating parameters. The urea hydrogen peroxide (UHP) used in the reaction was found to be stable up to its melt at 80 °C, at which temperature an exothermic decomposition occurred (694 J/g).7 In the reaction solvent, UHP was found to be stable below 60 °C, and in the presence of the catalyst, this decomposition temperature dropped to 40 °C.8 Isothermal tests of the UHP/ catalyst/solvent mixture showed the rate of UHP decomposition to be temperature-dependent and significantly slower than that of the oxidation of 1.9 Calorimetry was carried out on the system to measure heat evolution, revealing a significant adiabatic temperature rise (ATR) of 75−80 °C with a maximum heat evolution (18 W/L) that was well within the available vessel cooling capacity (30 W/L).10 The decomposition onset of the solid UHP (80 °C) and the ATR were the

Scheme 1. Oxidation of Sulfide 1 to Sulfone 3 by Urea− H2O2 (UHP) Proceeding through Intermediate Sulfoxide 2

Special Issue: Safety of Chemical Processes 14 Received: April 21, 2014 Published: June 9, 2014 © 2014 American Chemical Society

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main factors influencing the safe operating window. Thus, a reaction temperature of 30−35 °C and the addition of UHP limited to 1/4 of the total charge (ATR of 25 °C) were indicated to provide sufficient buffer between the UHP decomposition onset. Since gas evolution is also of concern, the total amount of active peroxide in the system at a given time was limited to 1/2 equiv based on the venting capacity of the available reactors. The desire for tight control over the active peroxide in the reaction combined with the slow reaction rate mandated a real time method for monitoring of peroxide levels and to confirm reaction initiation. Raman spectroscopy is uniquely suited to H2O2 monitoring as the O−O bond is particularly Ramanactive. In the present reaction mixture, the symmetric stretch vibration of hydrogen peroxide at 874 cm−1 (Figure 2)11 is coincident with a much stronger peak from sulfolane.12 This impacted its limit of detection; however, the signal-to-noise was sufficient to detect levels greater than 0.1 equiv of H2O2.13 Sulfur-containing compounds also display significant Raman scattering.

Figure 4. Raman peak area trends of the H2O2 (874 cm−1), sulfide (1093 cm−1), and sulfone (1160 cm−1). The UHP addition events are annotated as (a) 1/8, (b) 1/8, (c) 1/4, and (d) 1/2 of the total amount of UHP.

spectrum, and the observed fluctuations of I0 could be corrected by normalization of the spectrum to the solvent (sulfolane) peak at 2950 cm−1 (Figure 5). Application of Raman spectroscopy to establish charging intervals was further complicated by an upward drift of the peroxide baseline as the reaction progressed. Several factors may account for this, such as a contribution in this region from the product or a change in the reaction from heterogeneous to a homogeneous solution. While the return of the peak area to its initial value is not a reliable measure of peroxide consumption, charging times could be established based on the observed decrease in reaction rate and/or a significant decrease in the peroxide peak intensity (>80%) compared to its initial value. The normalized Raman spectra for a 10 kg run are shown in Figure 5 with a total of 2.5 equiv of H2O2 broken into five portions (1/8, 1/8, 1/4, 1/2 of the total charge).15

Figure 2. Raman signals for sulfolane (dashed line) and a sulfolane/ H2O2 mixture (solid line).

Selected Raman spectral regions of the sulfide (1) and sulfone (3) in sulfolane solutions are shown in Figure 3. The

IR = K ·ν 4 ·P 2·N ·I0

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(1)

ν = Raman signal frequency P = Polarizability of molecule N = Number of scattering molecules I0 = Excitation light intensity IR = Raman signal light intensity K = Combined constant

DEVELOPMENT OF A QUANTITATIVE RAMAN MODEL We sought to extend this approach to a quantitative model for the later stages of process development and implementation with the objective of eliminating labor-intensive sampling and offline analysis. A univariate model was first applied using leastsquares regression to correlate the yield as determined by HPLC with the Raman data. Sampling of 10 data points during the calibration run afforded a linear correlation between the spectral and HPLC data (R2 = 1.000). This model was then applied to a second set of Raman data (test run). Validation of the univariate model was established by correlation between the yields predicted by the Raman model and yields determined by HPLC analysis of 10 test run samples taken. Figure 6 shows linear regression coefficients and R2 values for the calibration and test runs. Overall, the univariate model displays consistent and accurate prediction of sulfone (3) concentration between the two data sets, with some deviation observed early on in the reaction progression, likely attributable to heterogeneity of the system at this point in the reaction.

Figure 3. Raman spectra of sulfide 1 starting material and sulfone 3 solutions in sulfolane.

unique sulfide- and sulfone-related peaks can be identified near 1093 cm−1 (S−Ar ring vibration with C−S stretching, Ar: armomatic ring) and 1160 cm−1 (SO2 symmetric stretching), respectively, and are well resolved from solvent interference.14 A qualitative treatment of the Raman data with minimal upfront investment proved sufficient for our initial implementation of this chemistry. Univariate analysis of the peak area for each component was determined using a two-point baseline (see Figures 2 and 3). According to eq 1, direct correlation of peak area (related to IR) with concentration (related to N) requires variance of the other terms of eq 1 to be small. However, significant fluctuations in I0 were observed over the 21 h process that resulted in a disjointed reaction profile (Figure 4). Fortunately, the influence of I0 is linear across the 1808

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Figure 5. (A) Raman spectrum of sulfolane. (B) Raman peak area trends of the H2O2 (874 cm−1), sulfide (1093 cm−1), and sulfone (1160 cm−1) peaks after normalization using sulfolane peak (2950 cm−1). The UHP addition events are annotated as (a) 1/8, (b) 1/8, (c) 1/4, and (d) 1/2 of the total amount of UHP.

with data pretreatment to minimize baseline fluctuation and to scale both independent (spectral data) and dependent (% yield) variables at the same dimension.16 Using the multivariate PLS method, analysis of the experimental data used previously revealed a linear correlation for both the calibration and test runs (Figure 7). The PLS model displays consistent and

Figure 6. Linear correlation curve with regression coefficients between actual yield (HPLC assay) and the yield predicted by the Raman univariate quantitative model.

A multivariate data treatment incorporates a greater data set and may diminish the observed error introduced by the heterogeneity of the reaction mixture. To this end, a spectral range of 1120−1180 cm−1 was selected incorporating both the sulfide (1140 cm−1) and sulfone (1160 cm−1) peaks. A partial least-squares (PLS) algorithm was leveraged in combination

Figure 7. Linear correlation curve with regression coefficients between actual % yield obtained by quantitative HPLC assay and Raman quantitative PLS using one latent variable. 1809

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safe implementation of this large-scale H2O2-mediated reaction. The approach described for the intermediate scale process avoided the significant investment of a quantitative model by using qualitative trends from the observable species. As product demand and scale increased, the advantages offered by a real time in-process control and end-point determination warranted the increased investment required for generation and maintenance of a quantitative model. When the complexity of the system under study was considered, a univariate data treatment was found to be remarkably accurate in the later stages of the reaction; however, changes that were not captured by the calibration samples (such as dissolution of the starting material) led to reduced robustness. Multivariate models are considered to be more robust and better able to accommodate sample and parameter variation by taking into consideration a greater spectral range. Under these circumstances, we have found that a multivariate approach was capable of accommodating the initial heterogeneity of the reaction mixture, leading to a robust Raman model at all points along the reaction profile. Finally, the robustness of the model is an ongoing process in which additional calibration samples are included that cover variation in sample and reaction conditions not previously incorporated in the model.

accurate prediction of sulfone concentration between the two data sets during both the early stages of reaction where monitoring is complicated by heterogeneity as well as the middle and late stages of reaction. When the two models (Figure 8) are compared, the linear correlation of the Raman data and HPLC data appears to be

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EXPERIMENTAL SECTION A RAMANRXN1 Analyzer was used in experiment done in 50 g lab scale. A RAMANRXN3 system with Pilot-E probe was used in experiment done in 10 kg scale. Both Raman systems used for reaction monitoring are from Kaiser Optical Systems (Ann Arbor, MI). The spectrometers use 785 nm laser excitation with a power of 500 mW. Raman spectra were recorded with 3 s exposure, 5 accumulations, and 1 min interval by a TE cool charge-coupled device (CCD). To ensure the consistency of Raman spectra, the Raman spectrometer was calibrated for Raman shift using a neon lamp and Raman peak intensity response using a NIST traceable white-light source. Cyclohexane was used as standard for calibration of the laser wavelength. A cosmic ray correction function provided by icRaman v4.1 software was also used to remove random cosmic spikes from the CCD detector. The iC Raman version 4.1 software (Kaiser Optical Systems) was used to control the spectrometer. Qualitative analysis of the reaction process was achieved by tracking the Raman peak area of each component. Separated univariate and multivariate quantitative models were generated using the iC Quant function of the software. Reference concentrations of components used for quantitative model generation were obtained by HPLC analysis of supernatant of in-process thief samples. Typical Experimental Procedure: The catalyst mixture is prepared in advance in a round-bottom flask as an aqueous solution. To the large reactor are charged sulfide (1), sulfolane, and the catalyst solution, and the mixture is warmed to 30 °C. The Raman probe is then installed, and monitoring is started for the starting material, product, and peroxide. H2O2 is added to the reactor (1/8 of total charge) in a single portion to initiate reaction as observed by Raman, and then the remainder is added in portions, with the charging interval determined by the consumption of H2O2. The mixture is stirred overnight at 30 °C. Two 50 g scale experiments were conducted and monitored by a Kaiser RAMANRXN1 spectrometer. For those two batches, 10 thief samples were taken from the reaction vessel, and the samples were assayed by an HPLC method for sulfone

Figure 8. Comparison of HPLC assay yields from 10 thief samples (time points and yields indicated by arrows) with predicted reaction profiles as determined by univariate and multivariate analysis of Raman data.

similar; however, the multivariate model performs significantly better in the early stages of the reaction. Table 1 evaluates the accuracy and precision of the two quantitative Raman models for the test run over 60 measurements collected through the 17th hour of the reaction. Given that HPLC assays can carry up to 2% error, the average values from both models display remarkably similar accuracy. The % RSD of the predicted values through the plateau region at the 17th hour for 60 individual measurements is also similar for the two models, 0.52 and 0.33% for the univariate model and multivariate model, respectively. Moreover, improvement in % RSD can be achieved upon averaging of multiple measurements. Table 1. Prediction Based on Quantitative Raman Models at the 17th Houra average % RSD a

univariate (peak area)

multivariate (PLS)

99.0 0.52

100.6 0.33

Note: 99.5% final yield by HPLC.

The validity of quantitative models rests on control of the reaction parameters, that the composition of the analyte (test samples) fall within the design space of the model, and on the performance of the Raman spectrometer. For this study, tight control of reaction parameters impacting the Raman spectral features was maintained,17 and factors impacting Raman spectrometer performance18 were minimized by instrument performance calibration and intensity normalization. In spite of the complications of following such a dynamic system, Raman spectroscopy performed admirably for this real time reaction monitoring application and was successfully leveraged for the 1810

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(13) Based on signal-to-noise ratio analysis of the H2O2 result by Raman probe, the estimated detection limit is about 0.04 equiv of the total amount of H2O2. (14) Socrates, G. Infrared and Raman Characteristic Group Frequencies, 3rd ed.; John Wiley & Sons: New York, 2001. (15) Safe UHP charging regimen was determined based on calorimetry, vent sizing calculations, and reaction kinetics. (16) The raw data were treated with a first-order derivative process and a mean centering process. (17) Reaction parameters that were controlled included temperature, stir rate, and composition of reactants. (18) Factors that impact the Raman spectrometer and can be corrected for by instrument calibration and spectral normalization include Raman shift accuracy, detector response, and laser excitation intensity.

concentrations at moments of sampling. Data from the two 50 g batches were used for the quantitative Raman method development and validation.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. Present Address †

Steven Shaw: Ash Stevens Inc., 18655 Krause Street, Riverview, MI 48193. Notes

The authors declare no competing financial interest.

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REFERENCES

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