Semicontinuous Blending of Pharmaceutical Ingredients and the Impact of Process Parameters on the Blending Performance of an Integrated Feeder Blender Operating Semicontinuously

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Introduction
Te pharmaceutical industry has predominantly operated on batch manufacturing.Only a handful of Food and Drug Administration (FDA) approved products have utilized continuous manufacturing.Tis is because most companies already have all the necessary equipment needed for the batch manufacturing and have ample regulatory experience in fling products with agencies.Equipment mapping, cleaning, and accommodating multiple products are also more straightforward in batch manufacturing.However, the industry is undergoing many changes to improve product quality and reduce product development time [1,2].Advancements in computing and modelling, Process Analytical Technology (PAT) [3], Industry 4.0 implementation, Quality by Design (QbD), Quality by Control (QbC), and digital twin technologies have all driven the adoption of continuous manufacturing in the pharmaceutical feld [4][5][6][7].Te signifcant benefts of adopting continuous manufacturing include a better understanding of the processes, the possibility of real-time process measurement and control, a smaller equipment footprint, lesser risk of contamination and human exposure, and higher processing rates [6].Te FDA has recognized these benefts and has been encouraging the adoption of continuous manufacturing [8,9].
Oral solid dosage (OSD) is the most common pharmaceutical product form [10]. Te manufacturing of OSD employs various unit operations such as feeding, blending, granulation, compaction, and coating [11].Blending is one of the essential unit operations as it ensures the homogeneous distribution of the active pharmaceutical ingredient (API), which has therapeutic value, in the blend of API and excipients [12].Te blended material must have a homogeneous distribution of API (one of the critical quality attributes) and good fow properties to aid the manufacturability in downstream processes.Almost all OSD manufacturing processes involve at least one blending step.
Ingredients can be blended to an acceptable level of homogeneity by utilizing either batch blending [13] or continuous blending [14].Te batch blenders, though easy to operate, sufer from limitations such as longer blending time, batch-to-batch variability, larger equipment, and fxed batch sizes [15].Batch blending also has signifcant scale-up challenges.For example, the material at the bottom of a large batch blender can get compacted and exhibit diferent bulk density and fow properties [14].Consequently, batch blending is not well suited for blending pharmaceutical excipients with high segregation potential [16].Te continuous mode of blending can solve most of these issues as less material is processed at a time and holding times which can lead to segregation are much reduced.Also, there is a higher fexibility concerning batch size and output, and it is not limited by the size of the blender [17][18][19].Many benefts of continuous blending have been reported in recent publications, such as more efcient processes with lower manufacturing costs and footprints, easier scale-up, and improved product quality [4][5][6]20].However, continuous blending also sufers from some limitations.Te residence time the material spends in the blender is short and depends on the RPM of the impeller and on the length of the blender, which acts as a design constraint.Te residence time may not be sufcient when blending many excipients and APIs in such a short time.Continuous blenders require feeders to feed all the necessary ingredients at a constant fow rate [16].Since the overall inlet mass fow rate equals the outlet mass fow rate, any variation in the fow rate of any ingredients can afect the blending performance of the continuous blenders [21].Materials with poor fow properties and feeders operating at low mass fow rates typically have higher variations [20].Tis is shown later in the results section.Formulations with low API drug concentration products and poor fow properties can be especially challenging [22].Continuous blending also demands frequent reflling of the feeders, which is also known to cause fow rate variations as the feeders do not operate in loss in weight mode during the refll operation [16].Lastly, it is crucial to identify whether or not the process has reached a steady state and whether it has a mechanism to discard the material not meeting the content uniformity specifcations until a steady state is reached.
Up to now, most of the research work on blending in pharmaceutical manufacturing has focused on batch blending and continuous blending.A lot of work has been performed on the batch blending aspects [23][24][25].Te amount of work on continuous blending has also increased in the last decade [26,27].Tese studies have focused on important process parameters to optimize blending unit operations and comparison of blending performance between two blending modes.However, not much has been performed on the semicontinuous mode of blending pharmaceutical ingredients and on directly comparing the semicontinuous mode with the two other modes.Even though continuous manufacturing has gained growing interest, the blending of pharmaceutical ingredients is still dominated by batch processes [28].Challenges such as feeding variability from the feeders, knowledge-intensive process development, and complexity involved in achieving a state of control have limited the wide implementation of continuous blending.
Te current study aims to overcome the limitations realized with batch blending and continuous blending of powders [20].Te downside of both modes can be addressed by adopting a novel approach of semicontinuous blending of powders [29].A series of small batches can be produced semicontinuously using an integrated feeder blender system.Previous studies have reported the implementation of batch blending [23-25, 30, 31] and continuous blending [15].Te implementation of continuous manufacturing has been slower than expected [32].Semicontinuous blending provides a promising alternative to batch blending and continuous blending, combining the advantages of both the existing blending modes.Te authors understand that this is the frst work describing the case study on semicontinuous blending mode and its proposed benefts.In this study, we conceptualize the relative advantages of implementing this new semicontinuous mode of powder blending, show a case study that describes the blending performance of a semicontinuous setup, and investigate the impact of diferent process parameters on the blending performance of an integrated feeder blender operating semicontinuously.Te blend properties, performance, and line rate results from semicontinuous blending are compared with batch blending and continuous blending results.Tis work will help in the implementation of this new approach to blending.Te semicontinuous blending mode could be particularly advantageous over batch blending, providing robust blending, easier operations and scale-up, lesser manual intervention, and faster blending times.Overall, the scope of this study includes the use of a binary blend system consisting of microcrystalline cellulose and acetaminophen to investigate the blend uniformity at the end of semicontinuous blending, compare the blend properties and blend homogeneity with the batch and continuous blending modes, and highlight the relative advantages of this new blending mode over the existing modes in pharmaceutical manufacturing.

Materials and Methods
2.1.Materials.Te materials used are acetaminophen (APAP) as the API and microcrystalline cellulose (MCC) as the excipient to investigate the binary blend system.APAP grade 0048 is purchased from Mallinckrodt, North Carolina, USA.Acetaminophen is sieved before usage to remove any agglomerates.Avicel microcrystalline cellulose (PH 102) is purchased from FMC Biopolymer, Pennsylvania, USA.Te blending uniformity of API is studied with the target API concentration set as 10% (w/w).

Semicontinuous Blending.
Te Xelum, integrated wet granulation line by Syntegon, is repurposed and used as a semicontinuous setup (Figure 1).Te integrated feeder blender setup of Xelum consists of K-Tron feeders, a conical blender, and an automated pneumatic valve.Te system can accommodate up to fve feeders at the top of the conical blender.Te equipment user interface has the provision for defning a set recipe to carry out multiple steps in sequence and can also be used to input the required process parameters and execute a design of experiments (DOE) with minimum manual intervention.Te current setup uses two QT20 K-Tron feeders, as the case study only employs two ingredients.Feeders charge a set weight of powder into the conical blender as required by the recipe by using as a target the diference between the initial and fnal weight as measured by the load cell on which they are kept.Since the amount of material delivered by the feeder for blending is not dependent on maintaining a set constant feeding rate via the built-in control strategy, the blend composition uniformity is not dependent on each input feeder maintaining its set rate.Te helix impeller inside the 10-litre conical blender is set to rotate slowly during the feeding stage.Once the feeding operation is completed, the blending phase begins, and the impeller rotation per minute is increased to the set point of each experiment.Te pneumatic valve at the bottom opens up upon blending completion, and the material is unloaded into a bag or transferred pneumatically to the next operation.Te next batch of materials then starts to be dispensed into the conical blender by using the same steps.Te impact of diferent process parameters on the blending performance is studied.Te critical process variables in semicontinuous blending are impeller rotation, blending time, and blender fll levels.Te impeller rotation is varied from 80 rotations per minute (RPM) to 160 RPM.Based on the screening experiments, the blending time is varied from 1 minute to 5 minutes and the blender fll level is varied from 30% to 70% of the blender operating volume.A full factorial design of experiment (DOE) is created to understand the impact of these variables on the blend uniformity.Important process parameters to optimize are blending time, impeller rotation per minute, and blender fll level.

Batch Blending and Continuous Blending.
Te batch blending is performed by using a 10-litre bin blender from Tote Systems.250 g of APAP and 2250 g of MCC are charged into the bin blenders.Te APAP is passed through the sieve so that there are no agglomerates.Te APAP layer is sandwiched between the MCC layers.Te blender is rotated for 25 minutes at 20 rotations per minute.After 25 minutes of rotation, the material is unloaded from the bottom of the blender.Continuous powder blending is a relatively recent phenomenon in which the material enters from one end of the continuous tubular blender and exits from the other end of the blender.Te mixing happens in both radial and axial directions.Important process parameters are material fow rate and impeller speed.Design parameters include the mixer design, impeller design weir angle, and mixer inclination.For continuous blending, a Gericke continuous blender is used.Te blender inlet is attached to two K-Tron feeders.One K-Tron feeder is used to add APAP at 1 kg/hr, and the other K-Tron feeder is used to charge the MCC at 9 kg/hr.Te total powder fow is 10 kg/hr, and the impeller rotation speed is 150 rotations per minute.Te impellers are oriented in the forward direction, and the weir is kept at an angle of 90 °.Te output from the continuous blender is collected in a bag.Samples weighing 1 g each are drawn from batch and continuous blenders to characterize the output blend.After completion of blending, the blend is spread on a rectangular tray and eight samples are collected from diferent locations using an appropriate scoop.Te batch and continuous blender process parameters were previously optimized as shown in the work by Yan-shu, Qinglin et al., and Kumar et al. at the Purdue pilot plant [3,33,34] for the same formulation.Te optimized parameters were then directly used here.

Sampling and Characterization.
Te bulk powder is characterized by using the GranuPack instrument, an automated and high-resolution tapped density measurement method.It precisely characterizes the densities and fow properties [35].Te height of the powder bed is measured automatically after every tap.Te tap number for our analysis is fxed at 500 taps.Bulk density, tap density, Hausner's ratio (HR), and Carr index (CI) are measured to understand the bulk properties [36].CI and HR values can explain the bulk fow properties, and the ingredients and the blended powder after every experiment are characterized.

Hausner′s ratio �
tap density bulk density Carr index � (tap density − bulk density) bulk density * 100. ( For blend uniformity analysis, eight samples, 1 g each, are drawn from every batch.After unloading from the blender, the blend is spread uniformly on a rectangular tray, and eight samples are randomly drawn from diferent locations in the tray.Tis ensured that the sampling was random and that every material had an equal chance of getting picked.After sampling, API concentration was measured in every sample by using an Ultraviolet-Visible (UV-Vis) spectrometer.A calibration curve is generated using diferent APAP concentrations.After sample Advances in Materials Science and Engineering preparation, UV absorbance is measured at a wavelength of 243 nm using the UV-visible spectrometer, and the APAP concentration in each sample is calculated.One gram of the sample is accurately weighed using a Mettler-Toledo precision balance with a sensitivity of four decimal places.Te sample is then dissolved in a 100 ml solution consisting of a 1 : 3 ratio of methanol to water.To ensure adequate dissolution of APAP, the sample is agitated within a 250 ml volumetric fask for 10 minutes at 250 revolutions per minute (RPM).Subsequently, 10 ml of the solution is extracted via pipette, fltered, and further diluted in a 200 ml methanol-water solution.From this diluted solution, 4 ml is carefully transferred to a cuvette.Te baseline absorbance of the methanol-water solution is subtracted, and the absorbance at 243 nm is measured by using a UV spectrometer to determine the concentration of APAP in various samples.Tis absorbance measurement is repeated three times, and the average is used.Te absorbance value is converted to APAP concentration by using the UV calibration curve shown in Figure 2. Relative standard deviation (RSD) is then calculated by using the individual APAP concentration values.
Relative standard deviation � standard deviation of the samples sample mean * 100. ( RSD values describe the blend uniformity of API in the fnal blends.Diferent experiments are then compared for blend uniformity and fow properties.Acceptance criteria for blend uniformity are set at RSD values of less than 5% and the individual API concentration values within ± 10% of the target concentration.

Results
Acetaminophen (APAP) is charged to the K-Tron feeder, and the feeder is operated at diferent fow rates.Te fow rate variations at the feeder are shown in Figure 3. First, the mass fow rate set point was kept at 1 kg/hour, and then the set point was changed to 4 kg/hour.Variations in the feed rate are considered acceptable if the actual values are in the range of ± 10% of the set point.At a 4 kg/hour fow rate, the process is within limits but at 1 kg/hr, the same blender shows higher variations.Te results of the fow rate show that the same feeder, when operating at diferent output rates, can exhibit more variation at fow rates close to lower limits.Tis variation can afect the blending performance in continuous blending mode [20].
Te characterization results of APAP and MCC are shown in Table 1.APAP, in particular, has very poor fow properties and is comparatively more challenging to handle.Te Carr index for APAP is 37.30, and for MCC is 20.47.Te CI range categorization is shown in Table 2 [36].Te APAP hence falls in the very poor to no fow category, and MCC falls in the passable fow category.
Ten, the impact of diferent process parameters on the blending performance is studied.Te critical process variables in semicontinuous blending are impeller rotation, blending time, and blender fll levels.Te impeller rotation is varied from 80 rotations per minute (RPM) to 160 RPM.Based on the screening experiments, the blending time is varied from 1 minute to 5 minutes, and the blender fll level is varied from 30% to 70% of the blender operating volume.A full factorial design of experiment (DOE) is created to understand the impact of these variables on the blend uniformity.Te experimental design is shown in Figure 4. Tree center points are also added.Te API concentration of each sample after every run is measured, and the RSD value for each run is calculated to understand the level of homogeneity.Te RSD   3. Te model ft is signifcant, with a R 2 value of 0.99.Te analysis of the DOE shows that out of the three process parameters, the rotation speed of the impeller is the most signifcant factor afecting the blending performance (Pareto chart in Figure 5).Te other signifcant factors are blending time and blender fll level, of which the blender fll level had the least impact on blend uniformity.Higher rotation speed and blending time resulted in better blending performance.Te feasible region where the RSD values are less than 5% (acceptance criteria) is shown in the contour plot (Figure 6).RSD results are plotted against the two most signifcant factors, impeller rotation speed and blending time.Te blue region in the top right corner of the contour plot shows the region where the RSD values are the least.Te fll level had the least efect on the blending performance, and the RSD plane at the lowest and highest fll levels is shown in Figure 7.At the highest fll level (70% of blender volume), the RSD values vary from 2.9 to 21.   from the batch and continuous blending have been reported previously.Te work of Jaspers et al. [15] shows that they achieved RSD values close to 4% by using the batch blender after 30 minutes of blending and 2% using the continuous blenders.Our research group has also worked with the batch blender from Tote Systems and the continuous blender from Gericke Systems.We performed the blending operations by using the optimized parameters in batch and continuous   Advances in Materials Science and Engineering modes.Te samples are collected and analyzed as performed for semicontinuous mode.Te RSD values are calculated in these two modes and are compared against the semicontinuous mode.One of the semicontinuous batches taken as part of verifcation experiments is used for the comparison.Te individual values of each of the eight samples for all three modes are shown in Figure 9. Te RSD values calculated for these modes are shown in Figure 9. Te RSD obtained for the batch blender is 4.01% and for the continuous blender is 1.94%.Tis is similar to what was obtained in previous studies [15,28].Te blend uniformity from the new semicontinuous mode at RSD 2.34% is better than that of the batch blender and comparable to the blend uniformity of the continuous blender.
Te bulk density, tap density, Carr index, and Hausner's ratio of blend generated via batch blending, continuous blending, and semicontinuous blending are compared in Table 4. Te bulk density of the output blend is least in the continuous blending mode, perhaps because the processing time inside the blender is the least in the continuous blender, and the material is not compacted by the weight of the rest of the material on top of the blender.However, the diference in results is not much and all three blending modes produced the output with similar bulk properties.Te bulk and fow properties are similar in all three cases; hence, either strategy can be adopted for blending materials without impacting the physical properties.
Samples from all experimental runs are characterized to understand the impact of change in the process parameters on the physical characteristics of the blend.Te CI values are shown in Table 3. Te DOE analysis shows that the model developed for CI values from the process parameters is signifcant, with R 2 values of 0.95.Te variation in CI values by varying the process variables is shown in the contour plot (Figure 10).Te blends with low RPM, low blending time, and low occupancy had better fow properties.Tis could be because the low RPM and blending time used in the study are sufcient to ensure that the ingredients are well distributed throughout the mixture for this formulation.Blending for a longer period at times can cause overmixing and lead to the formation of new agglomerates.Longer blending time and shear imparted by higher impeller speeds can also lead to particle size reduction due to attrition, impacting the fnal blend's characteristics.Such analysis could be important during optimization in scenarios where it is critical to have better fow properties.
Te material outputs from all three modes, batch blending, continuous blending, and semicontinuous blending, are compared next.Similar-sized blenders, available at the Purdue pilot plant, are used to perform the experiment and calculate the output from each blender system in kg/hour.Te important operations in all three modes are shown in Figure 11.In batch and semicontinuous modes, 2.5 kg of the material could be processed at a time.Te batch blending required 15 minutes for the following steps: (i) initial dispensing of material manually in the exact amount needed, (ii) passing the APAP through a mesh to remove any agglomerates, (iii) charging the excipient and API in layers inside the blender, and (iv) manually closing the blender and setting up the process parameters.Te blending time is 25 minutes, which was established in earlier studies [3,33].Te time needed to open the blender and unload the blend is 2 minutes.It took 42 minutes for the complete cycle, which corresponds to 3.57 kg/hr.In semicontinuous blending, the dispensing step only required flling up the feeders as the dispensing is automated by loss in weight feeders.Te blending time, as studied in the abovementioned case study, was 5 minutes.Te time to unload is 2 minutes.Te cycle time is 12 minutes for an output of 2.5 kg.We were able to perform fve such cycles in an hour, resulting in an overall line rate of 12.5 kg/hr.In the continuous blender, the Gericke continuous blender GCM 250 could deliver between 1 and 25 kg/hr output depending upon the input feed rate of the material and blender RPM.Te continuous blender is typically operated at a line rate of 10-12.5 kg/hr.Batch blending required the maximum human intervention.In this case, the output of the semicontinuous mode is better than that of the batch blender and is less than the maximum output of the continuous blender.

Discussion
Te results from the case study show that the integrated feeder blender setup used in a semicontinuous manner can produce blends with good homogeneity.Te material blended using the semicontinuous setup had a good homogeneity, and the validation experiments had a good repeatability.
Mixing phenomena in blenders can be categorized into three major mechanisms, convection, difusion, and shear.Most blenders involve some level of all the abovementioned mechanisms, but the dominant mechanism varies with the type of blender used [16].Te conical blender in the semicontinuous setup introduces convection by the action of impellers that move the powder inside the conical vessel, which helps achieve the desired homogeneity.Te blender ofers a stainless-steel conical bowl and a stirrer.Te material in this blender spends less time under shear when compared to a batch blender due to the short blending time requirement.Such vertical blenders have a smaller footprint and can provide adequate blending even with excipients having bulk property variations.Te vertical blender ofers some additional advantages as well.First, they could be operated at wide fll levels from 10% to 100% of operating volume.Second, the powder inside the blender is less susceptible to contamination and abrasion as the seal around the shaft is mounted on top of the blender.Lastly, the conical vessel and the seal are designed in such a way that they can withstand pressure and vacuum conditions [14].Tis helps in smooth unloading operations and downstream powder transfer.
Te signifcant benefts that can be realized/theorized by incorporating semicontinuous blending over batch blending are as follows: (1) Te blending time needed in semicontinuous blending, in general, is less than that required for batch blending.For example, in this case study, the (2) Batch blending requires extensive manual intervention, and there is a higher possibility of manual error as frequent material dispensing of the exact weight is needed per batch.Manual intervention is also needed during blender opening, material    Advances in Materials Science and Engineering charging, and following the process parameters accurately.In semicontinuous mode, the feeders can dispense the required quantity directly into the blender with little to no manual intervention.Tere is no risk of human error or potential material loss during dispensing and loading into the batch blender or following the process parameters.All the ingredients can be added simultaneously by diferent feeders.
(3) Unlike batch blending, the output of the semicontinuous blender can be used to feed either batch or continuous downstream operations.Te material can be unloaded for downstream batch operations and charged back to the next unit operation.For continuous downstream operations, the output can be planned so that it can regularly fll the hopper of the following continuous unit operation.(4) Mixing via a moving impeller during the addition of materials prevents stratifcation.(5) Te batch size can be varied in semicontinuous blending by varying the number of small batches combined for one batch.As shown in the case study, the blender fll level had the most negligible impact on the blending performance.Hence, the output of each small batch produced semicontinuously can also be varied by testing and changing the fll level inside the blender.(6) Te scale-up would be relatively easier in semicontinuous blending as it is not needed to go to a very large scale.Instead, the semicontinuous setup can be run for longer hours.(7) Te closed operation in semicontinuous mode reduces the chances of contamination and exposure to operators.(8) Lastly, the semicontinuous blender would require a smaller footprint.
Te benefts of semicontinuous blending over continuous blending are as follows: (1) Te blending time in semicontinuous blending can be easily varied for the given set of ingredients.In continuous blending, the amount of time the material stays in the blender is constrained by the length of the continuous blender.Te short blender length, however, can be compensated by the use of a weir at the end of the blender which can increase the residence time.Te change in impeller design that allows for back mixing can also increase the residence time for blending.In scenarios where many excipients and APIs must be blended in one go, longer blending Otherwise, the variation in the fow rate of any ingredients can afect the blending performance.Materials with poor fow properties can show more signifcant variations in fow rate.Loss in weight feeders operating at fow rates close to the upper or lower equipment operating limit can also show higher variation in mass fow rate.In semicontinuous blending, the feeders operate only as dosing devices and any fuctuation in the input fow rate does not afect the overall blending performance as feeding is terminated when the required mass has been delivered.(3) In continuous blending, it is crucial to have a more in-depth process understanding to identify the onset of the steady state and have a mechanism to evaluate the beginning of the steady state in real time and throw/divert the material produced before the steady state is reached.In semicontinuous blending, steadystate evaluation is not needed.However, semicontinuous blending will also beneft from real-time monitoring and analysis.PAT tools such as NIR and Raman spectrometers can be used to assess critical quality attributes in line for each small batch that is produced and divert only a small amount of material when a particular batch does not meet the specifcations without afecting adjacent small batches.(4) Te semicontinuous blender provides good fexibility regarding the number of ingredients to be added and blending time and hence would be more suitable for products with many ingredients and diferent material properties.Te setup would also be able to accommodate multiple products.Continuous blender also provides good fexibility and the possibility of using multiple feeders.However, while using these blenders in practice at the Purdue pilot plant, cleaning and product changeover operations for the semicontinuous blender were easier in our experience.Tese benefts over the existing blending modes make a compelling case to test the semicontinuous blending mode.
Te possible disadvantage of semicontinuous blending over continuous blending is that the former needs more human intervention while reflling the feeders and unloading the small batches.Automated reflling of feeders could overcome this disadvantage in installations on the production foor.Te semicontinuous blending would also utilize the real-time monitoring of API concentration, such as continuous blending, to ensure the blending performance in real time over several batches.Te case study with acetaminophen and microcrystalline cellulose provided promising results concerning the uniformity of API distribution and other process improvements.Many pharmaceutical processes have many ingredients that need to be blended in one step, and hence such a case study can be tested out next.An investigation of blend uniformity of API along with three to four excipients with diferent powder fow properties can be carried out to understand the methodology in such a scenario.

Conclusion
Te results from semicontinuous blending by using an integrated feeding blending process show good consistency.As conceptualized above, the possible benefts of incorporating semicontinuous blending make it a good alternative for blending in pharmaceutical manufacturing of oral solids alongside the current batch and continuous blending modes.Te important process parameters studied here are impeller RPM, blending time, and fll level inside the blender.Te impeller RPM has the most signifcant efect on blending performance.During semicontinuous blending at a 2.34% level, the observed RSD is considerably lower than the acceptable variation limit of 5%.Te fnal blend's bulk properties are similar to those achieved with the other two blending methods.Te blending performance could be further improved for this binary blend system.However, the scope of this work was to show the feasibility of the semicontinuous system and conceptualize its potential benefts.Semicontinuous blending mode has several advantages over batch blending mode, such as shorter blending time, smaller footprint, and others, as mentioned in the discussion section.It can produce homogeneous blends with good blend uniformity and requires lesser manual intervention.Tis study highlights the relative advantages of semicontinuous blending and would lead to more work in the direction of semicontinuous mode as the pharmaceutical industry is actively looking for better processes and alternatives to batch manufacturing.Te semicontinuous mode of blending provides one such alternative to the existing blending modes.

Figure 3 :
Figure 3: Variation in K-Tron KT20 feeder performance at two diferent set points.

Figure 4 :
Figure 4: DOE experiment design (center point and factorial points) with process parameters, impeller RPM, blending time, and fll level.

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Advances in Materials Science and Engineering blending time in batch blending was 25 minutes and in semicontinuous blending was 5 minutes.However, diferent formulations can have diferent blending times based on the ingredients and material properties.

Figure 9 :
Figure 9: API concentration variations and RSD variation comparison in batch blending, continuous blending, and semicontinuous blending.

Figure 10 :
Figure 10: Variation in CI values by changing the RPM (A) and blending time (B) in the design space.
3. At the lowest fll level (30% of blender volume), the RSD values vary from 2.9 to 19.2.Process variables from the feasible region are chosen (impeller RPM: 160, blending time: 5 mins, and fll level: 50%), and validation experiments are performed.Te results UV calibration curve for APAP concentration (μg/ml) measurement from absorbance values.

Table 1 :
Physical characterization of raw material.
51%, and 1.99%, respectively, are good.Te individual values are also in the ± 10% range of target API concentration.Te validation runs have shown good repeatability in terms of blending performance.Now, we compare blending output from batch, continuous, and semicontinuous modes of blending.Results

Table 3 :
DOE experiment parameters, RSD results, and CI results.

Table 4 :
Comparison of output blend from batch blending, continuous blending, and semicontinuous blending.
Standard deviation (SD) is mentioned in parenthesis.
In continuous blending, the fow rate of each of the input materials should be as constant as possible.