High-Throughput Extractions: A New Paradigm for Workup

Aug 25, 2016 - In the pharmaceutical industry, high throughput (HT) technology is well developed and routinely utilized in chemical process developmen...
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High-Throughput Extractions: A New Paradigm for Workup Optimization in Pharmaceutical Process Development Joshua A. Selekman,*,† Kristy Tran,*,† Zhongmin Xu,† Michael Dummeldinger,† Susanne Kiau,† Joseph Nolfo,‡ and Jacob Janey† †

Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States ‡ Research & Development IT, Bristol-Myers Squibb Company, P.O. Box 4000, Princeton, New Jersey 08543, United States S Supporting Information *

ABSTRACT: In the pharmaceutical industry, high throughput (HT) technology is well developed and routinely utilized in chemical process development for reaction optimization and isolations via crystallization. However, fewer HT technologies have been employed in the development of workup procedures, bridging optimized reaction and isolations. Frequently, extensive workups involving numerous unit operations are required to remove reaction stream components, such as impurities, solvent, and catalyst, prior to isolation. Herein, we describe a systematic yet flexible approach using designed experimentation, laboratory automation, and parallel experimentation to quickly and efficiently optimize unit operations that are required post reaction to remove reaction stream components (e.g., impurities, metal catalysts, solvent). This novel high throughput extraction (HTEx) platform has shown potential to broadly impact development by faster and more robustly improving process greenness, process mass intensity (PMI), cycle time, and ease of operation.



and cycle time.7 Taken together, multiple qualities of a phase split must be investigated in parallel to develop an efficient, operationally friendly extraction process. Given the complexity of having multiple input parameters to a workup and the single or combinatorial impacts of these inputs on multiple responses, an approach toward optimization of a workup procedure would benefit from a multivariate analysis requiring parameter variation data. In this light, laboratory automation has shown to be advantageous for pharmaceutical process development, specifically for the generation of large arrays of parallel experiments to investigate comprehensive design spaces and/or operating ranges for reactions and crystallizations.2,8−15 The execution of these high-throughput studies can often expedite the knowledge generation for the development and/or optimization process for producing drug substance or drug product, ultimately enabling the delivery of material within ever accelerating timelines.4,16 While the utilization of laboratory automation and highthroughput approaches are common throughout the pharmaceutical industry for developing and optimizing both chemical reactions and crystallizations, no methods have been reported to automate high-throughput studies for developing and optimizing workups to maximize removal of undesirable reaction stream components. Herein, we outline a new systematic approach to advance development of and optimize phase splits and extractions. This approach leverages screening strategies, statistical design of experiments (DoE), laboratory automation, and parallel experimentation as a natural extension and complement to current workflows for reaction and

INTRODUCTION Chemical processes developed for producing small molecule pharmaceuticals routinely involve a chemical reaction to generate the requisite compound of interest, a workup to remove impurities and other undesirable components from the reaction stream and an isolation via a crystallization. Ideally, a “bottom up approach” would be implemented wherein reaction and isolation conditions would be harmonious to allow for the direct crystallization of the requisite compound while expunging all other impurities and solvent.1 In reality, however, optimized reaction conditions are tuned for maximizing yield and minimizing key impurities while on the back end, there are significant efforts toward designing and optimizing crystallization processes with respect to quality and yield, as these operations act as quality gatekeepers.1−6 As such, a gap frequently exists between the reaction conditions and the conditions required for the final isolation. Failing a direct isolation, a series of workup operations are often required to remove byproducts, solvent and catalyst prior to isolation of high quality material, as defined by specifications and standards approved by the various regulatory organizations.4 These workups typically exist in the form of extractions (either liquid−liquid or solid−liquid) and phase splits prior to the final isolation. In addition to achieving adequate purging or removal of a reaction stream component, these extraction operations must also minimize product loss, operate within equipment related constraints, carry minimal risk of forming emulsions and, if possible, meet certain criteria with respect to “ease of operation” including minimal rag layer, clear phase cut by observation, and adequate phase color differential. Optimal workup conditions can also result in a “greener” process by reducing waste, process mass intensity (PMI), energy usage, © 2016 American Chemical Society

Received: June 27, 2016 Published: August 25, 2016 1728

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Mylar. Each sample was individually run in triplicate on an Olympus-Innov-X 5000 field portable EDXRF unit to determine Pd content. Settling time. Expanding upon this outlined approach for advancing process development with respect to extraction optimization, additional measures have been developed for exploring additional operational considerations. For example, utilizing video capture to observe the phase separation process following the stoppage of agitation can be used to assess the time required for the phases to fully separate. Given the measured settling time as well as the calculated height/volume of the phases in a scaled-down system, settling velocity for each phase split can be calculated. Furthermore, this settling velocity, defined in mm/sec, can be translated to larger reactor vessels with known geometry to make on-scale predictions of the time required for phase splits to occur (See Supporting Information for calculations). Data Analysis. Data was compiled and subsequently imported into JMP10 and Spotfire software programs for statistical analysis and visualization.

crystallization development and optimization of phase splits and extractions. In addition, we highlight the versatility of this high throughput extraction (HTEx) approach by outlining three case studies where this approach was applied to address three distinct, and fundamentally different, challenges in meeting quality requirements for producing three separate API materials.



MATERIALS AND METHODS Parallel Extraction Preparation. Parallel extractions are prepared in 8 mL glass vials by dispensing an equal portion of the reaction stream to each vial. Subsequently, additional components (e.g., aqueous solution, scavengers) are added for the extraction study, exact amounts of which are determined by the specific experimental design. Magnetic stir bars are added to each vial and the vials are then placed in 24-well metal plates. Each plate is mounted onto a magnetic stir plate or loaded onto a heating−cooling-stirring deck on an automated reaction platform with sufficient agitation to ensure adequate mixing of phases. Temperature and stir rate are then programmed according to the experimental design. Organic and Aqueous Phase Sampling. At each relevant time point, as defined by the experimental design, samples of the organic and, if necessary, aqueous phases are taken from each vial and subsequently dispensed at a designated location on an HPLC receiver plate. In the HPLC receiver plate, samples are diluted into a diluent, specific to the HPLC method used. Sample transfer was performed using the liquid handling capabilities of the automated equipment used. Specifically, a 16 gauge needle pierces through the septum in the vial cap and extracts a designated volume of the phase to carry (typically 20−50 μL). A backing solvent is chosen based on the solvent(s) used in each experiment. Diluted samples on the HPLC receiver plate were further diluted if necessary and run on an HPLC with a designated method for that particular reaction stream. Partition Coefficient or Removal Efficiency Calculation. Measurement lines on the visualization plate allow for the assessment of phase volume and height via visual analysis. Partition coefficient and removal efficiency in each extraction was calculated based on the volume of each phase and the concentration of the component of interest, as measured by HPLC. Phase Split Visualization. To assess the operational considerations of phase splits at various conditions, 6 vials at a time were loaded onto the custom phase visualization plate, a reaction block specifically designed to visualize phase splits, (see Supporting Information), mounted on a magnetic stir plate. This phase visualization plate was designed for rapid inspection of vial contents for volume, color, clarity, and the extent of a rag layer presence. It has a capacity of six vials arranged in a single row so all can be inspected simultaneously. It is fabricated from 6061-T6 aircraft aluminum using traditional machining methods and is made up of a two part assembly. The base has wells with cut outs to hold the vials in place while still giving the ability for the user to see through to the back plate. The back plate has black highlighted measurement lines for every half milliliter ranging from 0 to 8 mL to quickly assess volumes of each phase present. X-ray Fluorescence (XRF). To determine palladium (Pd) content in various process stream samples, XRF measurements were made as previously reported.17 In brief, 2 mL of each liquid sample was dispensed into a sample cup, sealed with



RESULTS AND DISCUSSION High Throughput Extraction Approach. In an effort to improve development efficiency for extraction operations in such a chemical process, a systematic approach was developed to optimize extractions with respect to maximizing removal of undesirable process stream components and, within these constraints, minimizing the operational burden. This HTEx approach employs various experimental design strategies while leveraging lab automation and parallel experimentation to investigate large arrays of extractions to find the optimal conditions, or inputs, necessary for achieving adequate removal of undesirable process stream components (Figure 1). This approach involves first optimizing a workup with respect to discrete or class variables (e.g., solvent, scavenger, base, acid) followed by further optimization with respect to continuous variables (e.g., organic/aqueous ratio, pH, volumes, temperature, time, etc.) to maximize removal of a component

Figure 1. Process diagram for the HTEx approach for extraction development and optimization. 1729

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Figure 2. Mesylation reaction to produce a process intermediate.

Figure 3. Workup procedure for removing GTI and DIPEA from the reaction stream prior to isolation.

solvent removal using liquid−liquid extraction. The third and final case study focuses on the removal of a catalyst and how the HTEx approach identified the critical parameters for improving residual catalyst removal. Taken together, these three case studies demonstrate the impact and versatility of HTEx and its application in improving or optimizing the workup conditions to achieve a variety of different and distinct objectives. Case Study 1: Removal of Genotoxic Impurity and Residual Base. The first case study highlights how this approach found improved conditions for removing residual base and a genotoxic impurity (GTI) from a process stream. In the chemical synthesis of an API, one critical step involves an alkylation using a mesylate species in the presence of N,Ndiisopropylethylamine (DIPEA) in dichloromethane (DCM) (Figure 2). The mesylate compound in this chemical reaction has shown to be a GTI, so it is therefore critical to ensure that the amount of this species in the isolated product is within the specification limit ( 10 N/A 1 1 1.5 2 2.5

good good good good good good good good good good good good good good fair poor fair fair good good good

Table 3. Extraction Study of KOBz Wash 8 vol 1N

8 vol 1N

8 vol 1N

KOBz

NaOH

KOBz

KOBz

stream concentration

8 vol DCM

16 vol DCM

8 vol DCM

16 vol DCM

scale (g) setting time (sec) organic layer length (mm) aqueous layer height (mm) reactor diameter (mm) setting velocity (mm/s) estimated pilot (∼400L) plant split time (min)

0.01 30 11 14 8 0.36 51

5.0 > 3600 130 66 160 0.018 > 1020

5.0 300 130 66 160 0.22 88

5.0 40 130 66 160 1.67 11

hydroxide control case which had a fair phase split quality with a moderate rag layer and a 1 min settling time. Encouraged by these results, sodium benzoate (NaOBz) and potassium benzoate (KOBz) were further investigated on larger scales as potential alternatives to NaOH and a more reliable and robust workup operation. The performance of the workup using these new conditions identified in the parallel phase split study were evaluated on scales of 10g−200g to assess the critical aspects of this workup including mesylate decomposition, DIPEA removal, and phase split quality (see Supporting Information for additional details of these followup studies). These follow-up studies determined that KOBz outperformed the NaOBz in terms of these critical parameters. With respect to GTI removal, it was determined that hydrolysis of the mesylate species is scale independent. Specifically, at 100fold greater volume than in the HTEx study, it was shown that adding an equal volume of DCM and twice the volume of 0.5N KOBz solution to the reaction stream at 30 °C for 90 min effectively removed the mesylate to ∼140 ppm levels, consistent with the results from the HTEx study. Interestingly, despite the weaker basicity, KOBz shows similar effectiveness in decomposing mesylate to alcohol as NaOH. This effectiveness may be attributed to the considerably higher solubility of KOBz in DCM thereby increasing the effective concentration of base

8 vol 1N

in the organic layer. Due to the lower pH of the aqueous KOBz solution, the DIPEA purge in the subsequent scale-up experiments ranged between 90 and 100% compared to 11-fold improvement in settling time from a calculated 1020 to 88 min on pilot plant scale (Table 3). Additionally, it was observed that greater dilution of the reaction stream with DCM prior to washing with aqueous KOBz was found to further improve split efficiency with respect to settling velocity. As shown in Table 3, the phase split was by far more facile for the diluted stream, and required 40 s, which translates to ∼11 min on pilot plant scale compared to ∼88 min predicted in an undiluted reaction stream, given settling time measured and pilot plant vessel geometry. In addition, very little rag layer formed in diluted stream, which results in ∼5% increase in yield compared to the original conditions. Using an HTEx study, a final workup procedure involving increased dilution of DCM of the reaction stream and three successive 8 L/kg washes consisting of 10% HOAc, 1N KOBz, and water was quickly discovered and successfully executed on laboratory scale (Figure 5). This refined workup procedure is set for implementation on pilot plant scale (∼50 kg) with a 25% reduction in projected PMI and cycle time, showcasing the potential of HTEx. 1732

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aqueous portion of this biphasic mixture is discarded and the process is repeated for a total of six extraction operations. Due to certain operational constraints, specifically the Vmax and waste generation, improvement of this undesirable process is a worthy goal. In an attempt to refine this process to achieve a more efficacious NMP removal while maintaining minimal product loss to the waste streams, the HTEx approach was employed. For this study, several aqueous systems as alternatives to water were investigated. In addition, continuous factors, such as the relative amounts of the organic phase, aqueous phase, and DCM added, were investigated, as were total volume and the addition of KCl. To investigate both discrete and continuous variables, a hybrid screening/DoE approach was used and an experimental design was generated (Table 4). In the experimental design, the first experiment, Vial 1, represents the current (baseline) conditions for the process. Vials 2−7 explore alternative aqueous systems. The remainder of the experimental array consists of a custom, D-optimal DoE design to explore the continuous factors with three alternative aqueous systems (KOH, K2CO3, and K3PO4), as well as the addition of KCl to the biphasic mixture. An organic stream was divided into 24 separate vials and the appropriate amounts of DCM, aqueous phase, and KCl were added according to the experimental design. The vials were loaded onto an automated platform and agitated overnight at 25 °C. Following overnight incubation, agitation was ceased, allowing the phases to split. To visualize the quality of the phase splits, images were taken of each vial (Figure 6). For operational considerations, the split clarity, phase colors, and the presence (or absence) of a rag layer were recorded and tabulated (Table 5). After allowing the phases to split, the heights of the phases in each vial were measured and the volumes of each phase were

Figure 5. Refinement of workup process following the HTEx approach.

Case Study 2: Removal of Solvent. Removing solvent from a process stream is often necessary prior to isolating a process intermediate or an API. In some cases, an extraction can be the most efficient and effective process of removing a solvent. The second case study illustrates how the HTEx approach can be applied to maximize solvent removal without compromising significant product yield loss. In this particular case, NMP is utilized as a reaction solvent in the production of an API and must be removed prior to the crystallization. As a result of the high boiling point and water solubility of NMP an aqueous extraction is necessary to replace the organic solvent with DCM. In this manner water and DCM is added to the process stream following the reaction to remove the NMP. The

Table 4. Screening/DoE Array of Experiments To Investigate Effects of Various Factors on NMP Removal vial

aqueous system

pH

organic, mL/g

aqueous, mL/g

DCM, mL/g

total volume, mL/g

KCl added?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

water LiOH NaOH CaOH KOH K2CO3 K3PO4 Water KOH K2CO3 K3PO4 water KOH K2CO3 K3PO4 KOH K2CO3 K3PO4 KOH K2CO3 K3PO4 KOH K2CO3 K3PO4

8.6 12.2 12.9 12.4 13.5 11.4 12.8 8.6 13.5 11.4 12.8 8.6 13.5 11.4 12.8 13.5 11.4 12.8 13.5 11.4 12.8 13.5 11.4 12.8

20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20

20 20 20 20 20 20 20 20 20 20 20 10 10 10 10 10 10 10 10 10 10 20 20 20

20 20 20 20 20 20 20 20 20 20 20 10 10 10 10 10 10 10 20 20 20 10 10 10

60 60 60 60 60 60 60 60 60 60 60 60 40 40 40 40 40 40 50 50 50 50 50 50

no no no no no no no yes yes yes yes no no no no yes yes yes no no no no no no

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Figure 6. Visualization of phase split quality for all aqueous systems studied.

Table 5. Qualitative Observations of Phase Splits vial

split clarity

triphasic?

bottom phase color

rag layer?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

clear clear clear clear clear clear clear clear clear clear clear clear clear clear clear fair fair clear clear clear clear clear clear clear

no no no no no yes yes no no yes yes no no yes no no no no no yes yes no yes yes

yellow amber yellow amber yellow yellow/amber yellow/amber dark yellow amber amber/amber yellow/amber amber dark amber clear/amber yellow dark amber yellow yellow amber clear/amber clear/amber amber clear/amber clear/amber

no no no yes no no no no no no no no no no no yes yes yes no no no no no no

Figure 7. % NMP removal vs % yield loss for various aqueous systems. The number next to each data point refers to the vial number. Refer to Table 4 for operating conditions in each vial.

water with 1.0 M KCl (Vial 8, blue data point), each at a total volume of 60 L/kg offered comparable yield losses with greater NMP purge. Specifically, these three alternative aqueous systems provided 32−37% removal of NMP in a single extraction compared to 24% of NMP removed using water. Yield losses for these three systems were only slightly higher (7−9%) compared with water (6%). Operationally, the split in each of these systems is clear and distinct, with no rag layer observed (Figure 7). With respect to the continuous variables, there is a clear correlation between NMP removal and the amount of DCM added to the reaction stream wherein more DCM results in higher NMP removal (Figure 8A). In addition, adding fewer aqueous volumes results in lower yield loss (Figure 8B). These results suggest that using 1 M KOH, 1 M NaOH, or 1 M KCl in water as aqueous system alternatives may be advantageous for improving the efficiency of NMP removal. This study identified these potential alternatives and motivated follow-up experiments to optimize operations to a single

subsequently calculated from the known vial parameters. In addition, each phase of each vial was sampled and run on an HPLC to determine NMP content and the amount of product present. Given the volume of each phase and the concentration of product and NMP in each phase, the amount of NMP purged from the organic phase and the yield loss were calculated and plotted (Figure 7). Compared to the baseline conditions using water at a total volume of 60 L/kg (Vial 1, red data point), many alternative systems offered increased NMP purge, but at the cost of higher yield losses in the aqueous phase. However, 1 M KOH (Vial 5, blue data point), 1 M NaOH (Vial 3, blue data point), and 1734

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Figure 8. (A) NMP removal vs DCM volumes and (B) yield losses vs aqueous volumes.

A process stream was divided into 16 parallel vials, each containing specified amounts of water and NAC and incubated at the specified temperature and for the appropriate duration according to the experimental design. The biphasic mixtures were incubated on an automated platform with agitation. After incubating for the specified time, agitation was stopped, allowing the phases to settle. The split quality of each experiment was observed (Figure 9). All vials split satisfactorily with the exception of Vial 3 (Figure 9), which was operated at the corner of the design space with lower amounts of water (9 vol) and NAC (1 g/g) and at higher temperature (50 °C). After allowing the phases to split, the aqueous layer was removed from each vial and organic stream samples were analyzed via XRF to determine Pd content in the organic phase. A visualization of the Pd content measured in each organic phase was then generated (Figure 10). Based on the data visualization image in Figure 10, water and temperature appear to have a profound effect on Pd content in the organic stream. Specifically, the vials that received more water (>9 vol) contained higher Pd content in the organic phase. In addition, biphasic mixtures that were incubated at a higher temperature (red data points, 50 °C) generally had higher Pd levels in the organic phase. The amount of NAC added, within the ranges explored in this study, did not appear to have an effect on Pd removal. To support these observations, a statistical analysis of these results was performed using JMP10 software (Figure 11). The statistical analysis investigating the impact of single factors and the two-way interactions on Pd content indicates that temperature and water are, in fact, significant with respect to impacting Pd content. Specifically, higher temperature and higher water content results in higher Pd content. This confirms what can be observed in the data visualization in Figure 10. In addition, the statistical analysis identified another significant factor, a two-way interaction between temperature and time, which is not necessarily intuitive when visualizing the data. Taken together, these results suggest that adding less water to the organic stream and incubating at a lower temperature during the biphasic mixing will maximize Pd removal from the process stream. The results from this HTEx study not only elucidated the significant factors in impacting Pd removal within a comprehensive design space, but also was confirmed on 15 g scale, motivated additional HTEx studies

extraction. Specifically, the results from this HTEx study enabled the design of more focused studies in manipulating continuous variables (volumes, concentration, temperature, and time) to maximize NMP purge and minimize yield losses. This increase in efficiency for a single extraction could ultimately reduce the Vmax and potentially reduce the number of extractions required to fully remove NMP from the process stream. A reduction in either of these operational parameters would also reduce the waste generation from this process offering a “greener” process. Case Study 3: Removal of Catalyst. The third and final case study focuses on an intermediate chemical step that involves a palladium (Pd) catalyst for a transformation. As is the case with all APIs strict quality specifications with respect to metal content is required. Thus, it is imperative to remove the Pd from the process stream prior to isolation. To remove Pd, the procedure calls for the addition of solid N-acetylcysteine (NAC) and water to the organic process stream. Given the various factors involved in this process, including the amount of NAC and water added, temperature, and incubation time, a full factorial DoE was used as a design for an HTEx study in an attempt to maximize Pd removal for this process (Table 6). Table 6. DoE Design To Investigate Factor Effects on Pd Removal vial

NAC, g/g

water, mL/g

temperature, °C

incubation time, hr

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2

9 9 9 9 12 12 12 12 9 9 9 9 12 12 12 12

25 25 50 50 25 25 50 50 25 25 50 50 25 25 50 50

1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 1735

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Figure 9. Visualization of phase split quality for the experiments incubated for 1 h.

Table 7. Palladium Levels of NAC Extractions Over Time at 40 °C Pd (ppm) scale 1 2 3 4

h h h h

HTEx 0.01g

reactor 15g

470

501 427 356 306

295



CONCLUSIONS Herein, we showcased a new, systematic approach to optimizing workups and extractions by leveraging statistical experimental design, parallel experimentation, and laboratory automation. We demonstrated how HTEx can be applied to help develop workup operations to achieve a variety of specifications. Expanding upon this outlined approach for advancing process development with respect to extraction optimization, additional measures have been developed for exploring an expanded set of operational considerations. For example, utilizing video capture to observe the phase separation process following the stoppage of agitation can be used to assess the time required for the phases to fully separate. Given the measured settling time as well as the calculated height/ volume of the phases in a scaled-down system, settling velocity

Figure 10. Pd content vs water volumes, temperature, and incubation time.

and served as a guide for focused follow-up experiments to continue the pursuit of a robust, optimized workup process (Table 7).

Figure 11. Screening analysis calculating the statistical significance of how each factor impacts Pd removal. 1736

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(13) Kumar, L.; Amin, A.; Bansal, A. K. Drug Discovery Today 2007, 12, 1046. (14) Murray, P. M.; Tyler, S. N. G.; Moseley, J. D. Org. Process Res. Dev. 2013, 17, 40. (15) McMullen, J. P.; Jensen, K. F. Annu. Rev. Anal. Chem. 2010, 3, 19. (16) Rubin, A. E.; Tummala, S.; Both, D. A.; Wang, C.; Delaney, E. J. Chem. Rev. 2006, 106, 2794. (17) Lewen, N.; Soumeillant, M.; Qiu, J.; Selekman, J.; Wood, S.; Zhu, K. Org. Process Res. Dev. 2015, 19, 2039.

for each phase split can be calculated. Furthermore, this settling velocity can be translated to larger reactor vessels with known geometry to make on-scale predictions of the time required for phase splits to occur. In addition, advancing automation for video capture of parallel streams, volumetric determinations, and color quantitation would be highly useful in building upon current capabilities to streamline high-throughput methods for workup and overall process development.



ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.oprd.6b00225. Additional information from Case Study 1, images of the phase split visualization plate, and detailed HPLC and GC methods (PDF)



AUTHOR INFORMATION

Corresponding Authors

*Telephone: (732) 227-5441; E-mail: joshua.selekman@bms. com. *Telephone: (732) 227-6990; E-mail: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The authors would like to acknowledge Fred Roberts and Jeff Nye for their contributions in the first case study; Michaël Fenster and Zhongping Shi for their collaboration on the work with the second case study; Eric Huang, Maxime Soumeillant, Jun Qiu, and Carolyn Wei for their collaborations on the third case study; Joerg Deerberg for helpful discussions; and Freeslate for their help in supporting Core Module 3 operation.



REFERENCES

(1) Chen, C.-K.; Singh, A. K. Org. Process Res. Dev. 2001, 5, 508. (2) Selekman, J. A.; Roberts, D.; Rosso, V.; Qiu, J.; Nolfo, J.; Gao, Q.; Janey, J. Org. Process Res. Dev. 2016, 20, 70. (3) Hsieh, D. S.; Huang, J.; Roberts, D.; Gao, Q.; Ng, A.; Erdemir, D.; Leahy, D.; Li, J.; Huang, M.; Lai, C. Cryst. Growth Des. 2012, 12, 5481. (4) McKenzie, P.; Kiang, S.; Tom, J.; Rubin, A. E.; Futran, M. AIChE J. 2006, 52, 3990. (5) Schmink, J. R.; Bellomo, A.; Berritt, S. Aldrichimica Acta 2013, 46, 71−80. (6) Santanilla, A. B.; Regalado, E. L.; Pereira, T.; Shevlin, M.; Bateman, K.; Campeau, L.-C.; Schneeweis, J.; Berritt, S.; Shi, Z.-C.; Nantermet, P.; Liu, Y.; Helmy, R.; Welch, C. J.; Vachal, P.; Davies, I. W.; Cernak, T.; Dreher, S. D. Science 2015, 347, 49−53. (7) Dunn, P. J.; Wells, A.; Williams, M. T. Green chemistry in the pharmaceutical industry; John Wiley & Sons, 2010. (8) Gardner, C. R.; Almarsson, O.; Chen, H.; Morissette, S.; Peterson, M.; Zhang, Z.; Wang, S.; Lemmo, A.; Gonzalez-Zugasti, J.; Monagle, J.; Marchionna, J.; Ellis, S.; McNulty, C.; Johnson, A.; Levinson, D.; Cima, M. Comput. Chem. Eng. 2004, 28, 943. (9) Gu, C.-H.; Li, H.; Gandhi, R. B.; Raghavan, K. Int. J. Pharm. 2004, 283, 117. (10) Rosso, V. W.; Pazdan, J. L.; Venit, J. J. Org. Process Res. Dev. 2001, 5 (3), 294−298. (11) Morissette, S. L.; Almarsson, Ö .; Peterson, M. L.; Remenar, J. F.; Read, M. J.; Lemmo, A. V.; Ellis, S.; Cima, M. J.; Gardner, C. R. Adv. Drug Delivery Rev. 2004, 56, 275. (12) Aaltonen, J.; Allesø, M.; Mirza, S.; Koradia, V.; Gordon, K. C.; Rantanen, J. Eur. J. Pharm. Biopharm. 2009, 71, 23. 1737

DOI: 10.1021/acs.oprd.6b00225 Org. Process Res. Dev. 2016, 20, 1728−1737