Novel, Calibration-Free Strategies for Supersaturation Control in

Article pubs.acs.org/crystal

Novel, Calibration-Free Strategies for Supersaturation Control in Antisolvent Crystallization Processes Published as part of a Crystal Growth and Design virtual special issue of selected papers presented at the 10th International Workshop on the Crystal Growth of Organic Materials (CGOM10) D. Duffy,*,†,‡ M. Barrett,†,‡ and B. Glennon†,‡ †

University College Dublin, Dublin 4, Ireland Solid State Pharmaceutical Cluster, University of Limerick, Limerick, Ireland

‡

ABSTRACT: In-situ attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy and focused-beam reflectance measurement (FBRM) were used to monitor and control the antisolvent crystallization of paracetamol from an acetone−water mixture, which was conducted in a 150 mL flat bottom crystallizer with a Mettler Toledo Easymax Reactor system. Following the monitoring of a series of unseeded and seeded crystallization experiments using a constant addition rate of antisolvent, a simple calculation method for the set point of antisolvent addition rate, to maintain constant supersaturation via ATR-FTIR, was developed and implemented for feedback control of unseeded and seeded crystallizations. The implemented technique used a single peak in the ATR-FTIR spectral region without any calibration to effectively maintain supersaturation to a prespecified set point. By developing a solubility curve in terms of peak height and knowing key information of the process at any given time, the addition rate of antisolvent could be manipulated to suit the demands of the crystallization. Four set point control experiments, three seeded and one unseeded, were investigated for comparison and were compared using FBRM, particle size distribution (PSD), and offline microscope image analysis. The results of the controlled feeding rate experiments show an increase in the final particle size measured by PSD, a decrease in the total batch time, and a reasonable elimination of agglomeration in the system.

1. INTRODUCTION

kinetics that are accurate enough to produce an optimal batch recipe.6 In antisolvent crystallizations, supersaturation is created by mixing a third component with the saturated solution in order to reduce the solubility of the solute. It is considered the separation and purification method of choice for heat -sensitive pharmaceuticals and agrochemicals.7 Antisolvent crystallizations are generally performed in a semibatch manner, whereby antisolvent is pumped into the crystallizer at a constant flow rate.8,9 It has been shown, however, that the constant linear addition of antisolvent is not always the ideal scenario10 and that a time varying flow rate can yield a better particle size distribution (PSD) by matching the generation rate of supersaturation with the growing crystal surface area.8,11,12 The possibilities of developing approaches to control crystallization processes in situ emerged with the introduction

Crystallization from solution is an important unit operation due to its ability to provide high purity separations and the impact that the final crystal size distribution from this step has on downstream processes. For efficient operation of a downstream process such as filtration or drying, a reasonable control over the final crystal size, shape and purity is of critical importance.1 Over the past few years, increasing emphasis has been placed on designing and operating pharmaceutical crystallization processes to produce product of a more consistent shape or size.2 If it is considered that a typical batch experiment in industry is carried out by following a specific temperature or antisolvent addition profile, then it can be hypothesized that sticking to this profile will not necessarily give you the desired outcome. This is because rigorous determination of an optimal batch recipe requires accurate growth and nucleation kinetics.3−5 While this may be a relatively straightforward exercise in some cases, for some of the more difficult systems, it can be a time-consuming problem to compute and determine © 2013 American Chemical Society

Received: November 14, 2012 Revised: June 14, 2013 Published: June 26, 2013 3321

dx.doi.org/10.1021/cg301673g | Cryst. Growth Des. 2013, 13, 3321−3332

Crystal Growth & Design

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lization of paracetamol from an acetone and water solution. The initial solvent mixture is 45 wt % acetone/water, and the starting temperature in all experiments is 23 °C. The monitoring of solute concentration in terms of peak height measured by an ATR-FTIR probe is demonstrated, and the effect that the supersaturation level being maintained during the course of the batch experiment on final particle size is investigated and compared with standard linear addition experiments, both unseeded and seeded.

of the ATR-FTIR instrument. Shown to be able to accurately measure in situ the liquid phase composition in the presence of solids,13−15 the ATR-FTIR allows effective crystallization control to be implemented without prior kinetic knowledge. The ATR-FTIR has been successfully used to implement feedback control in both cooling and antisolvent crystallizations.11,16,17 Developed previously8 was a feedback control methodology for unseeded and seeded crystallizations of paracetamol from acetone−water which used ATR-FTIR coupled with a chemometric model to control the feed rate of antisolvent addition to improve particle size, PSD, and batch time simultaneously. Also implemented6 was a direct concentration control approach to investigate different supersaturation profiles in the search for an optimal antisolvent addition profile with the goal of reducing process development time. Recent studies18 have extended this approach by designing and optimizing a combined cooling and antisolvent crystallization utilizing feedback control. Numerous other examples exist12,19 where the supersaturation control methodology for cooling crystallizations can be extended to antisolvent crystallizations to effectively control supersaturation using chemometrics and ultimately improve the final crystal size distribution (CSD). Normally, the antisolvent addition rate is calculated by solving the equation for the % of solvent set point, %S. Improvements were made to this standard method6 by investigating the effect of dilution on the control algorithm. All of these methods utilize chemometrics to infer accurate solution concentration measurements from corresponding peak height readings from an ATR-FTIR. Developments in recent years have seen the emergence of new control methods and robust model-free approaches for controlling crystallizers in particular. If it is considered that the object of most industrial crystallizers is to maintain the operation within the metastable zone, then by maintaining the concentration to a set point within this region using a supersaturation control approach or through manipulation of the solids content, then this objective can be achieved. Model-free approaches offer the distinct advantage of being capable of the same robustness as the approaches mentioned above such as concentration feedback control (CFC) while being more applicable to a pharmaceutical environment due to not being restricted by difficult and sensitive calibration procedures which may vary depending on the process environment and instruments being used. One such approach is direct nucleation control (DNC).20−22 DNC allows the system to cross the metastable boundary to induce nucleation whereupon it then maintains the number of particles at a predetermined value. It is based on the idea that the lower the number of fine crystals in the system, as measured as total counts between 1 and 10 μm using the FBRM, the larger the size of the final product crystals. The predetermined set point is based off of unseeded experiments which provide a qualitative estimate of a typical crystal number in the run. The crystal population is measured in situ using an FBRM, and like supersaturation control approaches it can be used to indirectly to control the key properties of the CSD. Extending this idea of model-free control, it was shown previously in the case of cooling crystallizations23,24 that chemometrics are not always required and that novel, calibration-free techniques can be implemented to maintain supersaturation at a desired level while simultaneously improving product properties and reducing overall batch time. This present study implements a supersaturation control method for the effective control of the antisolvent crystal-

2. SUPERSATURATION TRACKING METHOD Figures 1 and 2 depict the experimental layout for the antisolvent control work described herein. IR peak height,

Figure 1. Experimental setup for antisolvent crystallization.

Figure 2. Experimental setup depicting layout of process instruments.

measured by ATR-FTIR spectoscopy, is sent to a model developed externally, running on a control computer connected by an RS23 cable. Resulting antisolvent addition rate 3322



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where ΔC is the supersaturation of the process defined as the difference between the saturated concentration and the actual concentration. At a known solvent composition, the supersaturation will be the difference in peak height between the saturated solute concentration and the measured solute concentration defined as

calculations are sent to a Masterflex(L/S Precision Pump), which turns the pump head at the required RPM to match the required antisolvent addition rate. This was calibrated to different flow rates prior to the experiments. Knowledge of the supersaturation during any crystallization is of absolute importance. Typically, the application of IR spectroscopy is based on establishing a relationship between the individual peak heights in the systems IR absorption spectrum through chemometric techniques such as PLS. These give an accurate measurement of the concentration, and in turn an accurate measurement of the supersaturation once the solubility information has also been obtained as the supersaturation is generally reported as the difference between the actual dissolved concentration and the corresponding saturated concentration at a specific solvent composition or temperature. Generally, for crystallization processes, the supersaturation is maintained within the metastable region during the course of the batch.6 The major drawback is that accurate chemometric calibration and validation are needed to get an accurate concentration measurement at any point during the batch, and the accuracy of the calibration must be well within the supersaturation levels encountered in the process. In the approach adopted here, a characteristic peak height, specific to the solute of interest, is tracked directly. The peak height corresponding to the saturated solution at the same solvent composition is also measured, so that the supersaturation at any point in the batch is presented in terms of the difference in measured peak heights. The method for determining the required antisolvent addition rate, based on measured solute peak height, can be primarily defined by looking at the supersaturation, that is, the difference in the peak height of the solute of interest and the saturation concentration in terms of peak height obtained previously. The following information is known about the system in advance: (a) the solubility curve as expressed by eq 6; (b) the initial mass of liquid in the crystallizer; (c) the initial concentration and supersaturation as expressed by eq 7, and (d) the chosen set point for supersaturation, ΔCPH,S. For most systems, the solute saturation concentration at any time instant K, CK* can be defined as in eq 1: CK* = a0 + a1CK +

a 2CK2

+

a3CK3

ΔCi = gi(PHi − PH*i )

The solubility in terms of peak height is obtained through the addition of antisolvent at a rate of 0.1 g/min to a saturated solution which has had an excess amount of seed added to it to ensure there is no supersaturation present. By doing this, the solubility in terms of peak height can be obtained, and the dilution effect of the addition of a solvent on the ATR-FTIR spectra is accounted for. The supersaturation, expressed as the difference between peak height in eq 5, will be efficiently described, since the dilution effect on both peaks will be identical, and therefore, irrelevant for the difference between both. The solubility in terms of peak height can then be expressed as * = a0 + a1Q + a 2Q 2 + a3Q 3 C PH

* K ΔC PH, K = C PH, K − C PH,

Mk =

C PH,0M 0 C PH, K

(8)

where MK is the mass of liquid in the crystallizer at any time instant, K. The amount of antisolvent that has been added, Q(g), can easily be calculated,

(1)

Q = MK − Mo

(9)

A set point value for supersaturation is then chosen, ΔCPH,S, and since the actual supersaturation in the vessel is now known, along with information on the mass of solvent in the crystallizer, it can be determined that if there is a discrepancy between ΔCPH,K and ΔCPH,S, then the control system will decrease (when ΔCPH,K > ΔCPH,S), or increase (when ΔCPH,K < ΔCPH,S), the addition rate of antisolvent, to bring the supersaturation at time tK+1 to ΔCPH,S. If ΔCPH,K < ΔCPH,S, the total mass of liquid in the crystallizer needs to increase to MK+1 at tK+1 to make ΔCPH,K = ΔCPH,S. So the required amount of antisolvent needed at a future time instant K+1 to maintain a desired supersaturation set point is calculated from eq 10,

(2)

(3)

* k + ΔC PH,S Q k + 1 = C PH,

Therefore, the supersaturation is defined as ΔCi = Ci − Ci* = fi (PHi , S ) − fi (PHi*, S )

(7)

The mass of liquid inside the crystallizer at any time can be obtained from a mass balance on the crystallizer:

where S is the solvent composition, C is the solute concentration, and PH is the peak height measured by the ATR-FTIR. Similarly, the solubility as a function of peak height and solvent composition is given by Ci* = Ci*(S ) = fi (PH*i , S )

(6)

where Q is the total mass of antisolvent added to the reactor and a0, a1, and a2 are constants of the equation and CPH* is the saturation concentration in terms of peak height. Following the determination of the solubility, a polynomial is fitted to the trend to determine the constants a0, a1, and a2. This polynomial equation is used in the developed control algorithm. The concentration in terms of peak height, CPH is known at any instant K, at a known solvent composition, which allows the supersaturation to therefore be calculated:

where a0, a1, and a2 are constants, CK* is the solute saturation concentration, and CK is the solute concentration. Using the calibration-free method determined here, the solubility is defined in terms of peak height and solvent composition to account for the effects of dilution on the system when the antisolvent is added. So, at a known solvent composition, S, the concentration of a given i as a function of the characteristic peak height (PH), i.e., Ci = Ci(S) = f (PHi , S )

(5)

(10)

where ΔCS is a set point value defined in peak height, and QK+1 is the amount of antisolvent needed in the crystallizer to

(4) 3323



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for tracking the solute in situ. These problems cannot necessarily be overcome but can be avoided somewhat under certain assumptions. It was assumed that the obtained solubility curve is inclusive of the dilution effect and that the peak is only representative of the paracetamol in solution at all times during the batch experiment. This may not be the case in all antisolvent crystallization systems. The relationship between the solute concentration and the peak height is not proportional but due to the specific antisolvent addition policy being used can be said to have a one to one relationship.

maintain the desired supersaturation set point at a future time instant. By substituting C*PH,K for eq 6.6, eq 6.11 becomes, Q K + 1 = a0 + a1Q K + a 2(Q K )2 + a3(Q K )3 + ΔCS

(11)

MK+1 can be easily calculated from eq 9 due to QK+1 and M0 now being known. Equation 11, as in eq 6.6, is implemented as a polynomial equation in the control algorithm. If it less than the set point as previously mentioned then desired antisolvent addition rate is calculated from FK =

MK + 1 − MK ΔT

3. EXPERIMENTAL METHODS

(12)

Paracetamol (Sigma Aldrich, 98%) was the compound chosen for all antisolvent crystallization runs. Paracetamol, although not very soluble in water, is extremely soluble in acetone. A solvent mixture of acetone and water was used, with water being used as the antisolvent. The solubility of paracetamol in acetone and water across a range of temperatures and solvent compositions is presented in Figure 3. All

where FK is the feed rate of antisolvent in (g/min). This feed rate is then sent to the pump as a command in revolutions per minute (RPM) and the antisolvent added. A sampling time of 30 s was chosen for this work. The most important step in the application of this control method, or in any crystallization procedure for that matter, is the determination of the solubility curve. Typically, as has been noted previously, the solubility curve can be readily determined using the gravimetric method,25 using an FBRM26 or using an ATR-FTIR.13 During the controlled cooling crystallization work detailed previously, it was proposed that an accurate solubility curve in terms of peak height could be determined by slowly heating an undersaturated solution at 0.1 °C/min to its saturation temperature. The control procedure presented here contains a similar method for the determination of a solubility curve in terms of peak height for an antisolvent crystallization process. Full knowledge of the solubility of the API in the solvent mixture must be known prior to the control method as a point in the process design space must be decided upon before the development of the crystallization. A solution of water and acetone was prepared. Paracetamol was added so that the final solution was slightly supersaturated at 23 °C. The solution, at room temperature initially, is allowed to heat to 45 °C at a rate of 0.3 °C/min to fully dissolve all of the paracetamol. It is kept at this temperature for approximately 20 min to ensure complete dissolution of the solute. From this point, it is allowed to cool at 0.3 °C/min to 23 °C where it is held for 20 min. As the solution, at this point, is slightly supersaturated, the process is seeded with an excess amount of seed material to ensure desupersaturation of the solute to the solubility curve. From this point, antisolvent is added at 0.1 g/ min to determine the solubility curve in terms of peak height. There are problems that accompany this method and should be mentioned. The first and the most obvious is that if the solubility is presented in terms of peak height, which is measured in absorbance units, then the addition of antisolvent without a full chemometric calibration is subject to a strong dilution effect. In short, the addition of antisolvent will decrease the absorbance being measured as there will be a large increase in the volume of liquid. This means it is difficult to determine if this is indeed accurate solubility information. The resultant ternary system makes it extremely difficult to select a peak that will not become affected by the changing solvent conditions over the course of the batch. It is possible, then, that the previously selected peak specific to the solute of interest, that was once independent and isolated from other peaks attributed to the solvent/solvents, may not necessarily describe changes to just the solute any longer and may be incorporating changes in the solvent/solvents, impacting the resulting supersaturation. The second problem is that of the selection of a suitable peak

Figure 3. Solubility for paracetamol in acetone and water system across a range of solvent compositions at 23 °C. experiments conducted during the course of this research were carried out at an operating temperature of 23 °C. A solution is made up using 45 wt % acetone to 55 wt % water. This provides a starting working volume of 56.13 mL of solution. To this, 13.52 g of paracetamol is added providing a starting concentration of 0.2707 g/g of mixed solvent. Solubility of the paracetamol in a mixture of acetone and water in terms of peak height was obtained by making up a solution with an excess amount of the solute, adding a known amount of antisolvent so a certain supersaturation value is reached, and then seeding the solution with a known amount of seed. The system was allowed to desupersaturate to the solubility curve where upon 70 mL (70 g) of antisolvent was further added to bring the system to its isolation point of 18.75 wt % acetone. All experiments had a total antisolvent addition of 70 g with a final working volume of approx 130 mL. Experiments were performed in a 150 mL Mettler Toledo EasyMax reactor system, used in conjunction with the software iControl Easymax, iC FBRM and iC IR. Throughout these experiments, focused beam reflectance measurement (FBRM) from Mettler Toledo, model s400a, was used to characterize particle dimension. Ten second measurements were used for the characterization of all experiments. Attenuated total reflectance Fourier transform infrared spectroscopy, ATR-FTIR, iC10 from Mettler Toledo) coupled with a 1.5 m silver halide fiber optic was used to track in situ peak heights, specific to the API. Scans were taken every 15 s. The peak height was selected previously by taking background spectra of the acetone and water. A known amount of the 3324



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paracetamol was then added to the solution and heated to 45 °C. This allowed the solute to fully dissolve. Once dissolved, a spectral scan was taken again to determine a peak a sharp, isolated peak. This is highlighted in Figure 4. This peak was used for the tracking of the

provide guidelines for the selection of this peak,23 but the most important feature is that it should be independent of any other peaks; i.e., it does not overlap with other peaks. It can be seen that the peak chosen here is independent of other peaks and is a suitable candidate for solute tracking. The peak height chosen was a height to two-point baseline with the peak selected at a wavenumber of 1528 cm−1 with a two-point baseline at 1532 cm−1 to 1521 cm−1. Single peaks, peak areas, and peak ratios are also used in the literature, but this single peak height to twopoint baseline was deemed sufficient for this study. This gave a consistent peak height for the starting concentration of each crystallization experiment and was robust during all experiments. The selection of a single peak for solute tracking, although useful, comes with limitations. Naturally, in a batch cooling crystallization, where a single solvent or mixture of solvents is used and simply cooled, the complexities associated with the addition of a second solvent, or antisolvent, are not involved. The addition of an antisolvent has a strong influence on the IR spectrum, and it is probable that a one to one relationship cannot always be assumed with a previously selected peak, that was once isolated from other solvent, becoming affected at different solvent compositions or ratios. The peak selected in this study was assumed to be specific to the paracetamol at all stages during these process experiments but is a significant point worth bearing in mind for its application to other antisolvent crystallizations. 4.2. Solubility Determination in Terms of Peak Height. The solubility in terms of peak height is presented in Figure 5. 13.52 g of paracetamol were added to a 45 wt %

Figure 4. Spectra of paracetamol in a solution of acetone and water (start and end of batch experiments). solute concentration in terms of peak height during all unseeded, seeded, and controlled crystallization runs. The solute was then filtered, dried, and weighed. Microscope images were taken of the final sample for off-line analysis.

Table 1. Reactor Information for Process Experiments details

150 mL vessel

impeller type agitation speed (rpm) vessel diameter (m) impeller diameter (m) impeller clearance (m) nozzle diameter (mm) nozzle inlet position operating volume (mL)

six bladed rushton 325 0.05 0.025 0.01 6 beside impeller 56.13

4. RESULTS AND DISCUSSION Presented in Figure 3 is the solubility for paracetamol in acetone and water across a range of solvent compositions at 23 °C. The data were obtained using a gravimetric method where a solution mixture of 50 mL of acetone and water was made up at a specific solvent composition, and an excess amount of solid was added. The solutions with the added solid were agitated at 400 rpm in a 150 mL Easymax reactor for 24 h. Following this, the solutions were filtered, and any remaining mass was dried and weighed. The amount of solute remaining was subtracted from that that had been added to obtain the quantity that had dissolved, and this was determined to be the saturation concentration. 4.1. Selection of Suitable Peaks for Solute Tracking. Figure 4 shows the spectral region for paracetamol in acetone and water. The red line indicates the spectra at the start of the process experiments where the solution is saturated, and the blue line indicates the end of each experiment where 70 g of water has been added. The selection of a peak to track the solute concentration is an important aspect of any calibrationfree monitoring of a crystallization process. Recent studies

Figure 5. Solubility of paracetamol in an acetone−water solution at 23 °C, as measured by the ATR-FTIR calibration-free technique. Also shown as the dashed line is the set point chosen for a typical control experiment.

solution of acetone and water which was heated to 45 °C to ensure complete dissolution of the API. This was then cooled to 23 °C where it was held for 20 min. An excess amount of seed was then added to the solution which was allowed to desupersaturate until there was no change in the peak height. Following this, water was added at an addition of 0.1 mL/min to determine a solubility trace shown as the solid black line in Figure 5. The dashed line displayed in Figure 5 is an example of a chosen set point for this control work. The corresponding polynomial expressions fitted to this data are displayed as these 3325



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Figure 6. (A) Unseeded crystallization experiments conducted at four different addition rates. (B) Supersaturation profiles versus antisolvent addition volume in unseeded crystallizations.

addition experiment, this nucleation rate can be reduced sufficiently to allow for improved crystal growth. The supersaturation profiles for each of the unseeded experiments are illustrated in Figure 6B. They give a clear picture of the driving force behind each of the unseeded crystallization experiments. They show the characteristic feature of an unseeded crystallization in that the peak height increased and also shifted to the right as the addition of antisolvent was increased. The trajectories are seen to increase as the antisolvent is added to the crystallizer which is due to the increased generation rates of supersaturation during the batch experiment. A point is then reached where the system nucleates and supersaturation is consumed. The supersaturation profiles presented here provide a certain level of confidence in both the method for obtaining solubility information and in the calibration-free technique as a method for monitoring the supersaturation in situ. It becomes clear then that the supersaturation can be used as a feedback signal to adjust the addition rate of antisolvent in order to maintain the supersaturation at the desired set point. From Figure 6B, it was deduced that a set point of 0.015 A.U. would be an effective starting point for the controlled addition of an unseeded experiment as it was approximately 30% of the supersaturation levels reached using addition rates of 0.6 and 1 g/min. 4.3.1. Unseeded, Controlled Antisolvent Crystallization Experiments. An unseeded controlled experiment was performed initially to investigate the capability of the control algorithm to effectively maintain supersaturation to a set point. The difficulty in implementing such an approach for an unseeded antisolvent crystallization is that the crystal surface must be created through nucleation before any control can be implemented. This results in high levels of supersaturation being generated prior to nucleation. During the nucleation stage, the antisolvent addition can be carried out at a constant flow rate. A relatively slow rate of 0.35 g/min was chosen as this is the slowest addition rate that could be chosen for this pump with this tube length. The control method was not initiated until the nucleation had occurred. The sampling interval for this experiment was 15 s, and the flow rate of antisolvent was adjusted accordingly at the same frequency. The set point was set at 0.015 A.U., which was believed to be a sufficiently low value to suppress secondary nucleation. The masterflex pump used for the control experiments is a peristaltic pump with

equations were utilized in the control algorithm for addition rate calculations. Q = 1.96 × 102 + (− 1.33 × 103*C PH) + (3.43 × 103 *C PH 2) + ( −3.29 × 103*C PH 3)

which is the inverse of the set point expression depicted in Figure 5 is an example of a typical expression used for calculation of the required amount of antisolvent needed at a future time instant, as in eq 11. Knowing the concentration, CPH and information on the mass of solvent in the crystallizer as well as the supersaturation set point in conjunction with this expression allow the rate of antisolvent addition needed to maintain the desired supersaturation set point to be calculated from eq 12. To check the accuracy of the ATR-FTIR technique for determining the solubility, six further seeding experiments were conducted. In each experiment, a known amount of antisolvent was added to the reactor, and a subsequent excess amount of seed was added. The system was allowed to desupersaturate toward the solubility curve, and the point at which no change in the IR peak height was recorded as a solubility point in terms of peak height. This was compared to the solubility trace previously determined. It was found that the end result of the seeding experiments lay on the same corresponding point of the solubility trace within ±5% error. This was seen as a reasonable validation of the solubility determination method using the calibration free technique. 4.3. Unseeded, Constant Antisolvent Addition Crystallizations. Four unseeded linear addition experiments were investigated initially to gain a qualitative understanding of the process and to investigate whether the calibration-free technique was useful in monitoring changes in the supersaturation during a process experiment. The addition rate was varied from 0.6 g/min to 3 g/min, and a total of 70 g of antisolvent was added in each of the experiments. In Figure 6A, the resulting concentration profiles from these four unseeded runs are shown. As expected,27 the MSZW widens with an increase in the addition rate of antisolvent. With the slower addition of antisolvent, there is typically an increase in final particle size due to a lower nucleation rate allowing for fewer crystals to share the same amount of solute.8 By operating at a lower supersaturation set point in a controlled antisolvent 3326



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Figure 7. (A) Supersaturation trajectory for the unseeded crystallization control experiment with a set point of 0.015 A.U. (B) Resulting antisolvent addition profile for the unseeded control experiment. Final crystal product obtained from (C) controlled experiment and (D) unseeded linear addition of 0.6 g/min.

varying minimum and maximum flow rates depending on the length and diameter of the tubing used. The minimum flow rate available for the set up used here was 0.35 g/min with a maximum flow rate of 20 g/min. This was generally acceptable for all crystallization controlled experiments performed here, although occasionally the antisolvent addition rate required would be less than 0.35 g/min during the early stages of the controlled experiments. This meant that the system would operate in an on/off mode initially. If the end of the batch is considered, problems are encountered when the required addition rate becomes very high due to most of the solute having been used at this point.8 Such a high addition rate at the end of the batch would effectively ruin all the good work previously performed by the control method so the maximum addition of antisolvent was kept at 7 g/min and the experiment stopped once 70 g had been added. The system of paracetamol in acetone and water has previously been reported on with regard to its high tendency to produce agglomerated crystal products. Previous studies28,29 showed that the solvent composition, initial supersaturation levels, and mixing intensity have a significant impact on the levels of agglomeration in the system. It has been observed30 that agglomeration in this system increases with an increase in acetone concentration. When the same magma density of equal seed crystals is used and also with constant and equal supersaturation there was still no change in this fact which led to the conclusion that the acetone molecule can only act as an H-bond acceptor which promotes crystal−crystal adhesion. With this in mind, it becomes increasingly difficult to define a successful controlled experiment for this system. The FBRM, which measures chord lengths of crystals, is not a really useful piece of information as

the chord lengths being measured are not providing a very good description of the high levels of agglomeration in the system and will report, say, a single large crystal as the same as a crystal made up of a high volume of smaller crystals, cemented together. A successful controlled experiment was then defined as one that maintained the supersaturation effectively and which was shown to have a positive effect on agglomeration and particle size. Figure 7A displays the resulting supersaturation profiles for the unseeded case, and it can be seen to be reasonably effective in maintaining supersaturation at the set point. The resulting addition profile can be seen in Figure 7B, which shows two dominant linear sections. The first is the linear addition of antisolvent proceeding nucleation. The second is a much faster linear addition of antisolvent to keep the supersaturation level in the reactor at the set point. It can be seen that a high addition of antisolvent was required in order to maintain that high supersaturation level in the reactor. An examination of the final crystal product from this unseeded controlled example compared to the final product obtained from the unseeded linear addition of 0.6 g/min is also shown. A small reduction in both fine material and agglomeration can be seen with a minor increase in particle size. 4.4. Seeded, Constant Antisolvent Addition Crystallizations. Two seeded experiments were conducted initially to understand the behavior of supersaturation when a seed load was used in the system and the calibration free techniques ability to monitor changes in the supersaturation of a seeded, antisolvent crystallization effectively. The addition rate was kept constant at 2 g/min, and two different seed loadings were used. The resulting concentration profiles for these two experiments 3327



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Figure 8. (A) Concentration profiles for the seeded crystallizations using two different seed loadings and a constant linear addition rate (2 g/min) of antisolvent. (B) Supersaturation profiles from the seeded crystallizations using two different seed loadings and a constant linear addition rate (2 g/ min) of antisolvent. Microscope images of final crystal product from the two seeded crystallization experiments where (C) 0.25% and (D) 0.5% seed loading was used with a linear addition rate of 2 g/min.

along with the previously measured solubility curve is displayed in Figure 8A. It can be seen that the higher seed loading has reduced the initial levels of supersaturation generated. A closer look at the supersaturation profiles further highlights this point. The lower seed loading produces a higher peak height which is also narrower in shape. The higher seed loading while suppressing secondary nucleation and minimizes the peak height produces a supersaturation profile that takes much longer to be consumed. There is still some supersaturation left even at the end of the batch experiment. It does, however, indicate that controlled seeding has the potential to be useful. The final crystal products from the two seeded experiments are compared as microscope images in Figure 8C,D. Both show strong evidence of agglomeration and a very similar particle size. It reinforces the point made by a previous study30 that it is the solvent composition that influences the effects of agglomeration as the seeding here is seen to make very little difference despite the fact that the supersaturation levels in the reactor are actually very different. An SEM image of the final crystal product obtained from the seeded case using 0.5% seed loading is shown in Figure 9. The point made previously about the FBRM chord length measurement can be seen more clearly here. Taking the large, agglomerated crystal in the center of the picture, it can be seen that it is composed of a large number of smaller crystals which have been cemented together. The FBRM beam while passing over this and measuring the chord length would see this as one single crystal and report it as long chord length.

Figure 9. SEM image of final crystal product obtained from seeded experiment using a linear addition rate of 2 g/min and a seed loading 0.5%.

While the FBRM is still a very useful tool in providing particle size information, this note of caution should be advised. Illustrated later are the FBRM trends for the controlled experiments which produce very similar mean, median, and mean square weight (MSQW) information, and these microscope and SEM images illustrate that although the information may be similar, the crystal product morphology is actually quite 3328



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Figure 10. (A) Concentration profiles of the three seeded controlled experiments. Three different set points were used along with a seed loading of 0.5%. (B) Supersaturation trajectories for the three seeded control experiments using a seed loading of 0.5% and three varying set points. (C) Antisolvent addition profiles for the three controlled seeding experiments using a seed loading of 0.5% and varying set points. Microscope image of final crystal product obtained from three controlled experiments (a) 0.0065 A.U., (b) 0.011 A.U., (c) 0.015 A.U., and (d) an unseeded linear addition experiment of 1 g/min.

different. The SEM image serves to highlight just how significant the agglomeration can be in this system. 4.4.1. Seeded Controlled Antisolvent Crystallization Experiments. Three experimental runs were undertaken to assess the performance and ability of this calibration-free control method to achieve constant supersaturation during the seeded batch addition of antisolvent. As has already been seen, the control algorithm is successful at maintaining the supersaturation at a specific set point in the unseeded case. For the purposes of this illustration, three separate set points

were chosen, shown in Figure 10A and a seed loading of 0.5% was used which was shown previously to sufficiently suppress secondary nucleation. In all three cases, the control algorithm was initiated once the seed had been added and the FBRM total counts had stabilized. The supersaturation was then kept at its set point by varying the addition of antisolvent the control method outlined previously. Figure 10B shows the trajectories of the supersaturation profiles. Previously, it was seen that the unseeded case allowed the peak height to rise to a value of 0.03 A.U. before nucleating and desupersaturating. In all three cases 3329



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Figure 11. (A) PSDs from three antisolvent control experiments as well as two seeded linear addition rate experiments for comparison. (B) FBRM square weighted distributions of three seeded control experiments at increasing supersaturation set points and two seeded experiments with constant linear addition rates of antisolvent.

using a Malvern particle sizing unit are displayed. There is a distinct increase in the particle size as observed by a shift to the right in the PSD using a decreased supersaturation set point. Compared to the two seeded experiments with a linear addition of antisolvent, there is an increase in the mean particle size being measured by the PSD. This can be seen in Table 2. The

presented here, the supersaturation jumps initially before leveling off along the set point where it is maintained for the duration of the experiment. During the initial stages of the controlled addition, there is an unsteady period where the required amount of antisolvent is overestimated due to the rapidly changing conditions in the reactor. This is a problem with a simple control method such as this where tuning parameters are not in place. The resulting profiles of antisolvent addition are presented in Figure 10C. A general pattern emerges for all three runs: a linear addition of antisolvent initially, followed by a more curved, quadratic addition as the experiment progresses. It is in this region that the control method is most effectively manipulating the rate of addition of antisolvent. As the rate of deposition of solute onto crystals already present increases, the rate of supersaturation consumption increases which then requires the control algorithm to provide more antisolvent to generate further amounts of supersaturation. The resulting antisolvent addition rate profiles for each of the three cases are quadratic in shape, previously shown6 to be a more effective addition strategy of antisolvent than standard linear addition rate profiles. These profiles have the potential to be used for the scale-up of the process and eliminate the need for extensive experimentation and trial and error approaches. The microscope images highlight the final crystal product yielded from these controlled process runs as well as an unseeded linear addition rate experiment. It is not ideal to compare images from a controlled, seeded experiment to an unseeded uncontrolled process experiments, but they are presented for illustration purposes. An increase in the particle size and a small reduction in agglomeration can be seen, although agglomeration has not entirely been eliminated. It could be proposed that agglomeration could be entirely removed using a lower initial concentration of acetone. The method proposed here can be seen to be successful at using a calibration -free method to maintain supersaturation at a desired level to reduce batch time and improve particle characteristics, but studies on an alternative antisolvent crystallization system would demonstrate its effectiveness as a robust and reliable approach. 4.5. PSD and FBRM Trending of Crystallization Experiments. In Figure 11A, the resulting PSDs measured

Table 2. Mean Square Weight Values and Volume Based Mean Values from Three Controlled Experiments at Different Set Points, Two Seeded Experiments Using Two Different Seed Loadings, and One Unseeded Experiment experiment

mean square weight (μm)

D43 (μm)

0.0065 A.U. 0.011 A.U. 0.015 A.U. 2 g/min (0.5 wt %) 2 g/min (0.25 wt %) 1 g/min unseeded

164 156 146 133 140 118

294 265 258 242 257

lower seed loading also gives an increased particle size which is to be expected. The resulting square weighted distributions from the FBRM are presented in Figure 11B. As previously mentioned, agglomeration is a troublesome aspect of this system, and it presents a problem for the FBRM in discerning between crystals that are regularly shaped and those that are clumps of smaller crystals agglomerating to form a similar-sized shape. The FBRM would measure both of these as the same size as it is measuring a chord length of the particle and cannot distinguish between clusters and single crystals. As such, the FBRM weighted distributions should be treated with caution. It is a useful instrument for providing qualitative information, and in this instance a small shift to the right can be observed in the mean square weight, an indication of an increase in particle size, which would strongly support the conclusion that the utilization of the supersaturation control technique has allowed for increased particle growth but as agglomeration is so persistent in the system, the data are not wholly reliable. Table 2 presents the resulting mean square weights and volume based means (D43) from the three controlled experiments, two seeded experiments with a linear addition rate of 2 g/min using two different seed loadings, and one 3330



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C* ΔC ΔT F K M M M Q S tK

unseeded experiment. The D43 increases with a lowering of the supersaturation set point, and in general, the MSQW does too but not to the same extent. Although the differences are not dramatic, the increase in particle size is still evident.

5. CONCLUSIONS Crystallization of paracetamol from acetone and water was studied using ATR-FTIR spectroscopy across a series of different constant antisolvent addition rates, both unseeded and seeded, using a single peak height in a spectral region to gain a qualitative understanding into the supersaturation levels encountered during the process. In turn, this understanding led to the development of a calibration-free, novel control technique which allowed a desired supersaturation level to be maintained over the course of a batch crystallization experiment with the aim of improving particle size and developing “optimal” antisolvent addition trajectories that could in turn be used for the scale up of the process. The simple control algorithm developed allowed for the effective maintaining of supersaturation levels during without any complex calibrations having been performed. Four separate cases were investigated to determine whether the control technique was successful, three seeded and one unseeded control experiments at varying set points, and the control algorithm was successful in maintaining the supersaturation at the desired level. It was shown that improvements to final particle size could be made, as well as some improvement in agglomeration levels and a reduction in batch time. The method has the potential to be used at scale for easier implementation of a supersaturation control method for antisolvent crystallizations, although its application to alternative antisolvent systems may be limited due to influences of solvents on the single selected peak where they may interfere and where the single peak may not always describe the API in question, at all times.

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saturated solute concentration (g/g mixed solvent) Ssupersaturation (A.U.) sampling Interval (min) feed rate of antisolvent (g/min) time instant mass of liquid in the crystallizer (g) mass of liquid in the crystallizer at time zero mass of liquid needed in the crystallizer amount of antisolvent added (g) solvent composition sampling instant

Superscripts and Subscripts

0 i K K+1 PH S

■

initial value at the beginning of the crystallization denotes species value at sampling instant tK value at sampling instant tK+1 peak height set point

REFERENCES

(1) Mersmann, A. Supersaturation and nucleation. Chem. Eng. Res. Des. 1996, 74 (A7), 812−820. (2) Yu, L. X.; Lionberger, R. A.; Raw, A. S.; D’Costa, R.; Wu, H. Q.; Hussain, A. S. Applicatlons of process analytical technology to crystallization processes. Adv. Drug Delivery Rev. 2004, 56 (3), 349− 369. (3) Togkalidou, T.; Fujiwara, M.; Patel, S.; Braatz, R. D. Solute concentration prediction using chemometrics and ATR-FTIR spectroscopy. J. Cryst. Growth 2001, 231 (4), 534−543. (4) Miller, S. M.; Rawlings, J. B. Model identification and control strategies for batch cooling crystallizers. AIChE J. 1994, 40 (8), 1312− 1327. (5) Ridgway, K.; Carreon, O. H. Kinetics of crystallization of paracetamol and phenacetin from aqueous ethanol. J. Pharm. Pharmacol. 1977, 29, P48−P48. (6) Zhou, G. X.; Fujiwara, M.; Woo, X. Y.; Rusli, E.; Tung, H. H.; Starbuck, C.; Davidson, O.; Ge, Z. H.; Braatz, R. D. Direct design of pharmaceutical antisolvent crystallization through concentration control. Cryst. Growth Des. 2006, 6 (4), 892−898. (7) Mullin, J. W.; Leci, C. L. Evidence of molecular cluster formation in supersaturated solutions of citric acid. Philos. Mag. 1969, 19 (161), 1075−1092. (8) Yu, Z. Q.; Chow, P. S.; Tan, R. B. H. Application of attenuated total reflectance-fourier transform infrared (ATR-FTIR) technique in the monitoring and control of anti-solvent crystallization. Ind. Eng. Chem. Res. 2006, 45 (1), 438−444. (9) Yu, Z. Q.; Chew, J. W.; Chow, P. S.; Tan, R. B. H. Recent advances in crystallization control - an industrial perspective. Chem. Eng. Res. Des. 2007, 85 (A7), 893−905. (10) Jagadesh, D.; Kubota, N.; Yokota, M.; Sato, A.; Tavare, N. S. Large and mono-sized product crystals from natural cooling mode batch crystallizer. J. Chem. Eng. Jpn. 1996, 29 (5), 865−873. (11) Fujiwara, M.; Chow, P. S.; Ma, D. L.; Braatz, R. D. Paracetamol crystallization using laser backscattering and ATR-FTIR spectroscopy: metastability, agglomeration, and control. Cryst. Growth Des. 2002, 2 (5), 363−370. (12) Fujiwara, M.; Nagy, Z. K.; Chew, J. W.; Braatz, R. D. Firstprinciples and direct design approaches for the control of pharmaceutical crystallization. J. Process Control 2005, 15 (5), 493− 504. (13) Dunuwila, D. D.; Carroll, L. B.; Berglund, K. A. An investigation of the applicability of attenuated total-reflection infrared-spectroscopy for measurement of solubility and supersaturation of aqueous citricacid solutions. J. Cryst. Growth 1994, 137 (3−4), 561−568. (14) Dunuwila, D. D.; Berglund, K. A. ATR FTIR Spectroscopy for in situ measurement of supersaturation. J. Cryst. Growth 1997, 179 (1− 2), 185−193.

AUTHOR INFORMATION

Corresponding Author

*E-mail: damian.k.duff[email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This material is based upon works supported by the Science Foundation Ireland under Grant No. 07/SRC/B1158. ABBREVIATIONS ATR-FTIR attenuated total reflectance Fourier transform infrared AS antisolvent AU absorption units CFC concentration feedback control CLD chord length distribution CSD crystal size distribution DNC direct nucleation control FBRM focused beam reflectance measurement MSQW mean square weight (FBRM statistic) PH peak height PSD particle size distribution SEM scanning electron microscopy Notation

a0, a1, a2 constants of solubility equation, dimensionless C solute concentration (g/g mixed solvent) 3331



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Novel, Calibration-Free Strategies for Supersaturation Control in

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