Understanding and Avoidance of Agglomeration During Drying

Article pubs.acs.org/OPRD

Understanding and Avoidance of Agglomeration During Drying Processes: A Case Study Melissa Birch and Ivan Marziano* Pfizer Worldwide Research & Development, Ramsgate Road, Sandwich, Kent CT13 9NJ, United Kingdom S Supporting Information *

ABSTRACT: A systematic investigation into possible causes of agglomeration during drying was carried out, with a view to reduce the amount of agglomerates present in an active pharmaceutical ingredient. Several tools used in this study are described, including rheology to elucidate how the interplay of agitation (during drying and critical solvent levels) can aggravate agglomeration, and sieving to quantify the extent of agglomeration and the hardness of the resulting agglomerates. Finally, the implementation of a modified wash and the use of a blow-through protocol were demonstrated at pilot-plant scale to be effective in dramatically reducing the extent of agglomeration.

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INTRODUCTION In recent years, the increased awareness of the importance of the physical properties of active pharmaceutical ingredients (APIs) on quality and manufacturability of dosage forms has expanded beyond consideration of the solid form1 to encompass a more holistic understanding of the relationship between structure, properties, processing, and performance of materials, as captured in the Materials Science Tetrahedron schematic.2 Implicit in this approach is an understanding of the impact of individual manufacturing unit operations on API physical properties, typically including crystallization, filtration, drying, and a particle size reduction step. If the latter is embedded in the crystallization, for example through direct control of particle properties to a desired target or via wet milling, then the drying step becomes de facto the stage gate for the transition from API to drug product manufacturing, and can ultimately play a key role in defining the physical properties of the material transferred through to secondary manufacturing. The effects of drying processes on the physical properties of pharmaceutical materials have been well documented elsewhere.3,4 Nevertheless, there is a scarcity of predictive tools in the area, and indeed Kemp and Oakley have described drying as “the graveyard of academic theory”,5 pointing out the complex interplay of material properties, liquid- and vapour-phase processes, and equipment-dependent parameters involved in these processes. Some predictive tools, however, do exist and have been used during industrial process development, for example to predict the scale-up of contact drying processes from 200 g to 1000 kg scale.6 Indeed, due to the inherent complexity of the process, some of the simpler models have proven effective in providing fit-for-purpose predictions for drying operations.7 Within Pfizer Worldwide Research & Development, an initiative aimed at identifying predictive and simulation tools to assess the impact of filtration and drying on API physical properties has led to the development of assessment tools for attrition and agglomeration.8 In this contribution, a strategy for the prediction, prevention, and quantification of agglomeration © 2013 American Chemical Society

using one of the tools developed as part of this initiative is outlined. In particular, a remedy was sought to an increase in the levels of agglomeration observed after the isolation of an API, compound A, which could in turn cause issues with drug product potency and manufacturing. After an initial brainstorm to evaluate possible root causes for the change in the physical properties of the isolated material, two were identified as likely, namely excessive residual solubility in the final filtration cake wash causing the formation of solid bridges upon drying, and the combined action of agitation and residual solvent exercising capillary forces and promoting the formation of aggregates of particles that would eventually be consolidated during solvent removal. Further investigation based on comparative solubility and rheology studies furthered the understanding of these two effects and ultimately informed process modifications, thus leading to near-complete removal of agglomeration from the isolated API.

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EXPERIMENTAL SECTION

Rheology Measurements. All rheology measurements were carried out using a mixer torque rheometer (Caleva model MTR-3; Dorset, England). During a typical experiment, approximately 30 g of compound A were placed in the rheometer′s bowl. All measurements were taken with an agitation speed of 50 rpm. After an initial torque measurement of the dry powder, up to 20 aliquots of the chosen binder were added every 30 s until the mixture had assumed the characteristics of a slurry. Binder additions were 1 mL at the beginning of the measurement cycle, then 2 mL. Several parameters were recorded as part of each experiment after each binder addition, including mean torque intensity across several measurements.

Special Issue: Engineering Contributions to Chemical Process Development Received: April 15, 2013 Published: June 4, 2013 1359

dx.doi.org/10.1021/op4000972 | Org. Process Res. Dev. 2013, 17, 1359−1366

Organic Process Research & Development

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Figure 1. Scanning electron micrographs and photos of sieve cuts for material showing low levels of agglomeration (a, batch from old process) and more substantial agglomeration (b, batch from new process).

Solubility Measurements. All solubility measurements were carried out gravimetrically. A slurry of compound A at the desired temperature was prepared in a vial. Following a suitable equilibration period, the contents of the vial were allowed to settle; then a known volume of the resulting supernatant liquid was siphoned off using a pipette and rapidly transferred to a separate, preweighed vial, from which the solvent was allowed to evaporate, ultimately causing the formation of a dry residue of compound A. The latter was weighed, thus providing a measurement of solubility at the temperature of equilibration. Agitated Filter Dryer Experiments. All drying experiments were conducted in an Algochem ARLA laboratory-scale agitated filter dryer (AFD). For each experiment, the API was loaded first onto the AFD and was then washed with the chosen solvent mixture, which had been prechilled to 10 °C. Upon completion of washing, the damp solid was dried at 60 °C at 100 mbar and with agitation at 8 rpm. For selected batches, a blow-through step was performed between washing and vacuum drying as described in the Results and Discussion section. Pressure−Flow Rate Correlation Determination. In order to determine the pressure−flow rate correlation, a solid bed was prepared in the lab AFD by adding compound A and prechilled wash, followed by filtration. Set nitrogen pressures were then applied to the AFD, and the resulting flow rates were measured at the AFD outlet using a Cole-Parmer flow meter. This protocol was repeated with different amounts of compound A to give rise to solid beds of different thickness, and at different overhead pressures. Agglomeration Quantification by Sieving. Sieving was used to quantify both the extent of agglomeration and agglomerate hardness. An Endecotts Octagon digital sieve shaker was fitted with a 2 mm sieve and a receiver. Each sieving cycle lasted 1 min and was carried out with amplitude equal to 9. The percentage of compound A held on the sieve after one cycle with respect to the weight originally added was taken as a comparative measure of the extent of agglomeration. Additional, identical cycles were then carried out sequentially to determine agglomerate hardness.

increase in the amount of agglomeration, which was observed following the isolation of compound A during recent manufacturing campaigns. This observation was in contrast with examination of previous isolated batches, which showed substantially less agglomeration. The difference in the extent of agglomeration between older and more recent batches is shown in Figure 1, which includes both scanning electron micrographs and photos of the material held on a sieve following equivalent sieving protocols for the two samples. The presence of agglomerates was linked to the drying stage of API manufacturing following an experiment where slurry samples were collected at regular intervals during crystallization, showing the presence of primary particles only, whereas agglomeration was observed following isolation of the product. The initial step was to brainstorm possible causes of agglomeration during drying, which included: (1) The impact of compressive forces exerted by the agitator on the API cake during agitated drying. This possible root cause was ruled out, as the drying/agitation regime was maintained equivalent during all batches. Additionally, when a “dry” run (no solvent involved) to assess the impact of compression from agitation was carried out in the laboratory, no significant agglomeration increase was recorded from both visual inspection of the product and sieving. (2) Agglomeration resulting from ripening of surface amorphous content. If the API contained even a small percentage of amorphous material, it is possible that over time this amorphous material would ripen to crystalline compound A, causing the formation of interparticular solid bridges and consequent agglomerates. This possible root cause was ruled out because agglomeration was observed immediately upon isolation rather than on storage, and because no differences in crystallinity were noted from powder X-ray diffraction (PXRD) patterns between just-isolated API and compound A held on storage. (3) Differences in adhesion/cohesion behavior for particles isolated from different washes. Older batches were washed with an acetone/water mixture, whereas 2-methyl tetrahydrofuran (2-MeTHF) was adopted as a wash for more recent lots. This possible root cause was ruled out, as qualitative inspection revealed no difference in API “stickiness” when the wash was changed.

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RESULTS AND DISCUSSION Possible Root Causes of Agglomeration during Drying. The initial problem statement related to a substantial 1360



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Table 1 summarises the results of sieving data for several batches, showing the range of ABIs recorded and agglomeration

(4) The impact of solubility in the different washes. Specifically, the greater the solubility in the wash solvent mixture, the greater the likelihood of solid bridge formation upon drying due to the presence of dissolved API. As solubility measurements revealed that the solubility of compound A in 2MeTHF at the wash temperature was over 7 times higher than that measured in the acetone/water mixture, this was considered a likely cause for the rise in agglomeration for recent batches. (5) Agglomeration due to capillary forces (caused by solvent holding particles together during drying) being aggravated by agitation. During the early stages of drying, any residual liquid can induce the formation of liquid bridges between compound A particles.9 These forces, in tandem with agitation, can encourage the formation of agglomerates which are then further cemented upon drying, for example through the mechanism described above. Measurement of the Extent of Agglomeration and Agglomerate Hardness. In order to further assess the root cause of agglomeration and any process improvements to mitigate its occurrence, it was necessary to develop a comparative approach to assess the impact of process enhancements on both the extent of agglomeration and agglomeration hardness. While the extent of agglomeration can be easily quantified through sieving, there is no definitive technique to characterize agglomerate hardness. Various approaches were tried, including, for example, texture analysis10 and rheology,11 although ultimately sieving again appeared to be the most straightforward method to assess hardness. In order to ensure consistency between batches processed using sieving, an automated sieve shaker was used and programmed with cycles lasting one minute with amplitude set to 9. The percentage of the initial mass retained on a 2 mm sieve after one sieve-shaking cycle was taken to be a measure of the extent of agglomeration. Additionally, the rate of decrease in the percentage retained on the 2 mm sieve through successive cycles was taken as a measure of agglomerate brittleness. The data obtained (Figure 2) show that the percentage retained as a

Table 1. Extent of agglomeration and ABIs measured for compound A ingoing batch batch batch batch batch batch batch batch batch batch batch batch batch batch batch batch

% retained after first pass

agglomerate brittleness index (ABI)

8.5 24.9 14.5 10.3 28.5 23.2 16 6.9 0.8 7.2 0.2 3.6 3 1.3 3

0.44 0.33 0.66 0.52 0.18 0.84 0.88 0.85 2 0.1 >2 1.6 0.7 0.24 0.2

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

recorded across batches. Additional examples to elucidate ABI calculations are included as Supporting Information (SI). Understanding the Impact of Product Solubility in the Wash on Agglomeration. During drying, solvent is removed from a wet cake of the product. Any material dissolved in the solvent being removed will precipitate during drying, potentially in the form of solid bridges that can hold particles together as agglomerates. Clearly, the higher the solubility of the product in the wash liquors, the greater the extent of solid bridge formation will be. The relevant solubility data for compound A are presented in Table 2, indicating that that the Table 2. Solubility data for compound A in possible wash solvent media solvent system

solubility at wash temperature (g/L)

acetone/water 1:1 v/v 2-MeTHF 2-MeTHF/water 99:1 v/v 2-MeTHF/water 96:4 v/v

2.0 15.4 6.4 14.5

addition of a small percentage of water to the current wash that is, modifying the wash composition from neat 2-MeTHF to 2-MeTHF/water 99:1 v/vwould bring about a near-3-fold reduction in solubility. This modification was desirable since it would avoid the introduction of a new solvent such as acetone into the process, as 2-MeTHF/water is the current crystallization solvent mixture. This alternative wash appeared, in theory, likely to reduce agglomerate formation and would result in solubility broadly similar to that of the wash previously used, which was a mixture of acetone and water. In order to ascertain the contribution of this potential mechanism towards agglomeration, two laboratory experiments were carried out using the AlgoChem ARLA filter dryer, both involving washing of the same batch of compound A and subsequent drying. During the first experiment, compound A was washed with neat 2-MeTHF, whereas during the second experiment 2-MeTHF/water 99:1 v/v was used as the wash. The products from the two experiments were characterised using sieving, and agglomerate hardness was compared using

Figure 2. Sieving data for a typical compound A batch shown as mass retained on a 2 mm sieve following a series of 1 min, amplitude 9 cycles through an Endecotts Octagon sieve shaker. In this case, an ABI of 0.44 was recorded.

function of cycle number decays across successive sieve cycles. The data were fitted to a power function, and the absolute value of the exponent of the power function, as illustrated in Figure 2 for a typical batch, was defined as the agglomerate brittleness index (ABI), with a higher ABI indicating more brittle, softer agglomerates. 1361



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the ABI introduced in the previous section, with results summarised in Table 3. Table 3. Sieving data showing a comparison of 2-MeTHF vs 2-MeTHF/water 99:1 v/v as wash solvents experiment experiment 1: 2-MeTHF wash experiment 2: 2-MeTHF/ water wash



24.9

0.33

14.5

0.66

The data show that the material washed with 2-MeTHF/ water 99:1 v/v contains significantly fewer agglomerates than material washed with 2-MeTHF alone, and that the resulting agglomerates in the former have a higher ABI than the latter, meaning that 2-MeTHF/water 99:1 v/v generates softer agglomerates, as suggested by solubility data. As such, the results indicate that switching the wash to a solvent or solvent mixture where product solubility is lower would decrease the extent of agglomeration and the strength of the resulting agglomerates. However, implications on impurity purge during washing would also have to be assessed. Assessing the Combined Impact of Capillary Forces from Residual Solvent and Agitation during Drying. The critical level of solvent that maximises the tendency to agglomerate, or “sticky point”,12 was assessed using rheology. Knowledge of the sticky point during drying development is used to determine the solvent levels above which agitation must be avoided in order to minimise the risk of agglomerate formation, the main concern being that the combined effect of capillary forces, which are at their maximum at the solvent level corresponding to the sticky point, and agitation would ultimately encourage the formation of agglomerates. All measurements were carried out using a Caleva MTR-3 mixed torque rheometer. Mixer torque rheometry is widely used in the pharmaceutical industry, for example for the assessment of binder/powder interaction in wet granulation processes.13,14,14,15 During a typical rheology experiment, known amounts of “binder”, in this case the wash solvent, are added at regular intervals. For the experiments described here, the binder addition profile is described in Table 4. Typically ∼30 g of solid

Figure 3. Rheology plot for a typical compound A experiment with 2MeTHF as a binder.

summary of data showing the maximum torque recorded for each run and the binder amount corresponding to each maximum is shown in Table 5. Additional information on the use of mixed torque rheometry is presented elsewhere in this issue.8 Table 5. Summary of rheology data for compound A binder 2-MeTHF/water 99:1 v/v 2-MeTHF/water 99:1 v/v 2-MeTHF/water 99:1 v/v 2-MeTHF/water 99:1 v/v 2-MeTHF/water 99:1 v/v 2-MeTHF 2-MeTHF/water 99:1 v/v acetone/water 1:1 v/v 2-MeTHF:water 96:4 v/v 2-MeTHF/water 99:1 v/v

vol./addition (mL)

1− 10 11−20 total (additions 1−20)

1 2 30 mL

binder ratio at max peak torque (mL/g)

0.090

0.164

large particles

0.074

0.262

typical particles

0.074

0.259

typical particles

0.133

0.288

small particles

0.152

0.197

small particles with water

0.074 0.100

0.230 0.230

0.122

0.320

0.072

0.260

typical particles

0.070

0.262

typical particles

comments

typical particles

The data presented in Table 5 essentially clarify several aspects pertaining to the interplay of the solid/liquid system involved and the sticky point, in particular: • general tendency of compound A particles to agglomerate • impact of the nature of the binder (i.e., the wash) used on the tendency to agglomerate and on the hardness of the resulting agglomerates • impact of compound A physical properties (e.g., particle size) on the propensity to agglomerate A number of conditions pertaining to both the composition of the wash and the physical properties of compound A were explored during these experiments, as described in Table 5. Within the range of particle properties and different binders explored, the results show that the greatest tendency to agglomerate can occur with solvent levels ranging between 0.16 and 0.32 mL of solvent/g compound A. In practical terms, if agitation during drying is started when the residual solvent level is above the “sticky point” value (that is, the solvent level corresponding to the maximum torque needed to maintain

Table 4. Binder addition profile for rheology experiments addition no.

max torque (N m)

were charged at the start of each experiment. When the binder was added, the mixture was agitated at a fixed paddle rotation rate and for set lengths of time, with various torque-related parameters being measured as a function of the amount of total binder added. The torque required to maintain constant paddle rotation rate will be at a maximum when the agglomerates are at their strongest, while excessive addition of binder results in a mixture that is best described as a slurry and has the typical mobility of one. A typical plot of torque as a function of added binder is shown in Figure 3. The reported torque value refers to measured torque intensity, which is averaged over several measurements carried out following a binder addition. A 1362



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constant paddle rotation speed), agglomeration would be encouraged through the combined action of capillary forces from the solvent and mechanical forces from agitation. The hardness of these agglomerates is related to torque as measured by rheology and is listed in Table 5 as “max torque (N m)”. This is measured in situ as, typically, further binder addition during rheology measurements results in the formation of a slurry, thus preventing characterization by sieving. The impact of the nature of binder/wash solvent is shown in Figure 4. All data shown were acquired on the same ingoing

Figure 5. Impact of particle size on sticky point and agglomerate strength. Binder is 2-MeTHF in all cases.

particles. Indeed, if an estimate of surface area for each batch is obtained from the corresponding particle size distribution measurements using the software Sympatec Windox, which is commonly used for analysis of particle size data acquired through laser diffraction, and the data in Figure 5 are replotted as function of specific surface area, a correlation between the latter and the solvent amount corresponding to the “sticky point” emerges (Figure 6). Figure 4. Impact of wash composition on compound A agglomeration.

batch of material, i.e. the same physical properties such as particle size and shape. Essentially, little difference is seen between neat 2-MeTHF and water-wet 2-MeTHF as wash solvents for the same batch, in terms of both solvent level corresponding to the sticky point and strength of the resulting agglomerates. When acetone/water 1:1 v/v, which was the final wash used for the earlier compound A batches, is used instead, the sticky point occurs at a higher solvent level (0.32 mL solvent/g compound A vs 0.23−0.26 mL solvent/g compound A for neat or water-wet 2-MeTHF); that is, there is a lower tendency to agglomerate in acetone/water. However, the resulting agglomerates are harder in this solvent system. In practical terms, for the worst case scenario in terms of particle size and with a 2-MeTHF-based wash, the results essentially indicate that the risk of agglomeration during drying is at its maximum if agitation is started when the solvent content in the wet cake is greater than 13% w/w. This figure was obtained from the lowest amount of binder for which max agglomeration was observed, as reported in Table 5, 0.16 mL/g, converted to a weight basis. Additionally, a series of rheology measurements was carried out where the same binder was used (neat 2-MeTHF), but different batches of compound A were considered to capture the impact of particle size on the sticky point. The results show that, while typical batches show similar sticky point values, there is a variation in the amount of binder corresponding to maximum agglomeration for batches that are smaller or larger in particle size, as shown in Figure 5. According to this data, batches containing smaller particles will require more solvent to reach the sticky point, which is expected as these batches will have greater specific surface area. As capillary forces holding particles together are expected to act on the particle surface, greater surface areathat is, smaller particleswill require a greater amount of binder to result in the same capillary forces compared to larger, lower surface area

Figure 6. Sticky point occurrence as a function of batch specific surface area.

Overall, the following conclusions could be drawn from the rheology studies described here: (1) For 2-MeTHF or aqueous 2-MeTHF, the greatest risk of agglomeration occurs if agitation during drying is started when the cake is >13% w/w wet. The actual figure depends on specific surface area, which is linked to particle size. (2) Good reproducibility between batches with similar particle sizes was observed. (3) An acetone/water wash might slightly reduce tendency to form agglomerates; however, the resulting agglomerates will be harder to disrupt compared to 2-MeTHF-based systems. In order to substantiate some of the conclusions from the studies described here, an experiment was carried out where agitation was started during drying when compound A was still very wet. For this experiment, agitation was started when the solid was still 32% w/w wet with 2-MeTHF/water 99:1 v/v, resulting in the initial formation of large agglomerates, as shown in Figure 7. These agglomerates were subsequently broken down into smaller pieces by the mechanical action of the 1363



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the propensity to agglomerate. A switch from a 2-MeTHF to a 2-MeTHF/water 99:1 v/v wash was identified as an important step to decrease agglomeration during drying. Additionally, the results show that starting agitation during drying when the cake is more than 13% w/w wet increases the risk of agglomeration. As a precautionary measure to decrease solvent levels at the start of agitated drying to below the sticky point, a blowthrough stage, i.e. convective drying involving a nitrogen pressure gradient passing through the wet product cake postfiltration, was suggested as an initial step to reduce solvent content in the cake. Development of a Scale-up Strategy for the BlowThrough Stage. It was shown in the laboratory that, for a batch of compound A isolated on the AlgoChem ARLA AFD equipment, a 1-h N2 blow-though was sufficient to reduce the residual solvent levels below the sticky point, thus reducing the risk of agglomeration when agitation was started. However, it was necessary to develop a strategy for the scale-up of this unit operation. In order to ensure equivalent blow-through conditions in the laboratory and in the plant, the Carman−Kozeny equation16 was used (eq 1):

Figure 7. Large agglomerates of compound A observed during an AFD experiment. Note that the inner diameter of the laboratory agitated filter dryer is approximately 6 cm.

agitator during the later stages of the drying phase; however, characterization of this batch by sieving still showed an extremely high agglomerate content (28.5% w/w retained on the 2 mm sieve after one cycle) and low ABI (0.18), indicating hard agglomerates. Additionally, an experiment that employed the earlier process wash, acetone/water 1:1 v/v, was carried out and compared to the proposed new wash, 2-MeTHF/water 99:1 v/v, to assess whether comparable levels of agglomeration were obtained. During both experiments, a N2 blow-through was performed to ensure that residual solvent levels prior to agitation start were below the “sticky point” threshold indicated by the rheology experiments. The results are shown in Table 6. As expected

(1 − ε)2 μvs ΔP = 180 L ε3 Dp2

where ΔP is the pressure difference, L is the height of the bed, ε is the void fraction of the solid bed, μ is the viscosity of the solvent medium, vs is the gas flow used during the blowthrough normalised by area, and Dp is the particle diameter. If the material used to characterise the blow-through stage in the lab is representative of typical plant material, then ε and Dp are essentially constant, as is μ if the same solvent medium is used at both scales. Equation 1 can then be rearranged to:

Table 6. Comparison of different washes in terms of extent of agglomeration and agglomerate hardness

ΔP = KLvs

(2)

where K = 180(1 − ε) μ/ε Dp . Using eq 2, a correlation can be built between flow rate vs and the pressure difference ΔP above and below the filter cake, with a linear relationship that depends on L, the thickness of the filter cake. If a laboratory-based blow-through protocol is developed which considers both the flow rate employed and the amount of time the flow is applied for to achieve the require amount of solvent removal, then eq 2 can be used to calculate the ΔP that would result in an equivalent flow rate at the larger scale for constant blow-through time between scales. Several lab experiments were carried out in order to experimentally derive the constant K for compound A in 2-MeTHF/water 99:1 v/v mixtures. During these experiments, representative compound A was washed using the solvent mixture in the AlgoChem ARLA agitated filter dryer; then after filtration, a N2 purge/ blow-through was applied to the wet cake. The pressure used during the blow-through was controlled automatically using the AlgoChem software, while the corresponding N2 flow rate was measured using a gas flow meter fitted to the AFD outlet. The pressure could also be modified during a single experiment to obtain multiple data points for a fixed cake depth. A typical set of results is shown in Table 7. For example, for one of the experiments, a 2 h blow-through at 2000 mbar (ΔP ≈ 1000 mbar) was sufficient to bring down the solvent content in the wet solid from an initial 23 w/w% to ∼1%. For this experiment, the cake height was measured to be 2

ingoing batch 2-MeTHF wash 2-MeTHF/water (99:1 v/ v) wash Acetone/water (1:1 v/v) wash



8.5 3.6

0.44 1.6

3.0

0.7

(1)

from rheology experiments, there is a slightly lower tendency to form agglomerates in the acetone/water system, as measured by the amount of agglomerates retained after one sieving cycle. However, the agglomerates are softer for the 2-MeTHF/water system than for the acetone/water system, as shown by the lower ABI for material isolated from the latter. Both of those batches, however, show significantly less agglomeration than a batch washed with 2-MeTHF alone. Note, however, that in the case of 2-MeTHF alone, an additional impact from the increased solubility of compound A in the wash is present. Solubility in acetone/water and 2-MeTHF/water 99:1 v/v is approximately equivalent. Conclusions from Laboratory-Scale Experiments. After the initial brainstorming exercise, efforts were focused on understanding the impact of residual compound A solubility in the wash mixture, and of the amount of residual solvent at the beginning of agitated drying on agglomerate formation. The results indicated that the nature of the wash (being the last solvent in contact with the solid product prior to drying) affects 1364

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Table 7. ΔP-flow rate data for a typical compound A wet cake with 2-MeTHF/water 99:1 v/v as the wash solvent set pressure (mbar)

outlet pressure (mbar)

ΔP (mbar)

flow (L/min)

flow per unit area (L/min m2)

2030 2220 1367 1919 1858 1668 1460 1720

1008 1008 1008 1008 1008 1008 1008 1008

1022 1212 359 911 850 660 452 712

9.5 11.5 2.1 7.7 7 5 3 5.5

6857.0 8300.6 1515.78 5557.8 5052.5 3609.0 2165.4 3969.8

a wash and no blow-through, and one with 2-MeTHF/water and a blow-through step is shown in Figure 9.

1.3 cm. When the data acquired over several experiments were plotted (Figure 8), the value of K for typical compound A

Figure 9. Amount of agglomerates retained through a 2 mm sieve after a 1 min sieve shaking cycle for a batch with 2-MeTHF only as a wash and no blow-through (original drying protocol) and one with a 2MeTHF/water wash and a 1-h blow through (modified drying protocol). Both batches were carried out at pilot-plant scale.

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CONCLUSIONS While the intimate kinetics of individual batch-drying regimes17 are often difficult to measure, a clear understanding of the desired outcome from the unit operation is beneficial and can drive an empirical strategy for process understanding. In this case, avoidance of agglomeration was identified as a target process attribute. A detailed investigation of possible root causes for the emergence of agglomeration revealed that a recent swap in the wash solvent was partly responsible, and that additionally the interplay between residual solvent levels and agitation during drying could further encourage aggregation, eventually leading to agglomeration following drying. During the course of this study, rheology was employed to understand the impact of residual solvent levels and agitation during drying, while sieving was used to develop a novel approach to quantify agglomerate hardness for comparative purposes. Finally, the use of a solvent wash in which solubility was lower and the implementation of a blow-through step prior to agitated drying were sufficient to reduce the occurrence of agglomeration to negligible levels.

Figure 8. Experimental relationship between flow rates and ΔP for typical compound A.

particles was derived as the slope of the line representing ΔP as a function of the product of flow rate (normalised by area) and cake height (which was measured experimentally in the lab, but can be predicted for the larger scale on the basis of the bulk density of the product and the dimensions of the filter used). On the basis of this correlation, K was 0.0691 N*s*m−4. Having obtained K for the compound A/wash system, eq 2 was used to scale up an optimised drying protocol for a forthcoming pilot-plant batch. Using an average bulk density value of 0.65 g/cm3 for the solid, and a predicted yield of 10.2 kg for the batch, equivalent to 0.0157 m3 solids volume, a cake height of 5.2 cm was predicted in plant dryer, which had a plate surface area of 0.3 m2. Laboratory experiments had shown that a flow rate/area of 6857 L/min*m2 applied for 2 h would result in sufficient solvent removal prior to agitation start, thus decreasing the risk of agglomeration. With K = 0.0691 N*s*m−4 as per the above correlation, and L the cake height on scale-up equal to 0.052 m, based on eq 2, ΔP corresponding to the desired flow rate was calculated to be 24.6 psi or 1700 mbar. Assuming ambient pressure to be ∼1050 mbar, this equated to a pressure of 2700 mbar applied to the postfiltration wet cake in the plant dryer for 2 h. In practice, the level of solvent removed with this blowthrough protocol is beyond the agglomeration derisking needs, and a blow-through at 2000 mbar for 1 h was sufficient to remove residual solvent levels to

Understanding and Avoidance of Agglomeration During Drying

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