Statistical DoE Approach to the Removal of Palladium from Active

Article pubs.acs.org/OPRD

Statistical DoE Approach to the Removal of Palladium from Active Pharmaceutical Ingredients (APIs) by Functionalized Silica Adsorbents Jan Recho,* Richard J. G. Black, Christopher North, James E. Ward, and Robin D. Wilkes PhosphonicS Ltd., 44c Western Avenue, Milton Park, Abingdon, OX14 4RU, United Kingdom S Supporting Information *

ABSTRACT: The influence of four parameters (temperature, scavenging time, amount of scavenger, and concentration of palladium in the solution) on the efficiency of Pd removal from a cross-coupling reaction, using a commercially available Pd scavenger, SPM32, was studied. The DoE-based method employed yielded more information than is readily attainable from standard adsorption isotherms and kinetics experiments. The optimal regime of scavenging was identified; intuitive and nonintuitive effects of temperature, scavenging time, and scavenger amounts were highlighted; and a mathematical model quantifying predicted Pd removal from the synthetic intermediate was built.

1. INTRODUCTION In recent years, the use of transition metal-mediated reactions has become common in large scale active pharmaceutical ingredient (API) synthesis due to the wide array of organic chemistry transformations that these metals can catalyze.1,2 Among transition metals, palladium plays a prominent role in modern organic chemistry, with commonly used Pd-catalyzed reactions including hydrogenations, carbon−carbon crosscouplings (Sonogashira, Suzuki, Heck, Stille, Hiyama), carbon−heteroatom couplings (Buchwald-Hartwig), functional group deprotections and cyclization reactions. While this versatile methodology has provided organic chemists with exciting new possibilities, it has also presented a new challenge of removing the traces of Pd left in solution after the reaction.3,4 The toxicity of Pd has led major regulatory and advisory bodies (EMEA,5 ICH6) to issue tight guidelines, with the EMEA, for example, advising an oral concentration limit of 5 mg/kg, and a parenteral concentration limit of 0.5 mg/kg for Pd in drugs. The presence of additional Pd residues in synthetic intermediates can also affect the subsequent steps in a synthesis, catalyzing the formation of unwanted side products and impurities.7 To address these regulations, several strategies are used by process chemists to remove Pd impurities.4,8 In cases where Pd is not tightly bound to the API, or where the Pd species present can be easily removed, a simple solution can sometimes be found, such as an aqueous wash, distillation, crystallization,9 or adsorption onto activated charcoal.10 Other methods to work around the problem include using alternative synthetic routes11 or heterogeneous catalysis,12−14 but both of these options present additional consequences. In many cases, the metal is tightly bound to the API, and removing it presented a significant challenge, prompting long and costly studies.15 This is especially true for densely functionalized synthetic intermediates made for particular applications within the pharmaceutical industry. Indeed, some of the most common functional groups that provide biological affinity or performance tend to feature combinations of heteroatoms and electron-rich moieties © 2014 American Chemical Society

that bind strongly to metal residues. Removing the catalyst with high affinity metal scavengers containing functional groups which can effectively compete to remove the metal from the API is often then the only viable solution. Functionalized silicas are well-known as efficient metal scavengers and can be used in both small scale and large scale operations,16−19 either in batch or in continuous (cartridge) format.16,20 Silicas are stable in all of the common organic solvents, as well as in aqueous solutions (provided pH < 9); they do not swell, generate low back pressure (if any) in a cartridge, and their high porosity provides ample surface area for optimal contact between the scavenger functional groups and the API solution.21 However, while the use of functionalized silicas as scavengers to solve Pd removal issues is everincreasing, to the best of our knowledge very few quantitative studies have been conducted on their scale-up and to understand the parameters affecting Pd removal. One such study of note has been carried out by Girgis et al.,22 although the focus was less on characterization of the scavenging operation itself, but more on the transition from a batch mode of operation to a continuous-flow, cartridge-based mode of operation.16 This paper describes a systematic study of the influence of several key parameters on the scavenging of Pd from an organic product solution using functionalized silica scavengers, with the aim of building a mathematical model to quantitatively describe the scavenging operation. While this paper provides valuable insights into which parameters should be carefully monitored by process chemists when scaling up a Pd scavenging operation, it should be noted that by their very nature, such operations are very dependent upon the type of scavenger used, the nature and speciation of the metal, and the nature of the product solution to be scavenged. The relative importance of each parameter might be expected to change from one product solution to the other, and from scavenger to scavenger. The Received: January 29, 2014 Published: April 14, 2014 626

dx.doi.org/10.1021/op5000336 | Org. Process Res. Dev. 2014, 18, 626−635

Organic Process Research & Development

Article

threshold of 15% Pd retained in the product solution after workup was chosen. (3) The solution had to strongly retain Pd so that a metal scavenger would be required for its effective purification. To assess this criterion, a kinetics test was conducted on candidate product solutions using 2 mol equiv of the scavenger, SPM32. Those from which more than 60% of the Pd was removed within the first hour were rejected on the basis that they were insufficiently powerful to compete with the scavenger for Pd. A number of product solutions were trialed against these three requirements, either by using the crude product of a wellknown Pd-catalyzed reaction (Suzuki, Heck, amino acid Ndebenzylation) or by directly dissolving a molecular species bearing potential Pd chelating functionalities in an appropriate solvent (see Supporting Information, section 6, for details). The crude reaction product of the Buchwald-Hartwig crosscoupling reaction to give N-aryl-α-amino acid 3 met these criteria and was chosen as the reaction partner for this DoE study (Scheme 1).

general methodology employed, however, is intended to be adaptable to other solid phase scavengers, other metals, and other product solutions.

2. RESULTS AND DISCUSSION Building a mathematical model to represent Pd adsorption onto a scavenger required several steps: (1) selection of one scavenger23 and a model product solution from which to scavenge the Pdthe model solution should realistically reflect the characteristics of a synthetic intermediate; (2) characterization of the interaction between the product solution and the scavenger following an accepted process; (3) study of the scavenging process and identification of the key parameters that affect scavenging, which will be incorporated into the study; (4) identification of a suitable Design of Experiment (DoE) design space: the ranges over which each of the previously identified parameters will be studied, allowing a mathematical model to be built that can accurately model Pd adsorption from the chosen API-like molecule, depending on the variations of the chosen parameters. 2.1. Development of a Suitable API Intermediate/ Scavenger System Mimic. This study focused on Pd contamination of API-like products because Pd is widely used in organic synthesis,1,2 and its removal is therefore an important challenge for the pharmaceutical industry to overcome. PhosphonicS SPM32 scavenger was chosen for this study, as it is used in both academia24 and within the pharmaceutical industry and has been incorporated into the purification of a number of APIs by both pharmaceutical and biotechnology companies,25 including at the multikilogram scale.16 Although other options are available and used at scale,26 SPM32 is one of the most efficient scavengers for Pd removal from APIs, consistently achieving suitable Pd removal and proving robust under most operating conditions. The differentiating factor of PhosphonicS technology is the presence of additional heteroatom functional groups within the linker to the surface of the silica support. For SPM32, this appears as a dialkyl sulfide group providing an extra ligand binding site for Pd (Figure 1), in addition to the terminal thiol functionality which is present in competitors’ materials.

Scheme 1. Buchwald-Hartwig Reaction, the Crude Product of Which Was Used as a Model Solution for This Study

All of the reaction components are readily available, a high amount of Pd (typically 400−500 mg/kg) was consistently retained in the product solution, and the product was sufficiently competitive for Pd in the above-mentioned kinetics test. Furthermore, N-aryl-α-amino acids are a synthetically valuable group of building blocks used in the preparation of a number of biologically important molecules.28 The experimental procedure for this reaction is described in the Supporting Information. A two-step filtration of the crude reaction solution, first though a 10 μm pore sized sintered funnel, then through a 0.1 μm nylon filter to remove any suspended matter (mainly cesium carbonate, which is only sparingly soluble in toluene), results in a clear solution. This provided a study medium which was found to contain 426 mg/ kg of Pd. This concentration can be easily tuned by concentration or simple dilution in toluene. 2.3. Initial Characterization of the System. An accepted procedure to characterize the adsorption of a metal from the liquid phase onto a solid surface is to study the kinetic and thermodynamic properties of the adsorption under controlled conditions.22,29−31 An adsorption isotherm describes the equilibrium reached during the adsorption process at a constant temperature. Three useful pieces of information are thus generated: the efficiency of metal removal from the liquid phase as a function of the quantity of scavenger present; the overall potential of the scavenger for removing metal from solution (i.e., the final concentration of metal in solution at equilibrium); and an indication of the maximum loading of metal onto the scavenger using an excess of metal with respect to the scavenger. An isotherm curve describing the equilibrium state for the interaction of Pd scavenger SPM32 with a toluene solution of N-aryl-α-amino acid 3 was generated at 60 °C and is shown in Figure 2.

Figure 1. PhosphonicS SPM32 Pd scavenger.

Scavenger screening studies within the pharmaceutical industry have regularly found SPM32 and other multifunctional silica scavengers to be more efficient for Pd removal and a computational study has recently been conducted to better understand the importance of the thioether unit in this regard.27 The functional group loading (FGL) of the SPM32 scavenger comprises between 0.8 and 1.1 mmol of functional group per gram of silica, with the FGL of the particular batch of scavenger used in this study measured at 0.93 mmol/g (see section 2, Supporting Information). In order to pick an appropriate molecule featuring API-like functionality for the study, the following characteristics were deemed necessary: (1) The chemical composition of the solution had to be viewed as a realistic model of a synthetic intermediate by pharmaceutical chemists. (2) The concentration of retained Pd in solution had to be sufficiently high that it could be easily tuned to fit the study’s needsa lower 627



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Figure 2. Isotherm curve for the scavenging of the crude Buchwald-Hartwig product with PhosphonicS SPM32 scavenger (60 °C, 24 h contact time). Pd concentration before scavenging co(Pd) = 393 mg/kg.

Figure 3. Kinetics curve for the scavenging of the Buchwald-Hartwig product with PhosphonicS SPM32 scavenger (60 °C, 3 ME of SPM32 vs Pd, 300 rpm agitation speed). Pd concentration before scavenging co(Pd) = 393 mg/kg.

important parameters would be required to build a picture for the optimal scavenging conditions. The limits of using an isotherms/kinetics assessment to understand the behaviour of Pd removal using solid phase scavengers are quickly reached. If a single isotherm is measured at a single temperature, only a very limited picture of the thermodynamics of the scavenging reaction will be obtained. Better practice is to perform the isotherm at several temperatures, typically 3, in order to have an understanding of the effect of temperature on the Pd removal. In addition, a kinetics curve describes the system at one temperature only and at one ratio of scavenger to metal only. The number of experiments required to create these two curves can also be optimized, i.e. with a similar number of experiments, one could obtain far more information about the system’s behaviour. An alternative approach is to use statistical DoE, a wellknown and widely used method32−34 to obtain the largest possible amount of information on a particular process from the minimum number of experiments. Furthermore, it also provides a clearer picture of how the studied parameters influence the variation in performance. 2.3. Design and Implementation of the DoE Experiments. 2.3.a. Design Space Definition. A DoE-based methodology was used to study the influence on the overall efficiency of a scavenging operation of not only the two parameters that are most commonly studiedmolar equivalents (ME) and time (t)but also two further parameters that experience has shown to be critical to scavenging operations

It was decided that 24 h was sufficient to allow equilibrium of the adsorption process to be reached (see kinetics profile in Figure 3). The convex curve of this graph represents a “favorable isotherm” whereby a large quantity of Pd is retained on the scavenger as an excess of scavenger is introduced. The residual Pd in the product solution could be reduced to below the limit of detection of the analytical method, proving that SPM32 is an appropriate choice for this product solution. Additionally, up to 60 g of Pd can be loaded per kg of scavenger: a process chemist wishing to recover part of the cost of the Pd by sending loaded scavenger to a metal refiner would get a good economic return in this instance, increasing overall process efficiency. A kinetics profile of the adsorption reaction further assesses the compatibility of the scavenger with the product solution being treated. The kinetics curve for the interaction of 3 mol equiv of SPM32 with the toluene solution of N-aryl-α-amino acid 3 at 60 °C is shown in Figure 3. The exponential-like decrease of the Pd concentration in solution demonstrates a favorable reaction rate with 84% of the metal being removed within 4 h of treatment. Both the reaction rate (kinetics) and the equilibrium position (isotherm) of this metal adsorption process provided useful data for judging the potential of the scavenging process, but adopting this approach limits the data available to one temperature, 60 °C, and in the case of reaction rate, one single ratio of scavenger to metal (in this case 3 ME). Lots of additional experiments at various temperatures for each of the 628



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the initial concentration of Pd in the solution (before scavenging), co(Pd), and the temperature, T, at which the process is run. The ranges over which these four continuous parameters were studied defines the experimental space, and these are shown in Table 1.

Table 2. Pd Concentration of the Five API-Like Product Solutions targeted Buchwald-Hartwig reaction product solution 100 200 300 400 500

Table 1. Definition of the Experimental Space of the DoE Studya parameter studied Temperature - T

range 30 °C → 90 °C 0.6 → 3.0

points measured 30 °C, 45 °C, 60 °C, 75 °C, 90 °C 0.6, 1.2, 1.8, 2.4, 3.0

Molar equivalent of scavenger to Pd - ME Contact time between 20 min → 20 min, 60 min, 100 min, 140 scavenger and solution - t 180 min min, 180 min Concentration of Pd in the 100 mg/kg → 100 mg/kg, 200 mg/kg, 300 product solution - co(Pd) 500 mg/kg mg/kg, 400 mg/kg, 500 mg/kg

mg/kg mg/kg mg/kg mg/kg mg/kg

Pd Pd Pd Pd Pd

Buchwald-Hartwig Buchwald-Hartwig Buchwald-Hartwig Buchwald-Hartwig Buchwald-Hartwig

solution solution solution solution solution

measured Pd concentration (mg/kg) 100.0 202.4 314.8 411.4 507.3

Design of the Experimental Matrix. The 29 experiments optimization matrix was designed in collaboration with Dr. Andrei Zlota of The Zlota Co. LLC using the DoE Fusion PRO software (model robustness option).35 The matrix included a duplicated center point, and two additional replicates allowing for the estimation of experimental error. All experiments were carried out on the same day, using the same batch of SPM32 and the same batch of Buchwald-Hartwig reaction product solutions, to minimize any uncontrolled variations in the experimental conditions. Detailed experimental conditions can be found in the Supporting Information. The parameters’ values for each of the experiments in the matrix are shown on the left columns in Table 3, with the results on the right columns, in terms of residual Pd concentrationcf(Pd)and percentage of Pd scavenged% Pd. A noteworthy result is that entry #9 yields not only the lowest residual amount of Pd in solution, cf(Pd), but also the highest percentage of Pd scavenged. In contrast, entry #16 yields the highest residual amounts of Pd in solution, but this does not correspond to the lowest percentage of Pd removal. Depending on the application the scavenger is used for (purification of the solution, or recovery of Pd), the optimized values of all 4 parameters may be different. The residual Pd concentration, cf(Pd), will be focused on, as it is the key result, because a careful control of this number is most often needed during API purification. The variability observed in Table 3 for the process result cf(Pd), with concentrations between 21.7 mg/kg and 423.9 mg/kg, shows a good signal/noise ratio. The 21.7 mg/kg lower limit was deemed suitable in order to ensure precision in the measurements: indeed, under 20 mg/kg, the error on Pd concentration measurements rises over 5%. 2.4. Quantifying the Influence of the Four Parameters−Data Analysis. A coded variable is assigned to each parameter, which is proportional to each parameter, but varies between −1 and +1 (Table 4). A mathematical quadratic model linking the residual Pd concentration, cf(Pd), to all four parameters was devised using powerful quality-by-design software,36 and found to fit the data well. The mathematical model obtained is shown in Table 5. The error between this mathematical model and the data used to build it was found to be minimal (see Table 6). More detailed information on the design of the DoE study and the statistical analysis of the results may be found in the Supporting Information. This model gives the equation of a response surface. For each point on this response surface, the value of cf(Pd) corresponds to the values of the four parameters. Projections of this response surface give a clearer picture of the behaviour of the scavenger when two parameters are varied. For example, Figure

a

Upper and lower limits were chosen based on feasibility and effect of the studied parameter on the scavenging process.

The initial concentration of Pd in the solution before scavenging, co(Pd), may appear to be a surprising choice, as it is generally not a tunable parameter: Pd must be removed from the product solution regardless of co(Pd). However, a good understanding of the effect of initial concentration of Pd allows the provision of a better cost-to-benefits model at an early stage of the project. As shown in Table 1, the experimental matrix was designed with data points measured at five regular intervals throughout the chosen range. Temperature, T, was varied between 30 and 90 °C. The boiling point of toluene is 110 °C, and the upper limit of 90 °C was chosen to allow a wide error margin. The lower limit of 30 °C is the minimum temperature that could be reproducibly achieved without purposely cooling the experiments during the scavenging process. Molar equivalent of scavenger, ME, was varied between 0.6 and 3.0, with these limits being based upon the isotherm curve (Figure 2)varying the ME between these values ensures a large variation in the residual levels of Pd, which can be easily measured with small relative errors. Reaction time, t, was varied between 20 and 180 min. The kinetics curve (Figure 3) shows that 85% of the Pd is removed after 180 min, using this as the upper limit ensures that significant levels of Pd remain in the solution, simplifying trace analysis. A minimum of 20 min ensures that human error on small time measurements will have no significant impact. Concentration of Pd in the solution, co(Pd), was varied between 100 mg/kg and 500 mg/kg, which is the range in which the use of metal scavenger is typically the most cost efficient option. It would pose no particular experimental issue to extend this range if a project required it. 2.3.b. DoE Study. Description of the Experimental Procedure for the DoE Experiments. All five BuchwaldHartwig product solutions at five levels of Pd concentration were made from the same batch of crude Buchwald-Hartwig product, as described in the Supporting Information, to which additional solvent (toluene) was added or removed under vacuum to reach the desired Pd concentration. Metal content analyses were run using inductively coupled plasma−optical emission spectroscopy (ICP-OES), and are shown in Table 2. 629



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Table 3. DoE Experimental Matrix for the Study of the Influence of Temperature (T), Scavenging Time (t), Molar equiv of Scavenger vs Pd (ME), and Initial Pd Concentration (co(Pd)) on Scavenging Efficiency reaction conditions − 20 g of solution treated

Table 5. Mathematical Model Obtained, in Coded Variables coded variable model A = co(Pd) B=T cf(Pd) = +114.2618 +109.0803 (A) −31.6922 (B) −26.6544 (C) −79.3941 (D) +21.6016 (B)2 +33.8644 (C)2 −19.3548 (A * B) −6.2749 (A * C) −57.1664 (A * D) −14.2782 (B * D) −6.7416 (C * D)

results of the experiments

entry

c0(Pd) (mg/ kg)

T (°C)

t (min)

ME (equiv)

residual Pd concentration cf(Pd) (mg/kg)

Pd removal (%)

#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

100 400 100 100 300 300 500 400 300 500 500 200 100 200 200 500 500 200 300 100 100 500 400 400 500 300 100 100 500

30 45 30 90 60 30 90 45 90 30 30 75 60 45 45 60 30 75 60 30 30 90 75 75 30 90 90 30 90

20 140 100 180 100 180 180 60 180 180 20 140 20 140 60 20 100 60 100 20 180 180 140 60 20 20 20 180 20

0.6 1.2 3.0 0.6 1.8 0.6 0.6 2.4 3.0 3.0 1.8 2.4 3.0 1.2 2.4 0.6 0.6 1.2 1.8 0.6 3.0 0.6 2.4 1.2 3.0 0.6 3 1.8 3.0

94.1 239.8 36.3 70.9 103.9 237.3 357.0 173.5 21.7 170.0 364.5 31.6 46.6 114.1 80.9 423.9 419.8 108.4 100.5 96.0 29.1 354.6 69.2 230.9 311.7 244.0 31.5 49.5 118.4

6% 42% 64% 29% 67% 25% 30% 58% 93% 67% 28% 84% 53% 44% 60% 16% 17% 46% 68% 4% 71% 30% 83% 44% 39% 23% 69% 51% 77%

C = time D = ME

Table 6. Error Analysis of the Mathematical Model Obtained error statistic name

statistical value

R2 adjusted R2

0.9961 0.9935

Table 4. Relationship between the Coded and Natural Variablesa parameter studied temperature - T molar equivalent of scavenger (to Pd) - ME contact time between scavenger and solution -t concentration of Pd in the product solution co(Pd)

natural range

coded range

30 to 90 °C 0.6 to 3.0 20 to 180 min

−1 to 1 −1 to 1 −1 to 1

100 to 500 mg/kg

−1 to 1

Figure 4. Variations of cf(Pd) with ME and co(Pd), when temperature and time are fixed at 60 °C and 180 min.

combinations) can be sorted from that with the biggest effect on the scavenging efficiency, to that with the least, as represented in the Pareto chart (Figure 5). This ranking allows assessment of which parameter change would have the most important effect on a scavenging operation. Variations in the initial Pd concentration co(Pd) have the biggest effect on the final Pd residual concentration cf(Pd); as would be expected, the amount of scavenger required to reduce Pd to low levels increases with Pd input. The initial concentration of Pd in solution co(Pd) is not necessarily a parameter that can be tuned, but understanding the effects of its variations on Pd removal improves the process understanding. The next important parameter is the molar equivalent (ME) of scavenger with respect to Pd, which therefore remains an efficient variable to alter in order to improve Pd removal. Scavenging time and temperature appear less important, accounting for an impact on scavenging of roughly a third of

Points were measured for coded parameter values of −1, −0.5, 0, 0.5, and 1. a

4 is the projection of the response surface defined by T = 60 °C and t = 180 min. As expected, it shows a decrease in residual Pd when ME is increased (more scavenger added) and when co(Pd) is decreased (less Pd initially in solution). The dark blue area represents residual Pd concentrations below 28 mg/kg. For example, the model predicts that at 60 °C and 180 min of contact time, 1.0 ME of scavenger should be enough to treat a solution containing 100 mg/kg of Pd to below 28 mg/kg. 2.4.a. Ranking the Most Efficient Parameters. Based on the data shown in Table 3, the parameters studied (and their 630



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Figure 5. Pareto chart - Parameters in order of decreasing importance (left to right).

Figure 6. Interaction between c0(Pd) and ME. The red line represents the influence of co(Pd) on the result cf(Pd) at ME = 3. The blue shows the corresponding effect with ME = 0.6, T = 60 °C, and t = 100 min.

2.4.b. Effect Interactions. Interactions between parameters can highlight where a parameter change might be the most efficient. For example, Figure 6 shows the interaction between co(Pd) and the ME of scavenger. The nonparallel nature of two lines shows that increasing the ME will not have the same magnitude of effect at high or low values of co(Pd). At low values of co(Pd), an increase in ME will have an effect on cf(Pd) that will be significantly different to its effect at high co(Pd) values. The possibility of controlling the reaction with a given parameter should therefore be carefully considered to achieve

the effect of co(Pd). They represent the easiest parameters to manipulate in a scavenging process. Parameter A*D, a two-factor interaction which represents a simultaneous variation of co(Pd) and ME, has the third biggest effect on the result. An important A*D interaction means that varying factors A and D at the same time does not result in an effect that is simply the sum of the effects of varying A alone, and D alone. In this case, it means an increase in ME will have a different impact on cf(Pd) depending on whether one works at high or low co(Pd). 631



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Figure 7. Response surface contour plot. Variation of cf(Pd) with ME and co(Pd). T = 60 °C and t = 100 min.

Figure 8. Response surface contour plot. Variation of cf(Pd) with ME and co(Pd). T = 90 °C and t = 180 min.

the optimum effect, depending on the initial concentration of Pd co(Pd), it may or may not be worth varying the ME. Even

more than simply highlighting parameters which will have only a marginal effect on scavenging efficiency, fitting a mathematical 632



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Alternatively, the nature of the interaction between the scavenger and the Pd species might change, from mono- to bidentate for example. One point to highlight is that a DoE experimental matrix, while requiring roughly the same amount of measurements as plotting isotherms and kinetics at three temperatures, will yield far more valuable data, and lead to a better understanding of the scavenging process. 2.5. Verification Experiments. The mathematical model obtained provides an easy way of predicting the behaviour of this product solution/scavenger system, within the design space. To examine the validity of this model, two sets of verification experiments were carried out. One set was performed on the same 20 g scale and with the same apparatus as the 29 experiments that were used to build the model, and tests the validity of the model itself. The second set of verification experiments was carried out at a slightly larger scale, to provide an initial assessment of the impact of scale-up on the reliability of the model developed. The verification experiments were carried out under the following conditions: (1) T = 60 °C, t = 100 min, co(Pd) = 200 mg/kg, 2.6 ME (predicted residual from the mathematical model: cf(Pd) = 24 mg/kg); (2) T = 60 °C, t = 100 min, co(Pd) = 300 mg/kg, 2.8 ME (predicted residual from the mathematical model: cf(Pd) = 45 mg/kg). The scavenging parameters for the verification experiments were chosen for several reasons. One, they are mild scavenging conditions: between the extremes of temperature, not requiring a long contact time, and not using large amounts of scavenger. In other words, in a working domain that would be appealing to the industrial chemist. Two, the predicted residual Pd concentration cf(Pd) falls in a range allowing for more accurate measurements. It was noted that the relative error on cf(Pd) measurements increases above 5% on measurements of Pd concentrations below 20 mg/kg. The 50 mg/kg upper limit was set in order to demonstrate the validity of the model in an area where the conditions still define a meaningful scavenger operation. 2.5.a. Model Validity. Different batches of product solution were prepared and used for the verification experiments; hence, a slight variation of co(Pd) can be observed compared to previous experiments. The results of the two small scale experiments are shown in Table 7.

model to the data can also show areas where varying parameter levels will have a negative effect on scavenging. 2.4.c. Temperature and Time: A Nonevident Effect on Residual Pd. It would not be unreasonable to assume that increasing the contact time, t, between a scavenger and a product solution leads to lower residual Pd levels. Also, the effect of the temperature on scavenging efficiency is often assumed to be monotonic, either detrimental or beneficial depending on the type of scavenger considered. When the effect of temperature is studied by traditional methods, i.e., by plotting isotherms at three temperatures, its impact on Pd removal is assessed only at the reaction equilibrium. If instead kinetics are plotted at three temperatures, then the effect of temperature on Pd removal can only be assessed at one specific ME of scavenger. A large number of such “isotherm/kinetics at three temperatures” studies have been carried out within the field of metal adsorption.22,29−31 This study highlights the fact that the temperature and time parameters can actually be correlated with other parameters in the scavenging process. Under certain conditions, an increase in contact time, t, and temperature, T, can actually lead to complex and possibly detrimental effects on the scavenging efficiency. This would not be detected by running three isotherms at three different temperatures, except if they happened by chance to be run under exactly the right conditions. More generally, running “one factor at a time” investigations would not detect such interactions. Figure 7 shows the dependence of cf(Pd) on the two most important parameters of this study: co(Pd) and ME, when time and temperature are set respectively at 60 °C and 100 min. The red area of the graph is where treatment with SPM32 leads to poor results: cf(Pd) remains over the 50 mg/kg threshold, whereas in the white area, cf(Pd) is below 50 mg/kg. Considered in isolation, it shows an expected resultit is possible to reduce the residual Pd to below 50 mg/kg in a low concentration solution (co(Pd) = 100 mg/kg) with small quantities of scavenger (0.6 ME). For more concentrated solutions, higher ME of scavenger are required, until for co(Pd) > 350 mg/kg it becomes impossible to reduce Pd residuals to below 50 mg/kg (at this reaction time and temperature and within the parameter ranges studied here). Figure 8 is a plot of the same parameters as Figure 7, but at a higher temperature and longer reaction time. An interesting effect is observed when Figure 7 is compared with Figure 8. Under the harsher scavenging conditions described in Figure 8, it becomes possible to reduce the Pd content of solutions of the highest co(Pd) (500 mg/kg) down to below 50 mg/kg (top right corner). Under these conditions, however, the quantity of scavenger needed to obtain the threshold cf(Pd) of 50 mg/kg is increased to approximately 1.2 ME (bottom left corner of the graph). This is a significant increase in ME compared with Figure 7, where time and temperature were lower. A number of chemical explanations can be proposed for this phenomenon. It is not the purpose of this paper to prove or disprove them, but some suggestions can be submitted for consideration. It is possible, for example, that a higher temperature leads to a change in the speciation of the dissolved Pd, resulting in the formation of a species that is more difficult to scavenge. Another possible explanation could be that prolonged contact time between the product solution and the scavenger could lead to another dissolved molecule (e.g., the product or a byproduct) coordinating to the scavenger, thus using up active sites that then are unavailable for Pd chelation.

Table 7. Results of the Small Scale Verification Experiments temp. (°C) 60 60

time co(Pd) (min) (mg/kg) 100 100

196.4 291.5

ME

result: cf(Pd) (mg/kg)

expected cf(Pd) value according to model (mg/kg)

2.61 2.80

32.1 39.8

24.1 45.5

At 95% confidence, each verification experiment leads to results that fully fit the range at stake. The values lie within the 2σ range, deemed highly appropriate for this study. 2.5.b. Impact of a Scale Increase. The validity of the model to a moderate scale-up was tested by increasing the scale to 100 g of product solution (5 times larger). For these larger scale experiments, an alternative apparatus setup was used in order to better represent what could be encountered in an industrial application. A pitch-bladed overhead stirrer (blade diameter: 4.0 cm, blade height: 1.2 633



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Table 8. Scale-up Verification Experiment for 200 mg/kg a Product Solution

Experiment 1 (analysis repeated twice)

temp. (oC)

time (min)

co(Pd) (mg/kg)

60

100

193.1

ME



2.60 2.60 2.60

29.1 29.3 31.9

23.4 23.4 23.3

2.60 Mean Std. dev. σ

31.6 30.5 1.5

23.3

ME



2.80 2.80 2.80

41.2 39.6 40.0

45.5 45.5 45.6

2.80 Mean Std. dev. σ

39.8 40.2 0.7

45.6

Experiment 2 (analysis repeated twice)

Table 9. Scale-up Verification Experiment for a 300 mg/kg Product Solution

experiment 1 (analysis repeated twice)

temp. (°C)

time (min)

co(Pd) (mg/kg)

60

100

291.5

experiment 2 (analysis repeated twice)

which can generate a good amount of process knowledge with significantly fewer experiments. While there are many parameters that can be varied to improve the effectiveness of Pd removal from a pharmaceutical intermediate, an understanding of the importance of those parameters can lead to additional process benefits, such as the removal of Pd to lower levels or a more economic use of the metal scavenger. On scale-up, the latter benefit in particular has key importance as chemists try to develop economic manufacturing processes. A systematic study is also able to highlight effects that would have been otherwise missed, or wrongly attributed. A rise in temperature, typically, can be very beneficial under certain conditions, but this study suggests that the same parameter can become detrimental under other sets of conditions. Equally, an increase in ME of scavenger might have less of an impact under some conditions compared to others. The validity of this model to a moderate increase in scale was also tested, with modifications including not only a change in scale, but also an alteration of the stirring method (pitched blade overhead stirrer) to better reflect equipment used industrially. The model was found to remain valid, with only minor changes in cf(Pd) observed compared to small scale experiments. These characteristics not only are dependent upon the reaction used, the nature of the metal, and the product solution, but also change considerably from one scavenger to another. It was not the intention of this study to propose a set of general trends, applicable to any scavenging operation. It is hoped, however, to present chemists with an efficient method, adaptable to any scavenging operation, which allows an increased understanding and prediction of the behaviour of one given scavenging operation, aimed towards minimizing cost and time at scale. Using such a mathematical method, a process chemist would have the capacity to quickly adapt to changes in the process, with no additional experiments after the initial matrix other than one or two verification experiments. In the example presented here, the original concentration co(Pd) of Pd in the Buchwald-Hartwig product solution was shown to have the most statistically significant effect on

cm) was used instead of the shaker stage used at small scale. The agitation speed was set to 300 rpm, and the reaction vessel was a flanged round-bottomed glass flask (diameter 85 cm). At this agitation speed, a good suspension of the SPM32 scavenger in the product solution was observed. The scavenging operation was heated using a heating mantle equipped with a feedback temperature probe. To increase the reliability and the reproducibility of the analytical data, each experiment was repeated twice, and for each repeat, the analysis was also repeated. The results are presented in Table 8 and Table 9. These results are very similar for both the 20 g and the 100 g scales, and the model was verified successfully at 95% confidence. It therefore appears that the moderate scale increase, including the change of conditions (from a vial to a round-bottom flask, and from shaking to overhead stirring) has only a marginal influence on the reaction, and therefore does not significantly impact on the accuracy of the predictions made by the model. For meaningful scale-up predictions, however, further scaleup investigations remain necessary.

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CONCLUSIONS A method has been presented which is aimed at understanding the important parameters in a metal scavenging operation by the study of a Pd-catalyzed Buchwald-Hartwig reaction. Metal scavenging is a complex multivariate process; suitable multivariate analysis, such as statistical design of experiment, can be a powerful tool to quickly generate such process understanding. To the best of our knowledge, this is the first factorial DoE study on a metal scavenging process, and the benefits of the method are clearly illustrated. Optimized conditions under which to scavenge Pd from an API model solution can easily be identified. A matrix of 29 experiments might be considered to be a significant commitment of resources, which, while beneficial in terms of developing a process model, may not appear attractive to the process chemist. However, chemists should consider screening designs and fractional factorial screening designs, 634



Article

(18) Grosjean, C.; Henderson, A. P.; Hérault, D.; Ilyashenko, G.; Knowles, J. P.; Whiting, A.; Wright, A. R. Org. Process Res. Dev. 2009, 13, 434. (19) Salome, C.; Salome-Grosjean, E.; Park, K. D.; Morieux, P.; Swendiman, R.; DeMarco, E.; Stables, J. P.; Kohn, H. J. Med. Chem. 2010, 53, 1288. (20) Brown, J.; Chighine, A.; Colucci, M. A.; Galaffu, N.; Hirst, S. C.; Seymour, H. M.; Shiers, J. J.; Wilkes, R. D.; Williams, J. G.; Wilson, J. R. H. Tetrahedron Lett. 2008, 49, 4968. (21) Jal, P. K.; Patel, S.; Mishra, B. K. Talanta 2004, 62, 1005. (22) Girgis, M. J.; Kuczynski, L. E.; Berberena, S. M.; Boyd, C. A.; Kubinski, P. L.; Scherholz, M. L.; Drinkwater, D. E.; Shen, X.; Babiak, S.; Lefebvre, B. G. Org. Process Res. Dev. 2008, 12, 1209. (23) The possibility of including several scavengers in this study was considered, but was found to be impractical. The fact that there is no continuity in the nature of scavengers makes them difficult to study by DoE. For a continuously defined numerical parameter (e.g., temperature), one can easily define upper and lower limits for the design space (e.g., 30 to 80 °C) and a midpoint (e.g., 55 °C). There is no easy way to do this for a categorical parameter such as ″nature of scavenger”. Ways around this problem can be found by sorting scavengers based on one of their characteristics, such as the empirically measured efficiency of the scavenger, for example. However, this method introduces a source of potentially large error as this characteristic is only measured under one set of conditions, and is assumed to remain unchanged when conditions vary across the design space. Another drawback is that it significantly increases the number of experiments required to study a system. (24) (a) Salome, C.; Salome-Grosjean, E.; Stables, J. P.; Kohn, H. J. Med. Chem. 2012, 53, 3756. (b) Kohn, H. L.; Salome, C. WO 2010/ 148300, 2010. (25) (a) Ford, R.; Mather, A.; Mete, A.; Wiley, K.; Bull, R. J. US 2011/0190309, 2011. (b) Charrier, J. D.; MacCormick, S.; Storck, P.H.; Pinder, J.; O’Donnel, M. E.; Knegtel, R. M. A.; Young, S. C. Y.; Kay, D.; Reaper, P. M.; Durrant, S. J.; Twin, H. C.; Davis, C. J. WO 2012/138938, 2012. (c) McGee, P.; Garnett, I.; Juan, E.; Manage, A.; Carniaux, J.-F. US 2012/0165520, 2012. (26) http://www.phosphonics.com/. (27) Mondal, B.; Wilkes, R. D.; Percy, J. M.; Tuttle, T.; Black, R. J. G.; North, C. Dalton Trans. 2014, 43, 469. (28) Narendar, N.; Velmathi, S. Tetrahedron Lett. 2009, 50, 5159. (29) Wang, L.; Zhang, J.; Zhao, R.; Li, Y.; Li, C.; Zhang, C. Bioresour. Technol. 2010, 101, 5808. (30) Dinu, M. V.; Dragan, E. S. Chem. Eng. J. 2010, 160, 157. (31) Boparai, H. K.; Joseph, M.; O’Carroll, D. M. J. Hazard. Mater. 2011, 186, 458. (32) Owen, M. R.; Luscombe, C.; Lai, L.-W.; Godbert, S.; Crookes, D. L.; Emiabata-Smith, D. Org. Process Res. Dev. 2001, 5, 308. (33) Hersmis, M. C.; Spiering, A. J. H.; Waterval, R. J. M.; Meuldijk, J.; Vekemans, J. A. J. M.; Hulshof, L. A. Org. Process Res. Dev. 2001, 5, 54. (34) Alimardanov, A. R.; Barrila, M. T.; Busch, F. R.; Carey, J. J.; Couturier, M. A.; Cui, C. Org. Process Res. Dev. 2004, 8, 834. (35) More information may be found at http://www.linkedin.com/ pub/andrei-zlota/3/1a4/8b4. (36) Fusion Product Development; S-Matrix Corporation; Eureka, California, USA; http://smatrix.com.

scavenging efficiency, closely followed by the molar equivalents of SPM32 scavenger used and an interaction of these two factors.

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ASSOCIATED CONTENT

* Supporting Information S

Synthesis of the Buchwald-Hartwig stream. Analysis of the functional group loading (FGL) of PhosphonicS SPM32 scavenger. Typical procedure for an experiment in the experimental matrix. ICP-OES analysis of the Pd content in samples. Design and statistical analysis of the DoE experiment. Screening of Pd-containing solutions for good Pd retention. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We would like to thank Dr. Andrei A. Zlota of The Zlota Co. LLC for fruitful discussion and guidance regarding the setup of the DoE experiments described in this paper and the interpretation of their results.

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REFERENCES

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Statistical DoE Approach to the Removal of Palladium from Active

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