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Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and tableting
PHASCI-03483; No of Pages 9 European Journal of Pharmaceutical Sciences xxx (2016) xxx–xxx
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European Journal of Pharmaceutical Sciences journal homepage: www.elsevier.com/locate/ejps
Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and tableting Simo-Pekka Simonaho a, Jarkko Ketolainen a, Tuomas Ervasti a, Maunu Toiviainen b, Ossi Korhonen a,⁎ a b
University of Eastern Finland, School of Pharmacy, PROMIS-Centre, FI-70211 Kuopio, Finland VTT Technical Research Center of Finland, Photon Devices & Measurement Solutions, P.O. Box 1199, FI-70211 Kuopio, Finland
a r t i c l e
i n f o
Article history: Received 17 August 2015 Received in revised form 2 February 2016 Accepted 10 February 2016 Available online xxxx Keywords: Continuous manufacturing Feeding Blending Tableting
a b s t r a c t Drug manufacturing technology is in the midst of modernization and continuous manufacturing of drug products is especially the focus of great interest. The adoption of new manufacturing approaches requires extensive cooperation between industry, regulatory bodies, academics and equipment manufacturers. In this paper we introduce PROMIS-line which is a continuous tableting line built at the University of Eastern Finland, School of Pharmacy, PROMIS-centre. PROMIS-line is modular and tablets can be produced via dry granulation or direct compression. In three case studies, continuous feeding, blending and tablet performance is studied to illustrate some basic features of PROMIS-line. In conclusion, the PROMIS-line is an excellent tool for studying the fundamentals of continuous manufacturing of tablets. © 2016 Elsevier B.V. All rights reserved.
Introduction Traditionally drug manufacturing has been very conservative and even though highly dedicated products are manufactured old fashioned batch processing still dominates strongly. It has been said that a manufacturing operator from the beginning of the last century could easily recognize today's manufacturing equipment. Other mass production industries (petrochemical, food, mining, forestry, etc.) have implemented continuous manufacturing already decades ago and also Pharma industry has now started to seek the advantage of continuous manufacturing of drug products. Implementing continuous manufacturing as a common method will require cooperation between industry, regulatory, academic and equipment manufacturers. During the last decade International Conference on Harmonization (ICH) and FDA have launched a series of guidelines for drug manufacturing (ICH Guidelines Q7, Q8, and Q9 and FDA Guidance for Industry — PAT) which are intended to motivate manufacturers to enhance processes for better quality and apply continuous manufacturing to drugs. The main advantages of continuous manufacturing are: smaller footprint of manufacturing sites, no or limited scale-up, better process understanding with process analytic technologies (PAT), higher quality of products with the aid of PAT and faster production to market time (Leuenberger, 2001a; Plumb, 2005; McKenzie et al., 2006). Another advantage is that the same equipment can be used for the production of phases I–III clinical products (short runs) and final production ⁎ Corresponding author at: University of Eastern Finland, School of Pharmacy, FI-70211 Kuopio, Finland. E-mail address: ossi.korhonen@uef.fi (O. Korhonen).
(continuous run) [5]. This eliminates problems related to site and equipment change. All these advantages ultimately decrease production costs and increase the quality of pharmaceutical products (Spencer et al., 2011). Continuous manufacturing can be defined as a process where starting materials are manufactured into the final product as a constant flow with an integrated set of equipment, and equipment is controlled to produce required product quality. The scale of continuous production is defined by time rather than dimension of equipment as in batch production. Some pharmaceutical equipments operate inherently continuously, like tableting machines and roller compactors. Others, such as wet granulators and coaters, have to be modified for continuous production. A typical continuous tableting line consists of following unit operations (Byrn et al., 2015; Fonteyne et al., 2015). Weighting — continuous feeding of formulation components that is most often accomplished through the Loss-In-Weight (LIW) or Loss-In-Volume (LIV) feeders. Each feeder runs at a specified feed rate which is defined by formulation. Challenges for the feeding are cohesive materials and low feeding rates (b100 g/h). Next, formulation components are blended to form a homogeneous powder blend. Continuous blenders are typically tubular blenders which consist of a horizontal cylinder and a bladed shaft which rotates along its central axis. Powder is fed in one end and the impeller moves the powder to the other end of the cylinder and out of the blender. Ideal blending requires optimal amount of axial and radial movements of particles in the blender. In the case of direct compression formulation, powder blend is fed to tableting machine. However, often pharmaceutical blends require
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Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Table 1 Equipment in continuous tablet manufacturing line. Equipment
Brand and manufacturer
Specifications
3 Loss-In-Weight powder feeders Loss-In-Weight granule feeder Loss-In-Weight micro feeder Modified Loss-In-Weight feeder for lubricant and low dose API Two continuous blenders Roller compactor for dry granulation
K-Tron, K-ML-D5-KT20 K-Tron, K-CL-24-KT24 K-Tron, K-CL-SFS-MT12 K-Tron, K-CL-24-KT24 modified Hosokawa, Modulomix Hosokawa, Pharmapaktor L200/30P with flake crusher FC 200
Tableting machine Screw conveyer Vacuum conveyer Vacuum conveyer
PTK, PT-100 with PISCon Entecon Spiral Screw K-Tron, P10-BV-100-VE Volkmann, VS200 Eco
300 g/h–30 k/hND 300 g/h–30 kg/hND X–500 g/hND X–150 g/h 300–1250 rpm Screw speed: 0–10 rpm Roll speed: 0–20 rpm Roll pressure: 0–50 kN Flake crusher: 20–100 rpm 96 000 tabl/h Constant speed
granulation which can be performed with wet or dry granulation. Dry granulation (roller compaction) operates inherently continuously. Also wet granulation can be accomplished in continuous or semicontinuous mode with modern wet granulation equipment. Finally after tableting, tablets can be coated in a continuous coater. Powder transfer between unit operations can be performed with the aid of gravity or conveyers. In vertical configuration, pieces of equipment are placed on top of each other and powder is transferred between unit operations by gravity. This configuration requires a footprint of only a few square meters, but the height of the room has to be two to
three stories high. In horizontal configuration continuous line can fit in normal room height but conveyers (pneumatic or screw) are required to transfer powder between unit operations. Feeding and blending are among the most critical parts in the manufacturing process, affecting directly to the homogeneity of the powder mixture and thus on the uniformity of the end product. For this reason feeding accuracy/monitoring of feeding as well as ensuring proper blender settings are essential (Marikh, 2005; Pernenkil and Cooney, 2006; Portillo et al., 2008a, b, c; Engisch and Muzzio, 2012; Fonteyne, 2015).
Fig. 1. Three different operational configurations of PROMIS-line. Full configuration up (RC = roller compaction, *second blending can be skipped if not needed). Double blending/direct compression configuration in the middle. Direct compression configuration in the bottom.
Fig. 2. Schematic figure of full line configuration.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 3. Full line configuration.
To set up continuous line into operation, the primary task is to synchronize the yield of each piece of equipment in regard to balance of mass. If the line is not balanced adequately, material can start accumulating at a point of operation, or a unit of operation can run out of material if it functions at a faster rate than the previous unit. Thus, reliable mass flow meters are of great importance. Another important aspect is the understanding of process disturbances and how they are dampened or accumulated in subsequent unit operations. A key parameter for that is the residence–time distribution of each piece of equipment. Process monitoring and process controls are integral parts of continuous manufacturing. Different spectroscopic methods (mostly NearInfra-Red (NIR) and Raman) are among the most introduced PAT tools for process monitoring (Karande et al., 2010; Zhang, 2014). Also laser diffraction, image analysis and machine vision are used (Fonteyne, 2012). Preferably the PAT-tools run in-line. For process control, the first principle model-based controls are the most obvious choices, but also gray or black box models are used due to the lack of first principle models.
In this paper, we introduce PROMIS-line which is a research and development continuous tableting line constructed at the University of Eastern Finland, School of Pharmacy. PROMIS-line is a modular line which can be run in three different configurations. Next, equipment and configurations are described followed by three case studies performed with PROMIS-line. Description of PROMIS continuous tablet manufacturing line (PROMIS-line) With equipment presented in Table 1, different continuous set-ups can be flexibly configured: full line configuration, double blending/ direct compression configuration, and direct compression configuration (Fig. 1). The footprint of PROMIS-line in full configuration is 6 × 2.5 × 3.2 m (length × width × height); in direct compression configuration only 2 × 2 × 3.2 m (length × width × height). In full line configuration, up to four powder LIW feeders feed API and excipients to the continuous blender (Figs. 2 and 3). From continuous blender, screw
Fig. 4. Schematic figure of double blending/direct compression configuration.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 7. The mass flow value of MCC feeder as a function of time. The insert shows the mass flows during the first 8 min.
Fig. 5. Schematic figure of direct compression configuration.
conveyer transfers powder blend to the roller compactor. From roller compactor, vacuum conveyer transfers granules to the second feeding and blending station where granule LIW feeder and LIW microfeeder (for lubricant) feed the second continuous blender. This step can also be skipped if not needed. Finally, a vacuum conveyer transfers granules to the tableting machine. In-line PAT tools which have been implemented to the PROMIS-line at the moment are NIR measurement systems for blend homogeneity and image analysis systems for granule size measurements. In-line NIR probes have been placed to the output ports of continuous blenders to measure the blend homogeneity right after the
blending. There are two interface configurations available for NIR monitoring. The first one is powder flow chute where the powder flows over the sapphire window and NIR spectra are measured through the sapphire window. The second configuration is the so-called NIR-Sphere system which is an integrated sphere where powder flows through the tube which is placed in the sphere and NIR signals are collected from several angles with respect to tube. Advantage of NIR-Sphere is that it gives much better sampling of flowing powder than flow chute where only the bottom part of powder flow is measured. For granule size measurement after the roller compaction Innopharmalabs Eyecon™ system is used. ND : Real upper limit has not been tested. In double blending/direct compression configuration, line configuration is identical to full line configuration but roller compactor is excluded (Fig. 4). Powder blend from the first blending station is conveyed to the second blending station with either screw or vacuum conveyer.
Fig. 6. Snapshot of control and monitoring software (software created in-house based on Labview).
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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order than start-up. The amount of waste due to shut-down is 4–5 kg. Most of it is in the screw conveyer (2–3 kg) and the rest is in hoppers of roller compactor and tableting machine. The second demonstration of start-up and shut-down is direct compression configuration where feeders and blender are directly above the tableting machine and no conveyers are needed. Thus blender feeds tablet machine hopper. For smooth tableting 1–2 kg (depending of formulation) of powder is needed in feed frame of the tableting machine. With simple calculus of 20 kg/h production rate, this takes 3–6 min and the tablet machine can be started. In shut-down, all equipment is shut down simultaneously and the amount of waste is what remains in the feed frame. Process performance: case study I, powder feeders
Fig. 8. The mass flow value of ASA feeder as a function of time. The insert shows the mass flows during the first 8 min.
When intensive blending is required, two blenders can be coupled together. In direct compression mode, no conveying system is needed (Fig. 5). Powder feeders and blender are on the top of tablet machine and powder flows to the tablet machine by gravity. Optimum throughput in this continuous tableting line is 20 kg/h. Lowest tested throughput rate is 3.5 kg/h. Upper limit has not been tested but it is estimated that it might be 30–40 kg/h. Tableting machine is the rate limiting equipment (theoretical maximum 96 000 tabl/h) in the line. It should be noted that lower and upper limits of the line are dependent on formulation (cohesiveness and adhesiveness of powder/granule blend). Each piece of equipment of the line, except the tableting machine, is connected to the control-PC. With the aid of Labview control software (software created in-house), each piece of equipment can be controlled. The same software collects and stores the data from the equipment with time stamps. Data is also stored to Datain server (Kuava, Finland). Data can be illustrated in several graphs for monitoring purposes (Fig. 6). Start-up and shut-down of PROMIS-line Start-up time of the PROMIS line depends on selected configuration and the production rate. As a demonstration, full line configuration (second blending skipped) and a production rate of 20 kg/h are used. Start-up protocol goes as follows: 0 min starting feeders and blender, 0–12 min filling the screw conveyer, 15 min starting the roller compactor, 18 min starting the vacuum conveyer, 20 min starting the tableting machine and the first tablets out. When this set-up is in production, the amount of powder in the process is 6.6 kg. It should be noted that this mass hold-up is independent of the production rate. Start-up time is directly related to production rate, i.e. production rate defines how long it takes to feed 6.6 kg of powder. Most of the powder is in the screw conveyer (~ 2 kg) and hoppers of roller compactor (~ 2 kg) and tableting machine (~ 2 kg). Shut-down of this configuration goes in reverse Table 2 Feeder process parameters. Process parameters
Description
Set point [kg/h] Mass flow [kg/h] Net weight [kg] Pert [%] Drive command [%] Motor speed [%] Control [%]
Input value Measured mass flow The amount of powder in the feeder The signal/noise ratio in percentage to the set point Indicates the percentage from maximal feed rate Indicates how fast the motor runs Describes the feeder performance
As mentioned before, feeders play a very important role in continuous manufacturing; the steadier they are the more homogeneous is the output. The LIW feeders have a built-in control system that adjusts the mass flow based on the amount of material that has been fed. Usually the monitored parameter is the mass flow that is compared with the set point value. Once the mass flow equals the set point, the feeder is in steady state. Next, a simple case study in which two feeders are used is shown to illustrate the time to reach steady state. The used formulation was a binary mixture of microcrystalline cellulose (MCC) and acetylsalicylic acid (ASA) with the set point values of 17.14 kg/h and 2.86 kg/h respectively. In this test two LIW powder feeders (K-Tron, K-ML-D5-KT20) were used. The sampling rate was 1 s. Figs. 7 and 8 show the mass flow values acquired from the MCC and ASA feeders. At the beginning, the mass flow values deviate from the set point values but after 3 min they operate steadily. However, in the case of several feeders this traditional way is not as useful and multivariate methods offer much more robust tools to evaluate the steady state of the used feeders. Next, a model from the feeder process data is built using principal component analysis (PCA). Table 2 shows the process parameters and those that are included in the model (except Set Point which is a controlled input variable). SIMCA P + (Version 12.0.1.0, Umetrics AB, Sweden) was used in PCA. The total number of process parameters was 12 but the model was built up using eight parameters. The four excluded parameters were Pert, Drive command, Motor speed and control from the MCC feeder. These parameters were excluded based on their significance value which was lower than the threshold value. The size of X was 16 040 by 8. Each row corresponds to a certain time instant when the process parameter was measured. Thus, the time evolution of the process is visible in the PCA model. The model was built using the Autofit option of SIMCA and the R and Q values are shown in Table 3. From the score plot (Fig. 9) the time evolution of the feeders is clearly seen. When feeders started the scores move from top right to lower left corner and then up left and finally inside the circle. All this takes place during the first 3 min. The time instant when the scores are inside the circle is 2.5 min and the ASA mass flow at this time is 2.956 kg/h. This value is within specifications of label claim i.e. between 105% and 95%. In other words, when the scores are inside the circle feeders are operating in steady state. From Fig. 10 it is seen that parameters MassF1 and MassF2, i.e. the mass flow of MCC and ASA, are inversely correlated which seems to be a quite unexpected result. The reason for this finding can be seen from Figs. 7 and 8. When the feeders start, the ASA feeder overshoots while MCC feeder undershoots and this is the reason why these two parameters are inversely correlated. Based on the PCA model, the ASA feeder parameters are more important than the MCC feeder parameters. However, both feeders must operate in the steady state in order to have the desired binary mixture. In addition, the other feeder parameters than the mass flow could be used in the evaluation of the feeders especially if multivariate data analysis methods are used.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Table 3 Summary of PCA model. Var ID (primary) Total
Comp 1 Comp 2 Comp 3 Comp 4
R2VX
R2VX (cum)
Q2VX
Q2 limit
Q2VX (cum)
0,450652 0,258086 0,179142 0,0797069
0,450652 0,708738 0,887880 0,967587
0,262313 0,0577065 0,535382 0,611759
0,111186 0,125074 0,142929 0,166737
0,262313 0,304882 0,677036 0,874612
As a conclusion the performance of feeders defines the content of formulation and is thus the key unit operation in continuous manufacturing. Start-up of feeders caused an over- and/or undershoot which has to be taken into account when start-up procedure is defined. When steadystate has been achieved feed rates stayed very constant. Random spikes in feed rates are the most probable due to the accumulation and drop of powder in the output port of feeders. Multivariate analysis can be utilized to monitor and control complex processes. This case study illustrated simple feeding unit operation and how PCA model can be used to detect steady-state condition of feeders. Process performance: case study II, blender Continuous blending is a completely different concept than the traditional batch blending. In the batch blending all the material is inside the blender during the blending process. A continuous blender both blends and transports the material, thus there is a certain time or time distribution that describes how long blended material stays inside the blender. This time is called the residence time distribution (RTD). The performance of a blender can be analyzed using RTD and its operating conditions can be optimized using RTD (Gao et al., 2011; Portillo et al., 2008a; Portillo et al., 2008b), e.g. if there are fluctuations in feeding RTD that can be used to estimate how well a blender attenuates these fluctuations (Gao et al., 2011). A simple experimental test was made to evaluate the RTD of the used continuous blender. The test was made using a formulation that
had a paracetamol as API and its concentration was 5% of the total feed rate of 8.290 kg/h. The API concentration was monitored using NIR probe that was implemented in the blender outlet port. NIR equipment was the same with the one used in Kauppinen et al.'s (2013) work. The RTD was evaluated by adding an extra API shot in the inlet port of the blender and measuring API concentration after the blender. The amount of extra API was 10 g and it was applied manually by just pouring the whole amount once into the blender inlet port. Fig. 11 shows the measured API concentration as a function of time for three different blending speeds (500, 750, 1000 rpm). The response is normalized and zero indicates when the API shot was poured into the blender. From Fig. 11 it can be seen that the paracetamol concentration increases fast and within 20 s it starts to decrease. The concentration is back on the normal level after 60 s. Note that in Fig. 10 the normal level is between 0.1 and 0.3. The shape of the concentration change curve is almost like a parabola until 35 s when the amplitude stays constant about 10 s. After this shoulder there is a quite rapid decrease to the normal level. At 750 rpm, the shoulder is observed later at 500 rpm and 1000 rpm. The blending quality i.e. the homogeneity of the powder blend, is difficult to analyze using the RTD (Gao, 2011) but it has been reported that with a convective blender better blending occurs when RTD is narrow (Gao, 2011). The blending quality is discussed more detailed in the next section. However, RTD can be used in modeling of a blending and thus it can be used to find optimal blending settings (Gao et al., 2011; Portillo et al., 2008a; Portillo et al., 2008b).
Fig. 9. Score plot of the first two PC of X matrix.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 10. PCA p1/p2 loading plot corresponding the score plot.
Process performance: case study III, tableting The performance of the tablet press was tested with the same formulation as in the feeder test. The binary mixture of ASA and MCC was blended at 750 rpm and the blended powder was conveyed to the tablet press using a vacuum conveyor. The target values for the tablets were 350 mg and each tablet should have 50 mg ASA. Tablets were compressed using flat faced punches with the diameter of 10 mm. The turret speed was 60 rpm so the total production rate was 20 kg/h. In every rotation the average compression force and ejection force were measured and stored in the control center. At the beginning, the filling depth was adjusted which caused a drop in both the compression and ejection force curves as seen in Fig. 12. The tablets were compressed without a lubricant which is the reason for quite high ejection force. However, all the compressed tablets were intact i.e. no capping or lamination was observed. Tablet samples were collected every 20 min and their weight and ASA concentration were measured. The ASA concentration was measured using UV/VIS spectrophotometry (Thermo Spectronic Genesys 10 UV, Thermo Fischer Scientific Inc., Waltham, MA, USA, λ = 265 nm). Fig. 13a shows that the tablet weight was about 30 mg too high at the beginning but after adjusting the filling depth it was very close to the target value. In addition, it can be seen that the tablet weight fluctuates as a function of time. This fluctuation is sometimes called undulation (Lakio et al., 2010).
Fig. 11. Measured concentration change as a function of time.
One reason for this undulation is the difference in particle size (Lakio et al., 2010) and in the used formulation this is the case. ASA is needle shaped particles while MCC is fine powder. However, the amount of ASA in tablets is close to the target value thus indicating that the difference in particle size might cause variations in die filling. Interestingly, the tablet weight correlates with the amount of ASA and this indicates that the blender has blended these two ingredients well despite the particle size difference. At time instant 50 min, i.e. when the tablet weight is the closest to the target value, the ASA amount is also the closest to the target value. Finally, the content uniformity of dosage units was measured according to European Pharmacopeia. Ten tablets were first analyzed and the acceptance value was calculated. The calculations yielded the value of 12.6 for the acceptance value that is less than the criteria (L1 = 15). Thus, the content uniformity of the tablets is within specifications and it can be stated that the used continuous manufacturing line meets the target value and it is fit for purpose. Discussion and conclusions The introduced continuous manufacturing line can be built up with different configurations and thus it is very flexible. For example, the same equipment can be used in comparison between direct compressions with or without vacuum conveyor. Moreover, the flexibility makes it easy to implement on-line measurement systems to the line and test their performance in a real manufacturing environment. In addition, the sampling during continuous manufacturing can be tailored to fit the purpose because the equipment can be installed with a sufficient space between adjacent equipments. The results show that the continuous manufacturing line can be fit in a normal laboratory room and the top down configuration is not the only option for continuous manufacturing. This means that the footprint of continuous manufacturing is possible to minimize dramatically compared with the traditional batch processing. Process data is essential in continuous manufacturing. It can be used to monitor and evaluate the performance of the used manufacturing equipment. Moreover, the acquired process data analyzed using multivariate data analysis tools to model the whole manufacturing line and most importantly to gain valuable process understanding. In-line measurement systems or process analytic technologies (PAT) are equally important to monitor any process changes and to measure continuously the product itself. By combining the process data and PAT measurements, the real time release testing (RTRT) can be studied using the introduced manufacturing line. For example, different PAT systems like NIR and Raman can be implemented to measure concentration in
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 12. Average compression (a) and ejection (b) force as a function of time. The vertical lines indicate the tablet sampling time instants.
Fig. 13. Measured tablet weights (a) and ASA concentrations (b) as a function of time.
different locations before and after tableting and the measurement results from the different measurement locations are compared to find the most optimal measurement location. The introduced pilot scale line provides a flexible research platform for continuous manufacturing. It can be used to study formulations, PAT measurements system, process data modeling methods and process parameters.
Acknowledgments Construction of PROMIS centre is funded by the PROMIS Centre consortium (supported by the Finnish Funding Agency for Technology and Innovation (Tekes), Regional Council of Pohjois-Savo, North Savo Centre for Economic Development, Transport and the Environment)
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Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and tableting Simo-Pekka Simonaho a, Jarkko Ketolainen a, Tuomas Ervasti a, Maunu Toiviainen b, Ossi Korhonen a,⁎ a b
University of Eastern Finland, School of Pharmacy, PROMIS-Centre, FI-70211 Kuopio, Finland VTT Technical Research Center of Finland, Photon Devices & Measurement Solutions, P.O. Box 1199, FI-70211 Kuopio, Finland
a r t i c l e
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Article history: Received 17 August 2015 Received in revised form 2 February 2016 Accepted 10 February 2016 Available online xxxx Keywords: Continuous manufacturing Feeding Blending Tableting
a b s t r a c t Drug manufacturing technology is in the midst of modernization and continuous manufacturing of drug products is especially the focus of great interest. The adoption of new manufacturing approaches requires extensive cooperation between industry, regulatory bodies, academics and equipment manufacturers. In this paper we introduce PROMIS-line which is a continuous tableting line built at the University of Eastern Finland, School of Pharmacy, PROMIS-centre. PROMIS-line is modular and tablets can be produced via dry granulation or direct compression. In three case studies, continuous feeding, blending and tablet performance is studied to illustrate some basic features of PROMIS-line. In conclusion, the PROMIS-line is an excellent tool for studying the fundamentals of continuous manufacturing of tablets. © 2016 Elsevier B.V. All rights reserved.
Introduction Traditionally drug manufacturing has been very conservative and even though highly dedicated products are manufactured old fashioned batch processing still dominates strongly. It has been said that a manufacturing operator from the beginning of the last century could easily recognize today's manufacturing equipment. Other mass production industries (petrochemical, food, mining, forestry, etc.) have implemented continuous manufacturing already decades ago and also Pharma industry has now started to seek the advantage of continuous manufacturing of drug products. Implementing continuous manufacturing as a common method will require cooperation between industry, regulatory, academic and equipment manufacturers. During the last decade International Conference on Harmonization (ICH) and FDA have launched a series of guidelines for drug manufacturing (ICH Guidelines Q7, Q8, and Q9 and FDA Guidance for Industry — PAT) which are intended to motivate manufacturers to enhance processes for better quality and apply continuous manufacturing to drugs. The main advantages of continuous manufacturing are: smaller footprint of manufacturing sites, no or limited scale-up, better process understanding with process analytic technologies (PAT), higher quality of products with the aid of PAT and faster production to market time (Leuenberger, 2001a; Plumb, 2005; McKenzie et al., 2006). Another advantage is that the same equipment can be used for the production of phases I–III clinical products (short runs) and final production ⁎ Corresponding author at: University of Eastern Finland, School of Pharmacy, FI-70211 Kuopio, Finland. E-mail address: ossi.korhonen@uef.fi (O. Korhonen).
(continuous run) [5]. This eliminates problems related to site and equipment change. All these advantages ultimately decrease production costs and increase the quality of pharmaceutical products (Spencer et al., 2011). Continuous manufacturing can be defined as a process where starting materials are manufactured into the final product as a constant flow with an integrated set of equipment, and equipment is controlled to produce required product quality. The scale of continuous production is defined by time rather than dimension of equipment as in batch production. Some pharmaceutical equipments operate inherently continuously, like tableting machines and roller compactors. Others, such as wet granulators and coaters, have to be modified for continuous production. A typical continuous tableting line consists of following unit operations (Byrn et al., 2015; Fonteyne et al., 2015). Weighting — continuous feeding of formulation components that is most often accomplished through the Loss-In-Weight (LIW) or Loss-In-Volume (LIV) feeders. Each feeder runs at a specified feed rate which is defined by formulation. Challenges for the feeding are cohesive materials and low feeding rates (b100 g/h). Next, formulation components are blended to form a homogeneous powder blend. Continuous blenders are typically tubular blenders which consist of a horizontal cylinder and a bladed shaft which rotates along its central axis. Powder is fed in one end and the impeller moves the powder to the other end of the cylinder and out of the blender. Ideal blending requires optimal amount of axial and radial movements of particles in the blender. In the case of direct compression formulation, powder blend is fed to tableting machine. However, often pharmaceutical blends require
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Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Table 1 Equipment in continuous tablet manufacturing line. Equipment
Brand and manufacturer
Specifications
3 Loss-In-Weight powder feeders Loss-In-Weight granule feeder Loss-In-Weight micro feeder Modified Loss-In-Weight feeder for lubricant and low dose API Two continuous blenders Roller compactor for dry granulation
K-Tron, K-ML-D5-KT20 K-Tron, K-CL-24-KT24 K-Tron, K-CL-SFS-MT12 K-Tron, K-CL-24-KT24 modified Hosokawa, Modulomix Hosokawa, Pharmapaktor L200/30P with flake crusher FC 200
Tableting machine Screw conveyer Vacuum conveyer Vacuum conveyer
PTK, PT-100 with PISCon Entecon Spiral Screw K-Tron, P10-BV-100-VE Volkmann, VS200 Eco
300 g/h–30 k/hND 300 g/h–30 kg/hND X–500 g/hND X–150 g/h 300–1250 rpm Screw speed: 0–10 rpm Roll speed: 0–20 rpm Roll pressure: 0–50 kN Flake crusher: 20–100 rpm 96 000 tabl/h Constant speed
granulation which can be performed with wet or dry granulation. Dry granulation (roller compaction) operates inherently continuously. Also wet granulation can be accomplished in continuous or semicontinuous mode with modern wet granulation equipment. Finally after tableting, tablets can be coated in a continuous coater. Powder transfer between unit operations can be performed with the aid of gravity or conveyers. In vertical configuration, pieces of equipment are placed on top of each other and powder is transferred between unit operations by gravity. This configuration requires a footprint of only a few square meters, but the height of the room has to be two to
three stories high. In horizontal configuration continuous line can fit in normal room height but conveyers (pneumatic or screw) are required to transfer powder between unit operations. Feeding and blending are among the most critical parts in the manufacturing process, affecting directly to the homogeneity of the powder mixture and thus on the uniformity of the end product. For this reason feeding accuracy/monitoring of feeding as well as ensuring proper blender settings are essential (Marikh, 2005; Pernenkil and Cooney, 2006; Portillo et al., 2008a, b, c; Engisch and Muzzio, 2012; Fonteyne, 2015).
Fig. 1. Three different operational configurations of PROMIS-line. Full configuration up (RC = roller compaction, *second blending can be skipped if not needed). Double blending/direct compression configuration in the middle. Direct compression configuration in the bottom.
Fig. 2. Schematic figure of full line configuration.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 3. Full line configuration.
To set up continuous line into operation, the primary task is to synchronize the yield of each piece of equipment in regard to balance of mass. If the line is not balanced adequately, material can start accumulating at a point of operation, or a unit of operation can run out of material if it functions at a faster rate than the previous unit. Thus, reliable mass flow meters are of great importance. Another important aspect is the understanding of process disturbances and how they are dampened or accumulated in subsequent unit operations. A key parameter for that is the residence–time distribution of each piece of equipment. Process monitoring and process controls are integral parts of continuous manufacturing. Different spectroscopic methods (mostly NearInfra-Red (NIR) and Raman) are among the most introduced PAT tools for process monitoring (Karande et al., 2010; Zhang, 2014). Also laser diffraction, image analysis and machine vision are used (Fonteyne, 2012). Preferably the PAT-tools run in-line. For process control, the first principle model-based controls are the most obvious choices, but also gray or black box models are used due to the lack of first principle models.
In this paper, we introduce PROMIS-line which is a research and development continuous tableting line constructed at the University of Eastern Finland, School of Pharmacy. PROMIS-line is a modular line which can be run in three different configurations. Next, equipment and configurations are described followed by three case studies performed with PROMIS-line. Description of PROMIS continuous tablet manufacturing line (PROMIS-line) With equipment presented in Table 1, different continuous set-ups can be flexibly configured: full line configuration, double blending/ direct compression configuration, and direct compression configuration (Fig. 1). The footprint of PROMIS-line in full configuration is 6 × 2.5 × 3.2 m (length × width × height); in direct compression configuration only 2 × 2 × 3.2 m (length × width × height). In full line configuration, up to four powder LIW feeders feed API and excipients to the continuous blender (Figs. 2 and 3). From continuous blender, screw
Fig. 4. Schematic figure of double blending/direct compression configuration.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 7. The mass flow value of MCC feeder as a function of time. The insert shows the mass flows during the first 8 min.
Fig. 5. Schematic figure of direct compression configuration.
conveyer transfers powder blend to the roller compactor. From roller compactor, vacuum conveyer transfers granules to the second feeding and blending station where granule LIW feeder and LIW microfeeder (for lubricant) feed the second continuous blender. This step can also be skipped if not needed. Finally, a vacuum conveyer transfers granules to the tableting machine. In-line PAT tools which have been implemented to the PROMIS-line at the moment are NIR measurement systems for blend homogeneity and image analysis systems for granule size measurements. In-line NIR probes have been placed to the output ports of continuous blenders to measure the blend homogeneity right after the
blending. There are two interface configurations available for NIR monitoring. The first one is powder flow chute where the powder flows over the sapphire window and NIR spectra are measured through the sapphire window. The second configuration is the so-called NIR-Sphere system which is an integrated sphere where powder flows through the tube which is placed in the sphere and NIR signals are collected from several angles with respect to tube. Advantage of NIR-Sphere is that it gives much better sampling of flowing powder than flow chute where only the bottom part of powder flow is measured. For granule size measurement after the roller compaction Innopharmalabs Eyecon™ system is used. ND : Real upper limit has not been tested. In double blending/direct compression configuration, line configuration is identical to full line configuration but roller compactor is excluded (Fig. 4). Powder blend from the first blending station is conveyed to the second blending station with either screw or vacuum conveyer.
Fig. 6. Snapshot of control and monitoring software (software created in-house based on Labview).
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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order than start-up. The amount of waste due to shut-down is 4–5 kg. Most of it is in the screw conveyer (2–3 kg) and the rest is in hoppers of roller compactor and tableting machine. The second demonstration of start-up and shut-down is direct compression configuration where feeders and blender are directly above the tableting machine and no conveyers are needed. Thus blender feeds tablet machine hopper. For smooth tableting 1–2 kg (depending of formulation) of powder is needed in feed frame of the tableting machine. With simple calculus of 20 kg/h production rate, this takes 3–6 min and the tablet machine can be started. In shut-down, all equipment is shut down simultaneously and the amount of waste is what remains in the feed frame. Process performance: case study I, powder feeders
Fig. 8. The mass flow value of ASA feeder as a function of time. The insert shows the mass flows during the first 8 min.
When intensive blending is required, two blenders can be coupled together. In direct compression mode, no conveying system is needed (Fig. 5). Powder feeders and blender are on the top of tablet machine and powder flows to the tablet machine by gravity. Optimum throughput in this continuous tableting line is 20 kg/h. Lowest tested throughput rate is 3.5 kg/h. Upper limit has not been tested but it is estimated that it might be 30–40 kg/h. Tableting machine is the rate limiting equipment (theoretical maximum 96 000 tabl/h) in the line. It should be noted that lower and upper limits of the line are dependent on formulation (cohesiveness and adhesiveness of powder/granule blend). Each piece of equipment of the line, except the tableting machine, is connected to the control-PC. With the aid of Labview control software (software created in-house), each piece of equipment can be controlled. The same software collects and stores the data from the equipment with time stamps. Data is also stored to Datain server (Kuava, Finland). Data can be illustrated in several graphs for monitoring purposes (Fig. 6). Start-up and shut-down of PROMIS-line Start-up time of the PROMIS line depends on selected configuration and the production rate. As a demonstration, full line configuration (second blending skipped) and a production rate of 20 kg/h are used. Start-up protocol goes as follows: 0 min starting feeders and blender, 0–12 min filling the screw conveyer, 15 min starting the roller compactor, 18 min starting the vacuum conveyer, 20 min starting the tableting machine and the first tablets out. When this set-up is in production, the amount of powder in the process is 6.6 kg. It should be noted that this mass hold-up is independent of the production rate. Start-up time is directly related to production rate, i.e. production rate defines how long it takes to feed 6.6 kg of powder. Most of the powder is in the screw conveyer (~ 2 kg) and hoppers of roller compactor (~ 2 kg) and tableting machine (~ 2 kg). Shut-down of this configuration goes in reverse Table 2 Feeder process parameters. Process parameters
Description
Set point [kg/h] Mass flow [kg/h] Net weight [kg] Pert [%] Drive command [%] Motor speed [%] Control [%]
Input value Measured mass flow The amount of powder in the feeder The signal/noise ratio in percentage to the set point Indicates the percentage from maximal feed rate Indicates how fast the motor runs Describes the feeder performance
As mentioned before, feeders play a very important role in continuous manufacturing; the steadier they are the more homogeneous is the output. The LIW feeders have a built-in control system that adjusts the mass flow based on the amount of material that has been fed. Usually the monitored parameter is the mass flow that is compared with the set point value. Once the mass flow equals the set point, the feeder is in steady state. Next, a simple case study in which two feeders are used is shown to illustrate the time to reach steady state. The used formulation was a binary mixture of microcrystalline cellulose (MCC) and acetylsalicylic acid (ASA) with the set point values of 17.14 kg/h and 2.86 kg/h respectively. In this test two LIW powder feeders (K-Tron, K-ML-D5-KT20) were used. The sampling rate was 1 s. Figs. 7 and 8 show the mass flow values acquired from the MCC and ASA feeders. At the beginning, the mass flow values deviate from the set point values but after 3 min they operate steadily. However, in the case of several feeders this traditional way is not as useful and multivariate methods offer much more robust tools to evaluate the steady state of the used feeders. Next, a model from the feeder process data is built using principal component analysis (PCA). Table 2 shows the process parameters and those that are included in the model (except Set Point which is a controlled input variable). SIMCA P + (Version 12.0.1.0, Umetrics AB, Sweden) was used in PCA. The total number of process parameters was 12 but the model was built up using eight parameters. The four excluded parameters were Pert, Drive command, Motor speed and control from the MCC feeder. These parameters were excluded based on their significance value which was lower than the threshold value. The size of X was 16 040 by 8. Each row corresponds to a certain time instant when the process parameter was measured. Thus, the time evolution of the process is visible in the PCA model. The model was built using the Autofit option of SIMCA and the R and Q values are shown in Table 3. From the score plot (Fig. 9) the time evolution of the feeders is clearly seen. When feeders started the scores move from top right to lower left corner and then up left and finally inside the circle. All this takes place during the first 3 min. The time instant when the scores are inside the circle is 2.5 min and the ASA mass flow at this time is 2.956 kg/h. This value is within specifications of label claim i.e. between 105% and 95%. In other words, when the scores are inside the circle feeders are operating in steady state. From Fig. 10 it is seen that parameters MassF1 and MassF2, i.e. the mass flow of MCC and ASA, are inversely correlated which seems to be a quite unexpected result. The reason for this finding can be seen from Figs. 7 and 8. When the feeders start, the ASA feeder overshoots while MCC feeder undershoots and this is the reason why these two parameters are inversely correlated. Based on the PCA model, the ASA feeder parameters are more important than the MCC feeder parameters. However, both feeders must operate in the steady state in order to have the desired binary mixture. In addition, the other feeder parameters than the mass flow could be used in the evaluation of the feeders especially if multivariate data analysis methods are used.
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Table 3 Summary of PCA model. Var ID (primary) Total
Comp 1 Comp 2 Comp 3 Comp 4
R2VX
R2VX (cum)
Q2VX
Q2 limit
Q2VX (cum)
0,450652 0,258086 0,179142 0,0797069
0,450652 0,708738 0,887880 0,967587
0,262313 0,0577065 0,535382 0,611759
0,111186 0,125074 0,142929 0,166737
0,262313 0,304882 0,677036 0,874612
As a conclusion the performance of feeders defines the content of formulation and is thus the key unit operation in continuous manufacturing. Start-up of feeders caused an over- and/or undershoot which has to be taken into account when start-up procedure is defined. When steadystate has been achieved feed rates stayed very constant. Random spikes in feed rates are the most probable due to the accumulation and drop of powder in the output port of feeders. Multivariate analysis can be utilized to monitor and control complex processes. This case study illustrated simple feeding unit operation and how PCA model can be used to detect steady-state condition of feeders. Process performance: case study II, blender Continuous blending is a completely different concept than the traditional batch blending. In the batch blending all the material is inside the blender during the blending process. A continuous blender both blends and transports the material, thus there is a certain time or time distribution that describes how long blended material stays inside the blender. This time is called the residence time distribution (RTD). The performance of a blender can be analyzed using RTD and its operating conditions can be optimized using RTD (Gao et al., 2011; Portillo et al., 2008a; Portillo et al., 2008b), e.g. if there are fluctuations in feeding RTD that can be used to estimate how well a blender attenuates these fluctuations (Gao et al., 2011). A simple experimental test was made to evaluate the RTD of the used continuous blender. The test was made using a formulation that
had a paracetamol as API and its concentration was 5% of the total feed rate of 8.290 kg/h. The API concentration was monitored using NIR probe that was implemented in the blender outlet port. NIR equipment was the same with the one used in Kauppinen et al.'s (2013) work. The RTD was evaluated by adding an extra API shot in the inlet port of the blender and measuring API concentration after the blender. The amount of extra API was 10 g and it was applied manually by just pouring the whole amount once into the blender inlet port. Fig. 11 shows the measured API concentration as a function of time for three different blending speeds (500, 750, 1000 rpm). The response is normalized and zero indicates when the API shot was poured into the blender. From Fig. 11 it can be seen that the paracetamol concentration increases fast and within 20 s it starts to decrease. The concentration is back on the normal level after 60 s. Note that in Fig. 10 the normal level is between 0.1 and 0.3. The shape of the concentration change curve is almost like a parabola until 35 s when the amplitude stays constant about 10 s. After this shoulder there is a quite rapid decrease to the normal level. At 750 rpm, the shoulder is observed later at 500 rpm and 1000 rpm. The blending quality i.e. the homogeneity of the powder blend, is difficult to analyze using the RTD (Gao, 2011) but it has been reported that with a convective blender better blending occurs when RTD is narrow (Gao, 2011). The blending quality is discussed more detailed in the next section. However, RTD can be used in modeling of a blending and thus it can be used to find optimal blending settings (Gao et al., 2011; Portillo et al., 2008a; Portillo et al., 2008b).
Fig. 9. Score plot of the first two PC of X matrix.
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Fig. 10. PCA p1/p2 loading plot corresponding the score plot.
Process performance: case study III, tableting The performance of the tablet press was tested with the same formulation as in the feeder test. The binary mixture of ASA and MCC was blended at 750 rpm and the blended powder was conveyed to the tablet press using a vacuum conveyor. The target values for the tablets were 350 mg and each tablet should have 50 mg ASA. Tablets were compressed using flat faced punches with the diameter of 10 mm. The turret speed was 60 rpm so the total production rate was 20 kg/h. In every rotation the average compression force and ejection force were measured and stored in the control center. At the beginning, the filling depth was adjusted which caused a drop in both the compression and ejection force curves as seen in Fig. 12. The tablets were compressed without a lubricant which is the reason for quite high ejection force. However, all the compressed tablets were intact i.e. no capping or lamination was observed. Tablet samples were collected every 20 min and their weight and ASA concentration were measured. The ASA concentration was measured using UV/VIS spectrophotometry (Thermo Spectronic Genesys 10 UV, Thermo Fischer Scientific Inc., Waltham, MA, USA, λ = 265 nm). Fig. 13a shows that the tablet weight was about 30 mg too high at the beginning but after adjusting the filling depth it was very close to the target value. In addition, it can be seen that the tablet weight fluctuates as a function of time. This fluctuation is sometimes called undulation (Lakio et al., 2010).
Fig. 11. Measured concentration change as a function of time.
One reason for this undulation is the difference in particle size (Lakio et al., 2010) and in the used formulation this is the case. ASA is needle shaped particles while MCC is fine powder. However, the amount of ASA in tablets is close to the target value thus indicating that the difference in particle size might cause variations in die filling. Interestingly, the tablet weight correlates with the amount of ASA and this indicates that the blender has blended these two ingredients well despite the particle size difference. At time instant 50 min, i.e. when the tablet weight is the closest to the target value, the ASA amount is also the closest to the target value. Finally, the content uniformity of dosage units was measured according to European Pharmacopeia. Ten tablets were first analyzed and the acceptance value was calculated. The calculations yielded the value of 12.6 for the acceptance value that is less than the criteria (L1 = 15). Thus, the content uniformity of the tablets is within specifications and it can be stated that the used continuous manufacturing line meets the target value and it is fit for purpose. Discussion and conclusions The introduced continuous manufacturing line can be built up with different configurations and thus it is very flexible. For example, the same equipment can be used in comparison between direct compressions with or without vacuum conveyor. Moreover, the flexibility makes it easy to implement on-line measurement systems to the line and test their performance in a real manufacturing environment. In addition, the sampling during continuous manufacturing can be tailored to fit the purpose because the equipment can be installed with a sufficient space between adjacent equipments. The results show that the continuous manufacturing line can be fit in a normal laboratory room and the top down configuration is not the only option for continuous manufacturing. This means that the footprint of continuous manufacturing is possible to minimize dramatically compared with the traditional batch processing. Process data is essential in continuous manufacturing. It can be used to monitor and evaluate the performance of the used manufacturing equipment. Moreover, the acquired process data analyzed using multivariate data analysis tools to model the whole manufacturing line and most importantly to gain valuable process understanding. In-line measurement systems or process analytic technologies (PAT) are equally important to monitor any process changes and to measure continuously the product itself. By combining the process data and PAT measurements, the real time release testing (RTRT) can be studied using the introduced manufacturing line. For example, different PAT systems like NIR and Raman can be implemented to measure concentration in
Please cite this article as: Simonaho, S.-P., et al., Continuous manufacturing of tablets with PROMIS-line — Introduction and case studies from continuous feeding, blending and table..., European Journal of Pharmaceutical Sciences (2016), http://dx.doi.org/10.1016/j.ejps.2016.02.006
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Fig. 12. Average compression (a) and ejection (b) force as a function of time. The vertical lines indicate the tablet sampling time instants.
Fig. 13. Measured tablet weights (a) and ASA concentrations (b) as a function of time.
different locations before and after tableting and the measurement results from the different measurement locations are compared to find the most optimal measurement location. The introduced pilot scale line provides a flexible research platform for continuous manufacturing. It can be used to study formulations, PAT measurements system, process data modeling methods and process parameters.
Acknowledgments Construction of PROMIS centre is funded by the PROMIS Centre consortium (supported by the Finnish Funding Agency for Technology and Innovation (Tekes), Regional Council of Pohjois-Savo, North Savo Centre for Economic Development, Transport and the Environment)
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