Continuous Manufacturing of Pharmaceuticals E-Book
177,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Advances in Pharmaceutical Technology
- Sprache: Englisch
A comprehensive look at existing technologies and processes for continuous manufacturing of pharmaceuticals
As rising costs outpace new drug development, the pharmaceutical industry has come under intense pressure to improve the efficiency of its manufacturing processes. Continuous process manufacturing provides a proven solution. Among its many benefits are: minimized waste, energy consumption, and raw material use; the accelerated introduction of new drugs; the use of smaller production facilities with lower building and capital costs; the ability to monitor drug quality on a continuous basis; and enhanced process reliability and flexibility. Continuous Manufacturing of Pharmaceuticals prepares professionals to take advantage of that exciting new approach to improving drug manufacturing efficiency.
This book covers key aspects of the continuous manufacturing of pharmaceuticals. The first part provides an overview of key chemical engineering principles and the current regulatory environment. The second covers existing technologies for manufacturing both small-molecule-based products and protein/peptide products. The following section is devoted to process analytical tools for continuously operating manufacturing environments. The final two sections treat the integration of several individual parts of processing into fully operating continuous process systems and summarize state-of-art approaches for innovative new manufacturing principles.
- Brings together the essential know-how for anyone working in drug manufacturing, as well as chemical, food, and pharmaceutical scientists working on continuous processing
- Covers chemical engineering principles, regulatory aspects, primary and secondary manufacturing, process analytical technology and quality-by-design
- Contains contributions from researchers in leading pharmaceutical companies, the FDA, and academic institutions
- Offers an extremely well-informed look at the most promising future approaches to continuous manufacturing of innovative pharmaceutical products
Timely, comprehensive, and authoritative, Continuous Manufacturing of Pharmaceuticals is an important professional resource for researchers in industry and academe working in the fields of pharmaceuticals development and manufacturing.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 1171
Veröffentlichungsjahr: 2017
Ähnliche
Table of Contents
Cover
Title Page
Copyright
About the Editors
Peter Kleinebudde
Johannes Khinast
Jukka Rantanen
List of Contributors
Series Preface
Preface
Chapter 1: Continuous Manufacturing: Definitions and Engineering Principles
1.1 Introduction
1.2 Advantages of Continuous Manufacturing
1.3 Engineering Principles of Continuous Manufacturing
1.4 Conclusion
References
Chapter 2: Process Simulation and Control for Continuous Pharmaceutical Manufacturing of Solid Drug Products
2.1 Introduction
2.2 Pharmaceutical Solid Dosage Manufacturing Processes
2.3 Mathematical Modeling Approaches
2.4 Unit Operations Models
2.5 Process Control of Continuous Solid-based Drug Manufacturing
2.6 Summary
Acknowledgments
References
Chapter 3: Regulatory and Quality Considerations for Continuous Manufacturing
3.1 Introduction
3.2 Current Regulatory Environment
3.3 Existing Relevant Regulations, Guidelines, and Standards Supporting Continuous Manufacturing
3.4 Regulatory Considerations
3.5 Quality/GMP Considerations
3.6 Quality Considerations for Bridging Existing Batch Manufacturing to Continuous Manufacturing
3.7 Glossary and Definitions
3.8 General Regulatory References
Disclaimer
Note
Chapter 4: Continuous Manufacturing of Active Pharmaceutical Ingredients via Flow Technology
4.1 Introduction
4.2 Micro Flow Technology
4.3 Multi-step Synthesis of Active Pharmaceutical Ingredients in Micro Flow
4.4 Larger-scale Syntheses
4.5 Current Industrial Applications
4.6 Conclusion and Outlook
References
Chapter 5: Continuous Crystallisation
5.1 Introduction
5.2 Principles of Crystallisation
5.3 Crystallisation Process Development
5.4 Continuous Crystallisers and Applications
5.5 Process Monitoring, Analysis and Control
5.6 Particle Characterisation
5.7 Concluding Remarks
References
Chapter 6: Continuous Fermentation for Biopharmaceuticals?
6.1 Introduction
6.2 Operation of Fermentation Systems
6.3 Continuous Fermentation Examples
6.4 Discussion
6.5 Conclusions
References
Chapter 7: Integrated Continuous Manufacturing of Biopharmaceuticals
7.1 Background
7.2 Continuous Upstream Processing
7.3 Continuous Downstream Processing
7.5 Process Monitoring and Control
7.6 Process Economics of Continuous Manufacturing
7.7 Conclusions
Acknowledgments
References
Chapter 8: Twin-screw Granulation Process Development: Present Approaches, Understanding and Needs
8.1 Introduction
8.2 Continuous Wet-granulation using a TSG
8.3 Components of High Shear Wet Granulation in a TSG
8.4 Material Transport and Mixing in a TSG
8.5 Granule Size Evolution During Twin-screw Granulation
8.6 Model-based Analysis of Twin-screw Granulation
8.7 Towards Generic Twin-screw Granulation Knowledge
8.8 Strengths and Limitations of the Current Approaches in TSG Studies
8.9 Glossary
References
Chapter 9: Continuous Line Roller Compaction
9.1 Roller Compaction
9.2 Main Components of a Roller Compactor
9.3 Theory of Powder Densification in Roller Compaction
9.4 Johanson Model
9.5 Modified Johanson Model
9.6 Experimental Observations of Pressure Distribution from Instrumented Roller Compactors
9.7 Off-line Characterization of Ribbon Quality
9.8 In-line Monitoring of Roller Compaction Process
9.9 Formulative Aspects of Roller Compaction
9.10 Roller Compaction as a Unit Operation in Continuous Manufacturing
9.11 Process Control of Continuous Roller Compaction
9.12 Conclusions
References
Chapter 10: Continuous Melt Extrusion and Direct Pelletization
10.1 Introduction
10.2 The Extruder
10.3 Feeding
10.4 Twin-screw Extrusion
10.5 Operation Point
10.6 Downstream Processing
10.7 Continuous Manufacturing with HME
10.8 PAT for HME
10.9 Process Integration into Computerized Systems
10.10 Conclusion
References
Chapter 11: Continuous Processing in the Pharmaceutical Industry: Status and Perspective
11.1 Industry Drivers for Continuous Processing: Competitive Advantages
11.2 Continuous Manufacturing in Bioprocessing
11.3 Continuous Manufacturing for Oral Solid Dosage Forms
11.4 The Pharmaceutical Supply Chain of the Future
11.5 Conclusion
Acknowledgments
References
Chapter 12: Design of an Integrated Continuous Manufacturing System
12.1 Introduction
12.2 Step 1: Rough Conceptual Design
12.3 Step 2: Material Property Screening
12.4 Step 3: Characterizing Unit Operation Using Actual Process Materials
12.5 Step 4: Develop and Calibrate Unit Operation Models Including Process Materials
12.6 Step 5: Develop an Integrated Model of an Open Loop System
12.7 Step 6: Examine Open Loop Performance of the Process
12.8 Step 7: Develop/Fine Tune PAT Methods for Appropriate Unit Operations
12.9 Step 8: Implement Open Loop Kit with PAT and IPCs Enabled
12.10 Step 9: Design of the Control Architecture
12.11 Step 10: Develop Integrated Model of Closed Loop System
12.12 Step 11: Implementation and Verification of the Control Framework
12.13 Step 12: Characterize and Verify Closed Performance
12.14 Conclusions
References
Chapter 13: End to End Continuous Manufacturing: Integration of Unit Operations
13.1 Introduction
13.2 Process Description
13.3 System Dynamics
13.4 Process Monitoring and Control
13.5 Outlook: Opportunities for Novel Unit Operations and System Configurations
13.6 Summary and Closing Thoughts
References
Chapter 14: Methodology for Economic and Technical Comparison of Continuous and Batch Processes to Enhance Early Stage Decision-making
14.1 Introduction
14.2 Technical–Economic Evaluation Methodology
14.3 Conclusion
References
Chapter 15: Drivers for a Change – Manufacturing of Future Medicines for Personalized Drug Therapies
15.1 Introduction
15.2 Personalized Medicine
15.3 Flexible Dosing with Innovative Products
15.4 Future Health Care Scenario
References
Chapter 16: Perspectives of Printing Technologies in Continuous Drug Manufacturing
16.1 Introduction
16.2 Inkjet (Microdrop Generation Techniques)
16.3 Flexographic Printing
16.4 Formulation Approaches for Inkjet and Flexography
16.5 Process Control and Process Analytical Technology for Continuous Printing Applications
16.6 From Laboratory-scale Printing Towards an Industrial Scale
16.7 Three-dimensional Printing/Additive Manufacturing
References
Chapter 17: Development of Liquid Dispensing Technology for the Manufacture of Low Dose Drug Products
17.1 Introduction
17.2 Background
17.3 Goals for the LDT Program
17.4 Overview of LDT
17.5 LDT Machine Design Details
17.6 Scale-independence of the LDT Technology
17.7 Real-time Release Potential
17.8 Occupational Health, Environmental and Cleaning Considerations
17.9 Conclusion
Acknowledgments
References
Index
End User License Agreement
Pages
xvii
xviii
xix
xx
xxi
xxii
xxiii
xxv
xxvi
xxvii
xxviii
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
Guide
Cover
Table of Contents
Preface
Begin Reading
List of Illustrations
Chapter 1: Continuous Manufacturing: Definitions and Engineering Principles
Figure 1.1 General overview of a CM process chain.
Figure 1.2 Overview of continuous primary pharmaceutical manufacturing.
Figure 1.3 Overview of continuous secondary pharmaceutical manufacturing.
Figure 1.4 Schematic of a system with continuous phase contact.
Figure 1.5 The three principal flow modes.
Figure 1.6 Batch reactor and the associated temporal and spatial gradients.
Figure 1.7 Schematic of residence time distribution.
Figure 1.8 Schematic of a plug-flow reactor and temporal and spatial profile.
Figure 1.9 Schematic of a ideally mixed reactor (left). Corresponding temporal and spatial profiles (right).
Figure 1.10 Schematic of a cascade of CSTRs and spatial profile.
Figure 1.11 RTD for various numbers of CSTRs.
Figure 1.12 Schematic overview of typical sequence, from multivariate raw data (e.g., spectra, images) to product quality parameters (e.g., API concentration, coating thickness of pellets or tablets).
Figure 1.13 Model simulation of an extruder with filling ratio, temperature, pressure and RTD [29].
Chapter 2: Process Simulation and Control for Continuous Pharmaceutical Manufacturing of Solid Drug Products
Figure 2.1 Types of models used in the solid drug product manufacturing process.
Figure 2.2 The three major continuous solid dosage form manufacturing routes.
Figure 2.3 Side view of a discrete element model simulation of a hopper being emptied by an aperture down the bottom. The grids represent the discrete bins from which data can be collected. Each particle has its own velocity, represented using the gray gradient. (a) Hopper at time = 0. (b) Hopper at time = 2 s.
Figure 2.4 (a) Schematic of an RTD pulse experiment for an arbitrary unit operation. (b) Development of a model based on the results obtained from the pulse experiment. This step often requires a RTD literature review to match profiles.
Figure 2.5 Three different feeder types with their major components symbolized. The feeder hopper is represented inside the large top box, the flow aid system is inside the small central box, and the conveying system is shown inside the long bottom box.
Figure 2.6 Residence time distribution mixing model of a feeder. The model consist of an ideal no-mixing region, followed by a well-mixed region.
Figure 2.7 Feeder composition variability reduction due to blender effects. High frequency variations are smoothen after the blender, emphasizing the goal of blending: filter feeding noise from the feeders.
Figure 2.8 Discretization of a DEM simulation. The information collected in each of the bins can then be allocated to the population bins in a PBM.
Figure 2.9 Effects of blender process parameters on the residence time distribution. In the left, flow rate is varied, keeping blender blade speed constant. In the right, the flow rate is kept constant, while varying the blade speed. An increase in the breath of the distribution indicates the system has better mixing. Conversely, narrow distributions point to less mixing.
Figure 2.10 (a) Schematic of counter-rotating rolls in a compaction system. Note the exit roll width is that of the minimum nip width. (b) Schematic of the stress acting on a slab element undergoing compression between two rolls according to the slab method.
Figure 2.11 DEM-PBM coupled framework developed by Barraso and Ramachandran [115, 175].
Figure 2.12 Flowsheet models for a continuous direct compression system. The output from each unit operation model (represented as a schematic) is the input for the subsequent unit.
Figure 2.13 Direct compaction flowsheet model. A GUI will pop up by double clicking a unit model. This will help users to easily set the parameters for the unit model.
Figure 2.14 Simulation of the direct compression line modeled in Figure 2.13. For the case study of refilling the a feeder unit. (a) API feeder mass flow rate (kg/h). (b) Excipient feeder mass flow rate (kg/h). (c) Lubricant feeder mass flow rate (kg/h). (d) Concentration of API at the outlet of Comill. (e) Concentration of API at outlet of blender. (f) Concentration of API at inlet and at outlet of blender. Black and gray lines are inlet and outlet concentrations of API, respectively. (g) Material height inside transfer pipe (m). (h) Mass flow rate of feed frame (kg/h). Black represents inlet. Gray represents outlet. (i) Tablet weight (kg). (j) Tablet hardness (Pa).
Figure 2.15 Systematic methodology for design of control system (adapted from Singh
et al.
[42, 52]).
Figure 2.16 Closed-loop process flowsheet of direct compaction tablet manufacturing process. PSD: Particle size distribution; MPC: model predictive control; PID: proportional integral derivative; FFC: feedforward control; DRTO: dynamic real time optimization.
Figure 2.17 Model based performance evaluation of closed-loop continuous tablet manufacturing process.
Figure 2.18 Comparison of MPC with PID controller.
Chapter 4: Continuous Manufacturing of Active Pharmaceutical Ingredients via Flow Technology
Figure 4.1 Overview of commercially available micro flow reactors.
Figure 4.2 (a) Microreactor sequence for continuous synthesis of asymmetric di-substituted alkynes. (b) The structures and the yields of the di-substituted alkynes synthesized. Reproduced from Ref. [48] with permission of John Wiley & Sons.
Figure 4.3 Solvent-free intensified synthesis of rufinamide precursor in capillary reactor. Reproduced from Ref. [52] with permission of Wiley-VCH Verlag GmbH & Co. KGaA.
Figure 4.4 Intensified synthesis of 2,4,5-tri-substituted imidazoles. Reproduced from Ref. [53] with permission of the American Chemical Society.
Figure 4.5 Top: HP/HT microreactor with a single channel microreactor. Bottom left: HP/HT microreactor assembly: (1) and (3)compression parts, (2) cooling fluid pathway, (4) O-rings and grooves, (5) Pyrex plate for optical access, (6) single channel microreactor; Bottom right: Photograph of the final assembly. Reproduced from Ref. [56] with permission of the American Chemical Society.
Figure 4.6 Top: Experimental setup for electrically heated tubular flow reactor, along with temperature profile. Bottom: Conversion of methyl formate as a function of temperature for three different residence times. Reproduced from Ref. [57].
Figure 4.7 (a) Scheme of catalyzed hydroxylation of 2-hydroxybiphenyl to 3-phenylcatechol accompanied with NADH regeneration by formate dehydrogenase (FDH). (b) Schematic representation of a tube-in-tube reactor (TiTR) with an aqueous–organic two-liquid segmented flow within porous Teflon AF-2400 tubing and oxygen on the shell side. Reproduced from Ref. [77] with permission of the American Chemical Society.
Figure 4.8 Left: (a) Schematic exploded view of the reactor assembly used in photo-oxidation of citronellol with singlet oxygen; (b) Positioning of LED lamp array around the reactor. Right: Photographs of phase behavior at 55 °C for starting compounds at (a) 120 bar, (b) 140 bar, (c) 180 bar and (d) a biphasic mixture of scCO
2
and peroxide product. Reproduced from Ref [81] with permission of Wiley-VCH Verlag GmbH & Co. KGaA.
Figure 4.9 Micro-sieve tray based micro-distillation device to separate binary mixtures. Left: Compact view. Right: Exploded view. For a more detailed description of components please refer to the original reference. Reproduced from Ref. [84] with permission of Wiley-VCH Verlag GmbH & Co. KGaA.
Figure 4.10 Zig-zag micro-distillation device to separate binary mixtures. Left: Micro chip. Right: Close-up of the channel with incorporated micro-pillars. Reproduced from Ref. [85] with permission of the Royal Society of Chemistry.
Figure 4.11 Single-stage distillation device with integrated condenser and membrane-based vapor–liquid separator. Reproduced from Ref. [89] with permission of the Royal Society of Chemistry.
Figure 4.12 Multi-step synthesis of Imatinib with in-line scavengers and evaporation. Reproduced from Ref. [92] with permission of the Royal Society of Chemistry.
Figure 4.13 API process work flow along with analytical needs and typical equipment used to meet those needs. Reproduced from Ref. [97] with permission of the American Chemical Society.
Figure 4.14 Aspects to consider during the design of in-line analytical equipment for continuous flow processes.
Figure 4.15 Control loop scheme for a Grignard reaction monitored by NIR. Reproduced from Ref. [98] with permission of the American Chemical Society.
Figure 4.16 IR spectrum of the Paal–Knorr reaction components along with their characteristic peaks. Reproduced from Ref. [100] with permission of the American Chemical Society.
Figure 4.17 (a) Micro reactor used in oxidation of benzyl alcohol with a window for reaction-monitoring. (b) Raman microscope positioned on top of the micro reactor. Reproduced from Ref. [105] with permission of Elsevier B.V.
Figure 4.18 Top: UV-absorbance of thermal isomerization of endo-1 to exo-1. Bottom: Response surface showing the effect of temperature and residence time on the thermal isomerization of
endo
-1. Reproduced from Ref. [112] with permission of the American Chemical Society.
Figure 4.19 Left: Synthetic steps from intermediate 1 to aliskiren hemifumarate. Right: Process flow diagram including the major unit operations. R – reactor, S – separation, Cr – crystallization, W – filter/wash, D – dilution tank, E – extruder, MD – mold. Reproduced from Ref. [126] with permission of WILEY-VCH Verlag GmbH & Co. KGaA.
Figure 4.20 Synthetic pathway toward Artemisinin performed in continuous flow reactor. For a detailed description of the setup components, please refer to the original reference. Reproduced from Ref. [128] with permission of WILEY-VCH Verlag GmbH & Co. KGaA.
Figure 4.21 Multi-step synthesis of Ibuprofen. Reproduced from Ref. [130] with permission of Wiley-VCH Verlag GmbH & Co. KGaA.
Figure 4.22 Top: Reaction scheme for the synthesis of hydroxypyrrolotriazine. Bottom left: Laboratory-scale continuous setup. Bottom right: Pilot plant assembly on a portable rack. Reproduced from Ref. [137] with permission of the American Chemical Society.
Figure 4.23 Top: Reaction scheme for the synthesis of 6-hydroxybuspirone. Bottom left: Laboratory-scale continuous setup and bottom of the Quad oxidation reactor. Bottom right: Internal reaction tubes and extra-tubular baffles of the Quad trickle-bed reactor. Reproduced from Ref. [143] with permission of the American Chemical Society.
Chapter 5: Continuous Crystallisation
Figure 5.1 Examples of different platforms for continuous crystallisation of pharmaceutical compounds. (a) Continuous oscillatory flow reactor. Reprinted with permission from: [16], (b) MSMPR cascade. Reprinted with permission from: [33], (c) A seeded segmented tubular flow reactor. Reprinted with permission from: [28], (d) Kenics static mixer with multiple anti-solvent addition. Reprinted with permission from: [27] and (e) Tubular crystalliser with contact secondary nucleation device. Reprinted with permission from: [34]. Copyright American Chemical Society.
Figure 5.2 (a) General form of phase diagram for solution crystallisation. (b) Cooling process trajectory through phase diagram.
Figure 5.3 A schematic illustration of: (1) Classical nucleation with growth of clusters until a thermodynamically stable critical nucleus is formed. (2) The two-step nucleation process where the formation of stable crystal nuclei from disordered liquid clusters. Once critical nuclei are formed, growth will occur until a detectable crystal is achieved. Reprinted with permission from [67]. Copyright 2015 N.E.B. Briggs.
Figure 5.4 Schematic illustrating the principal mechanisms of secondary nucleation. Reprinted with permission from [67]. Copyright 2015 N.E.B. Briggs.
Figure 5.5 Schematic highlighting key stages in a crystallisation process development workflow.
Figure 5.6 Temperature-dependent solubility measurement in the presence of excess solid material using an ATR-UV method.
Figure 5.7 Images of crystal growth using a flow cell.
Figure 5.8 A comparison of MSZW data obtained in crystallisation parameters with different hydrodynamic environments.
Figure 5.9 Schematic of MSMPR crystalliser and typical residence time distribution response.
Figure 5.10 Mean particle size evolution of calcium lactate with residence time. Reprinted with permission from [88]. Copyright 1999 American Chemical Society.
Figure 5.11 Comparison between chord length distributions from FBRM for fedbatch, reverse addition, plug flow and MSMPR crystallisations. Reprinted with permission from [23]. Copyright 2013 Elsevier.
Figure 5.12 Schematic of MSMPR with recycle and integrated membrane. Reprinted with permission from [89]. Copyright 2014 American Chemical Society.
Figure 5.13 SEM photographs of NaHCO
3
crystals with magnification ×30 for various experiments with and without calcium based additives. Reprinted with permission from [90]. Copyright 2014 Elsevier.
Figure 5.14 Schematic of MSMPR with wet mill as part of a loop or upstream. Reprinted with permission from [92]. Copyright 2015 American Chemical Society.
Figure 5.15 Comparison of steady state product from setup: (a) without and (b) with wet milling loop. Reprinted with permission from [92]. Copyright 2015 American Chemical Society.
Figure 5.16 Steady state transition from β to α polymorph in seeded 25 °C MSMPR (120 min residence time): (a) polymorph mass density profiles and (b) optical images of the collected crystal samples. Reprinted with permission from [95]. Copyright 2014 American Chemical Society.
Figure 5.17 Effect of mean residence time on the crystal size distribution. Reprinted with permission from [29]. Copyright 2011 Elsevier.
Figure 5.18 Schematic of MSMPR with recycle and evaporation separator. Reprinted with permission from [31]. Copyright 2012 American Chemical Society.
Figure 5.19 Schematic of MSMPR cascade and typical residence time distribution response.
Figure 5.20 Attainable range of weight mean size and the corresponding range of coefficient of variation for the two-stage MSMPR cascade. Reprinted with permission from [101]. Copyright 2015 Elsevier.
Figure 5.21 SEM images of agglomerates ranging from (a) irregular shaped to (b) uniform spheres. Reprinted with permission from [102]. Copyright 2015 American Chemical Society.
Figure 5.22 Overlapping contour plots of yield and α polymorph purity to identify the operational window. Reprinted with permission from [21]. Copyright 2015 American Chemical Society.
Figure 5.23 Schematic of an MSMPR cascade for preferential chiral crystallisation. Reprinted with permission from [103]. Copyright 2015 American Chemical Society.
Figure 5.24 Representation of plug flow in comparison to laminar and turbulent flow. Residence time distribution response for true plug flow and typical plug flow response.
Figure 5.25 SEM images of dried lipoic acid–nicotinamide co-crystals from continuous.
Figure 5.26 Measurements of solute concentration, C, and particle size, L, for extended operation. Reprinted with permission from [105]. Copyright 2015 Elsevier.
Figure 5.27 Schematic diagram of the Roughton mixer plug flow crystalliser setup. Reprinted with permission from [106]. Copyright 2012 Elsevier.
Figure 5.28 Schematic process flow diagram of the kenics continuous crystallisation system with multistage anti-solvent addition. Reprinted with permission from [27]. Copyright 2010 American Chemical Society.
Figure 5.29 Crystal size (volume based) for L-glutamic acid as a function of the number of points of addition of anti-solvent. Reprinted with permission from [27]. Copyright 2010 American Chemical Society.
Figure 5.30 COBC setup for seeded crystallisations. Reprinted with permission from [107]. Copyright 2015 American Chemical Society.
Figure 5.31 (a) Schematic of the plug flow setup with ultrasound for
in situ
seed generation and (b) y-mixer where solution and air are mixed to generate segmented flow. Reprinted with permission from [28]. Copyright 2012 American Chemical Society.
Figure 5.32 Schematic of multi-orifice oscillatory baffled crystalliser with ultrasound. Reprinted with permission from [83]. Copyright 2015 American Chemical Society.
Figure 5.33 Particle size distribution and average particle size range produced by different crystallisation methods. Top: particle size distribution of the product. Bottom: average particle size ranges, D(v,0.5) attained with the given method. Reprinted with permission from [109]. Copyright 2015 Elsevier.
Figure 5.34 Overlay of a series of mid-ATR-FTIR spectra for a fixed concentration solute-solvent system highlighting the effect of variable temperature across a wide spectral range.
Figure 5.35 A full calibration data set for a given solute-solvent system. Five variable temperature experiments in the selected spectral range can be observed.
Figure 5.36 Schematic representation of the model-free control approaches for supersaturation control. Set points can be adjusted to maintain supersaturation at the required value in response to transients or fluctuations in the process. Reprinted with permission from [173]. Copyright 2013 Elsevier.
Figure 5.37 Results for the dynamic seed addition for bimodal and trapezoidal distributions (a) and (c) show the comparisons of target and simulated CSDs at the end of the batch, and (b) and (d) illustrate the dynamic seed addition profiles, with amount of seed in wt%. Reprinted with permission from [174]. Copyright 2012 Elsevier.
Chapter 6: Continuous Fermentation for Biopharmaceuticals?
Figure 6.1 Typical fermentation train of biopharmaceuticals from seed to industrial production.
Figure 6.2 Schematic overview of a batch fermentation, where there are no medium flows entering or leaving the reactor.
Figure 6.3 Schematic overview of a fed-batch fermentation, where there is a feed entering the reactor, but no flow leaving the reactor.
Figure 6.4 Schematic overview of a continuous fermentation, where there is a feed entering the reactor, and a flow leaving the reactor.
Figure 6.5 Interdependency between fermentation parameters, highlighting the challenge of fermentation modeling and control. DO in the center is a typical control variable; gray shading indicates typical manipulated variables.
Figure 6.6 Plant-wide control structure.
Figure 6.7 Schematic representation of a continuous ethanol fermentation process with yeast recirculation.
Figure 6.8 Schematic diagram of a U loop reactor.
Figure 6.9 Annual global production of fermentation products referenced in this work. [49, 50].
Figure 6.10 Considerations for development of a continuous process for biopharmaceutical production. In bold are the key terms we believe limit the application of continuous processes for production of biopharmaceuticals.
Chapter 7: Integrated Continuous Manufacturing of Biopharmaceuticals
Figure 7.1 Comparison of a hypothetical process for manufacturing of a biopharmaceutical with a conventional process (top) and a seamless process (bottom). The seed bioreactors are not shown.
Figure 7.2 Comparison of a batch and a continuous refolding process using matrix assisted refolding. In the continuous operation the system is started and then run continuously, while in the batch system the reactor must be filled, operated and cleaned in a cyclic manner. During filling and CIP the reactor is “idle” because it does not generate product. Details are described by Wellhoefer
et al
. [85].
Figure 7.3 The ATF system of Repligen integrates a diaphragm pump, a stainless steel housing and a single-use hollow fiber filter cartridge. The operation is as follows: (1) Pressurized air flows into the bottom of the ATF pump. (2) The air pressure forces the diaphragm gently up, displacing liquid and creating a fast flow of cell culture media across the surface of the hollow fiber filter. (3) Media flows rapidly through the filter fibers, with a cell-free filtrate being generated. (4) The cell culture fluid remaining on the upstream side of the hollow fiber filter is returned back into the bioreactor. (5) The system then reverses: air is exhausted through the pump bottom. (6) The diaphragm moves down creating a rapid flow of cell culture media from the bioreactor back into the ATF system. The system is now ready for the next cycle. Reproduced with kind permission of Repligen.
Figure 7.4 Process integration: classification of continuous unit operations in terms of in- and outflow. Every batch operation can be rendered continuous using a surge tank (a, b) with a volume ≥ the inflow volume of one batch cycle. (c) A fully continuous unit operation accepting a continuous inflow and producing a continuous outflow.
Figure 7.5 Principle of pre-coat filtration and body field filtration.
Figure 7.6 Pseudo continuous removal of flocs after calcium phosphate flocculation of pre-clarified culture supernatant with a laboratory-scale depth filter.
Figure 7.7 Categories of membrane filtration processes from batch-wise operation to fully continuous. Reproduced from Jungbauer 2013 [36], with kind permission of Elsevier.
Figure 7.8 Visualization of rapid mixing of 45 w/v% PEG 6000 with aqueous buffer in a tubular reactor equipped with helical type static mixers. The viscosity was 12 mPa at room temperature.
Figure 7.9 Precipitation of IgM in a stirred tank reactor with PEG, where the size of the precipitate was monitored with a Malvern Zeta Sizer [82].
Figure 7.10 Flow diagram of a fully continuous precipitation using PEG. Step A: precipitation of impurities at low pH by addition of citric acid and low concentrations of PEG. Step B: pH adjustment and further addition of precipitant. Step C: Harvesting of precipitate and concentration thereof. Step D: Washing of precipitate by addition of PEG containing wash buffer. Step E: Resolubilization. Adapted from Hammerschmidt
et al
. [30].
Figure 7.11 Different modes for diafiltration: (a) continuous diafiltration, (b) continuous concurrent diafiltration, (c) continuous counter-current diafiltration. Reproduced from Jungbauer 2013 [36], with kind permission of Elsevier.
Figure 7.12 3D-view of the ball room concept for a manufacturing plant of the future. From Klutz
et al
., 2015 [39], reproduced with kind permission of Elsevier.
Figure 7.13 Dynamic control for switch of columns in periodic counter-current control from Warikoo
et al
. [83] Reproduced with kind permission of John Wiley & Son, Inc.
Chapter 8: Twin-screw Granulation Process Development: Present Approaches, Understanding and Needs
Figure 8.1 Three main units of the continuous manufacturing line, ConsiGma™ by GEA Pharma Systems (Collette™, Wommelgem, Belgium). The continuous twin-screw granulation system contains (a) powder feeder, (b) liquid addition system, (c) twin-screw granulator and (d) wet granules transfer line (Courtesy of GEA Pharma Systems).
Figure 8.2 Screw configuration with 12 kneading discs (two mixing blocks, each containing six kneading discs) indicating the geometry of the screws used in a TSG [11].
Figure 8.3 The feed segment (a), work segment (b) and discharge segment (c) of a TSG during operation.
Figure 8.4 Due to non-ideal plug flow transport in the twin-screw granulator, the material spends different times, leading to a residence time distribution.
Figure 8.5 Mean residence time and standard deviation based on the experimental RTD profile at various material throughputs (10–25 kg/h), number of kneading discs (2, 6, 12), stagger angle (30–90°) and different screw speeds (500–900 rpm) [8].
Figure 8.6 Radial and axial mixing as a function of the material feeding characteristics and the RTD in a TSG.
Figure 8.7 The residence time distribution (left) and normalised residence time distribution (right) profiles with a shaded region denoting the standard deviation at different screw speed (500, 700 and 900 rpm) at material throughput of 10 kg/h during various experiments (ID) using twin-screw granulation [SA: stagger angle (), NK: number of kneading discs (−)].
Figure 8.8 A moisture map was used to calculate the mixing index; and the frequency and amplitude of the corresponding mean temporal profile was used to track dynamics of moisture content at different process conditions.
Figure 8.9 Changes in the GSD based on the Feret diameter of the granules (see [27]) at different sampling locations along the screw length: 1, before first kneading block; 2, on the first kneading block; 3, between first and second kneading block; 4, on the second kneading block; 5, after the second kneading block; 6, outlet of the granulator. A screw configuration with 12 kneading discs (two blocks) was used in the twin screw granulator and resulted in three different GSD for sample locations 1, 3 and 5.
Figure 8.10 Scatter plot with PLS loadings of the two first model dimensions [23].
Figure 8.11 Schematic diagram of three conceptual models based on non-ideal flow for the RTD in a TSG with a series of continuously stirred tank reactors: (a) without a plug-flow volume fraction, (b) with a plug-flow volume fraction and (c) with plug-flow volume fraction and dead zones [11].
Figure 8.12 Experimental (•) and simulated (—) trends for dynamic change in quartiles of the GSD (, and ) at low [(a) and (b)] and high [(c) and (d)] screw speeds for the first [(a) and (c)] and second [(b) and (d)] mixing zones [10].
Figure 8.13 Granule growth regime map for twin screw granulation by Dhenge et al. [4].
Figure 8.14 Steps required to develop a generalised granulation regime map for twin-screw granulation [45].
Figure 8.15 Visualisation of granulation mixing of liquid and powder during wet granulation using particle scale simulation of the mixing zone of the TSG [49].
Chapter 9: Continuous Line Roller Compaction
Figure 9.1 Principles of roller compaction.
Figure 9.2 Horizontal (a), inclined (b), and vertical (c) roll configurations.
Figure 9.3 Slip, nip, and release regions.
Figure 9.4 Schematic illustration to the determination of nip angle.
Figure 9.5 Three-dimensional velocity distribution during ribbon formation [12].
Figure 9.6 Force/pressure sensors installed at the surface of roll.
Figure 9.7 Schematic illustration of roll pressure as a function of roll angle. Sensor location A represents pressure sensor at the edge of the roll, location B sensor between edge and center and location C sensor at the centerline of the roll.
Figure 9.8 Schematic illustration of shear stress as a function of roll angle.
Figure 9.9 Average relative density of ribbon as a function of ribbon width measured by sectioning, micro-indentation, and X-ray micro-computed tomography [13].
Figure 9.10 Sinusoidal density variation in sodium chloride ribbon [14].
Figure 9.11 Relative density distribution during ribbon formation, three-dimensional FEM model [12].
Figure 9.12 (a) Line projection of porosity variation across sample width [horizontal solid line in plot (b)]. (b) Intensity images of porosity. Measured bulk porosities were 26.35, 36.56, and 50.27%, from left to right [15].
Figure 9.13 NIR-CI images to monitor chemical and physical information from the ribbon. First principal component contains porosity information (a) and (b). Second principal component: ASA content (c) and (d). Third principal component: MCC content (e) and (f) [16].
Figure 9.14 Continuous production line in the University of Eastern Finland, School of Pharmacy [20].
Chapter 10: Continuous Melt Extrusion and Direct Pelletization
Figure 10.1 Classification of screw extruders (according to [2]).
Figure 10.2 Plastification unit: I – feeding; II – solid conveying; III – start of melting; IV – melting; V – metering; VI – mixing.
Figure 10.3 Plastification with wall adhering melt. Picture courtesy of Montanuniversitaet Leoben, Polymer Processing.
Figure 10.4 LIW feeder with feed rate control based on weight detection.
Figure 10.5 Schematic illustration of bridge around the agitator.
Figure 10.6 Volumetric feeding experiments using calcium stearate (Lohmann) with different agitators. Left: 80% of nominal screw speed; right: 20% of nominal screw speed. Agitator “Type 1” shows stable bridging in the hopper. Agitator “Type 2” provides material flow in the hopper with little fill level influence on feed rate. Agitator “Type 3” shows the build-up of an unstable bridge at the beginning and a strong fill level dependence of feed rate.
Figure 10.7 Relationship between dispersive and distributive mixing.
Figure 10.8 Intermeshing counter-rotating twin-screw extruder (according to Hensen
et al
. [12]).
Figure 10.9 Velocity and shear rate profile in a counter-rotating twin-screw extruder (according to Hensen
et al
. [12]).
Figure 10.10 Partial flows depending on the movement rate of a three-flighted (left) and two-flighted (right) screw (according to Hensen
et al
. [12]).
Figure 10.11 Relationships in the screw gap of a co-rotating twin-screw extruder (according to Hensen
et al
. [12]).
Figure 10.12 Various screw elements.
Figure 10.13 Influence of the offset angle on the processing behavior of kneading blocks.
Figure 10.14 Different operation points depending on the process parameters. Picture courtesy of Montanuniversitaet Leoben, Polymer Processing.
Figure 10.15 Operation area of a conventional single-screw extruder. Picture courtesy of Montanuniversitaet Leoben, Polymer Processing.
Figure 10.16 Overview of possible downstream processes.
Figure 10.17 Injection molding process – schematic flow illustration. Picture courtesy of Engel GmbH Austria and IPIM, Johannes Kepler University Linz, Austria.
Figure 10.18 Strand cutting. Picture courtesy of Automatik Plastics Machinery GmbH.
Figure 10.19 Hot die face cutting. Picture courtesy of Automatik Plastics Machinery GmbH.
Figure 10.20 Cooling calender principle. Picture courtesy of BBA Innova GmbH.
Figure 10.21 Coat-hanger die (according to Hensen
et al
. [13]).
Figure 10.22 Time-dependent migration of layer A into layer B during co-extrusion.
Figure 10.23 Example process line with process parameters provided by the unit operations (light gray boxes), PAT tools (white boxes) and out of specification segregation spot (dark gray boxes).
Figure 10.24 Schematic overview of a typical sequence: from multivariate raw data (e.g., spectra, images) to product quality parameters (e.g., API concentration, coating thickness of pellets or tablets) [44].
Figure 10.25 Schematic of a basic data acquisition and process control system for a continuous HME line consisting of several processes (i.e., feeding, extrusion, pelletizing, etc.).
Chapter 11: Continuous Processing in the Pharmaceutical Industry: Status and Perspective
Figure 11.1 Countercurrent multi-column chromatography system (courtesy of Jornitz Biosystems Inc.).
Figure 11.2 Prefabricated, autonomous cleanroom units (courtesy of G-CON Manufacturing Inc.).
Figure 11.3 A horizontal wet granulation line, including compression and coating equipment (courtesy of GEA).
Figure 11.4 Gravity flow in a horizontal set-up (courtesy of GEA).
Figure 11.5 IBC docking station and contained material handling (courtesy of GEA).
Figure 11.6 From powder to coated tablets in a vertical set-up (courtesy of Vertex and GEA) [23].
Figure 11.7 Batch versus continuous: integration and space reduction (courtesy of GEA).
Figure 11.8 Nominal NPV after six years: batch (Batch DC) versus continuous (Conti DC) processing (courtesy of GEA).
Figure 11.9 Product launch cash flow: batch (Batch DC) versus continuous (CDC) processing (courtesy of GEA).
Figure 11.10 Nominal NPV after 6 years: batch (Batch DC) versus continuous (Conti DC) production of high volume/low value and low volume/high value product (courtesy of GEA).
Figure 11.11 M.E. Porter's value chain.
Figure 11.12 The bullwhip effect [32].
Figure 11.13 Continuous manufacturing, today and tomorrow (courtesy of Pfizer).
Figure 11.14 Material handling, wet granulation and direct compression in one horizontal layout (courtesy of GEA).
Chapter 12: Design of an Integrated Continuous Manufacturing System
Figure 12.1 Diagram of the main components of a loss in weight feeder. A volumetric feeder is mounted on a load cell with a feedback controller monitoring and controlling the feed rate.
Figure 12.2 (a) RTD response of a K-Tron KT-20 feeder to a pulse of tracer material (acetaminophen). The solid lines show the weight of the material in the feed hopper as a function time. The spikes indicate hopper refills. (b) Fit of the data to standard CSTR and PFR models. It can be observed that mixing inside the feeder mimics a perfect CSTR, characterizing substantial back mixing.
Figure 12.3 Effect of impeller speed on (a) mass-holdup, (b) number of blade passes, and (c) relative standard deviation of the active concentration in the outlet stream for an all forward blade configuration.
Figure 12.4 Illustration of radial mixing phenomenon in a continuous tubular blender along the blender length. Each radial cross-section in the blender exhibits the same arrangement of components over time but subsequent cross-sections do not.
Figure 12.5 Noise analysis of KT-20; worst case noise coupled with worst case RTD for filtering noise. (a) Normalized RTD of the blender. (b) Filtering ability of the blender. (c) Concentration in versus predicted concentration out after axial mixing in blender. (d) Noise spectrum of the raw feeder (upper line) versus effective frequency filtering done by the blender (lower line).
Figure 12.6 Model integration for a multi-unit operation process. Each block represents an individual unit operation model connected to a subsequent model using an information transfer port and an information connection. Both the port and connection type transfer specific information between units, which will become part of the calculations inside that unit. “Powder” connections and ports contain information regarding how each unit operation affected the powder stream properties such as flow rate, particle size, and bulk density.
Figure 12.7 At time 0, feed ratio was changed from 6% APAP to 10% APAP. The series of squares is the in-process spectra of the material post the blender. The series of circles represents NIR measurements on tablets sampled at the exit. It takes about 9 min after the perturbation having exited the blender to manifest itself into tablets.
Figure 12.8 Illustration of closed-loop and open-loop operation (adapted from [50]).
Figure 12.9 Combined feedforward/feedback control.
Figure 12.10 Integration of a control loop with the process model.
Figure 12.11 Flow of communication from a sensor to the data management tool. Examples of each tool from different vendors are also given.
Figure 12.12 Flow of communication from the PAT data management tool to the actuator.
Figure 12.13 Plant operating and control user interface.
Chapter 13: End to End Continuous Manufacturing: Integration of Unit Operations
Scheme 13.1 Synthetic route to aliskiren hemifumarate starting from advanced intermediate
1
using continuous processes.
Figure 13.1 Process flow diagram with control loops. P – pump; M – mixer; R – reactor; TC – temperature controller; PC – pressure controller; CT – concentration transmitter; FT – flow transmitter; RC – ratio controller; S – separation; Cr – crystallization vessel; LC – level controller; PT – pressure transmitter; W – filter/wash; D – dilution tank; CC – concentration controller; FC – flow controller; E – extruder; MD – mold; sp – control set point. Adapted from [1]. Copyright 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Figure 13.2 Dynamic development of the level in crystallizer Cr2 during startup (a) and concentration of
4
in the mother liquor in crystallizer Cr2 obtained from HPLC analysis during the same period (b).
Figure 13.3 Dynamic development of the chord length distribution of API crystals during an experimental run of an integrated CM pilot plant. Reprinted (adapted) with permission from [37]. Copyright 2014 American Chemical Society.
Figure 13.4 Examples of hierarchical viewings for the continuous pharmaceutical pilot plant.
Figure 13.5 The concentration of an inert impurity at the outlet of an integrated continuous pharmaceutical pilot plant, which was introduced as a short pulse at the inlet of the process. The data have been obtained from simulations using a state of the art process simulator (JACOBIAN®, Res Group Inc.).
Figure 13.6 Flow rate of HCl added to mixer M3 (manipulated variable of ratio control RC2).
Figure 13.7 Dynamic development of the concentration of key intermediate compounds: (a) compound
4
in dilution tank D1; (b) compound
6
in dilution tank D2. Both concentrations are obtained via a density measurement. The dotted gray line is the set point of the automated feedback controllers. Reprinted (adapted) with permission from [53]. Copyright 2014 American Chemical Society.
Figure 13.8 Process flow sheet for two possible configurations to control the concentration of an intermediate compound within the CM process (salt filters are not shown). In scheme (a), the UV sensor (CT) is used for monitoring and the fresh solvent flow rate is the manipulated variable of a ratio control loop (RC). In scheme (b), the UV sensor (CT) is a controlled variable within an outer concentration control loop (CC) that manipulates the set point of an inner ratio control loop (RC).
Figure 13.9 Dynamic development of the concentration of compound
5
before entering the dehydration column (S5) for two tested control schemes: (a) ratio control only [configuration (a) in Figure 13.8]; (b) ratio control with an outer feedback concentration control loop [configuration (b) in Figure 13.8] including set point (solid line). Reprinted (adapted) with permission from [53]. Copyright 2014 American Chemical Society.
Figure 13.10 Measurement of time delay and approximation of the measured response with a first order plus dead time process.
Figure 13.11 Dynamic development of the level in crystallizer Cr2 during a period of operation where the influence of disturbances was clearly visible (set point is indicated by the gray dashed line).
Figure 13.12 Example of a comparison of experimental pilot plant behavior and simulated pilot plant behavior after parameter estimation [22].
Figure 13.13 Predicted behavior of optimal averaging level controllers for a selected disturbance that occurred during pilot plant operation. The triangles illustrate the simulated process behavior with a proportional feedback controller as implemented during pilot plant operation. The circles illustrate a proportional–integral feedback controller with tuned parameters that are recommended for averaging level control [18]. The diamonds illustrate the simulated behavior in the case of optimal averaging level control [21] would be implemented [22].
Figure 13.14 Dynamic development of in-line pressure around two parallel reactors (R2). The sudden increase in pressure just after triggers an alarm for the operator.
Figure 13.15 (a) Emulsion droplets with a dissolved hydrophobic API are dispersed in an aqueous solvent containing the uncrosslinked alginate. (b) Upon cross-linking in a calcium bath, the nano- or macro-emulsion droplets are entrapped in the hydrogel matrix. (c) Upon evaporation, the dissolved API in emulsion droplets crystallizes to form crystals that are embedded in the dried hydrogel matri13. Panels (d) and (e) show hydrated “cross-linked” and “dried” composite hydrogel particles, respectively. (f) Microscopy images of “dried” composite hydrogels and (g) SEM image of “dried” composite hydrogel sliced open with embedded API identified (dotted circle). Reprinted with permission from [39]. Copyright 2014 American Chemical Society.
Figure 13.16 (a) Dissolution profile of dried composite hydrogel particles with different crystal sizes prepared by controlling the emulsion droplet size at fixed API concentration (saturated fenofibrate in anisole). (b) Dissolution profile of smaller crystals in hydrogel particles compared to the commercial drug product Tricor tablets. Reprinted (adapted) with permission from [39]. Copyright 2014 American Chemical Society.
Figure 13.17 Tablets made from composite hydrogel particles containing fenofibrate crystals () and final drug loading of 40%. Reprinted with permission from [39]. Copyright 2014 American Chemical Society.
Figure 13.18 Schematic and photos of making and processing thin films into tablets. A wet mass is made with dissolved or crystallized API. The wet mass is coated and dried in a commercial coater, folded, bonded, and tableted.
Figure 13.19 AFM images of PVA films containing nano-indentations with (a) 40, (b) 60, (c) 65, (d) 80, (e) 85, and (f) 90 degree angles, as well as (g) round indentations. Reprinted with permission from [40]. Copyright 2015 American Chemical Society.
Figure 13.20 (a) Schematic of electrospinning. (b) Tablets made from electrospun materials.
Figure 13.21 SEM micrographs of drug particles (fenofibrate) on electrospun PVA fibers.
Chapter 14: Methodology for Economic and Technical Comparison of Continuous and Batch Processes to Enhance Early Stage Decision-making
Figure 14.1 Decision-making chain and development progress for implementation of a new process.
Figure 14.2 Methodology for evaluating process chains in early stage development.
Figure 14.3 Example of pharmaceutical process chain of primary and secondary manufacturing.
Figure 14.4 Overview of the overall equipment effectiveness [15, 16, 22].
Figure 14.5 Methodological sequence to evaluate the process option.
Figure 14.6 Typical simulation work flow and cost influencing factors [13].
Figure 14.7 Methodology to evaluate processes and their technical feasibility according to the cost-utility analysis [12].
Chapter 15: Drivers for a Change – Manufacturing of Future Medicines for Personalized Drug Therapies
Figure 15.1 Idealized point of care device. Reprinted with permission from [5]. Copyright (2012) American Chemical Society.
Figure 15.2 Concepts for individual dosing using solid and liquid oral drug formulations [11] with permission from Elsevier.
Figure 15.3 Schematic drawing of the solid dosage pen [8] with permission from Elsevier.
Figure 15.4 Counting and dispensing devices from Balda Medical. Left: mechanical device (mMTS); center: electronical device (eMTS); right: “wheel mouse” (sMTS) with control tube for visual inspection.
Figure 15.5 Classes for combination products enabling flexible drug dosing [11] with permission from Elsevier.
Figure 15.6 Manufacturing on demand based on printing: inkjet printing of different drugs and drug loads. Reprinted from [20] with a permission from Elsevier.
Figure 15.7 Customised structures for 3D printed products: (a) API in layers; (b) API core inside a coat. Reprinted with permission from [25]. Copyright (2015) American Chemical Society.
Figure 15.8 Preformulation and characterization challenges of inkjet printable formulations. Reprinted from [29], with permission from Elsevier.
Figure 15.9 Engineering view of pharmaceutical development. Reprinted from [32], with permission from Elsevier.
Figure 15.10 Elements of the future healthcare system. Reprinted from [32], with permission from Elsevier.
Chapter 16: Perspectives of Printing Technologies in Continuous Drug Manufacturing
Figure 16.1 Schematic presentation of printing technologies of potential interest for the printing of bioactive substances. The printing technologies shown are qualitatively divided according to their print resolution and throughput capabilities. Top left: flexography; top right: gravure; bottom left: screen; bottom right: inkjet.
Figure 16.2 Schematic illustrations of the operating principles of various inkjet technologies. Left: Single jet continuous inkjet system (binary mode). Middle: Drop on demand thermal inkjet system (single drop). Right: Drop on demand piezoelectric inkjet system (single drop).
Figure 16.3 A schematic illustration of a flexographic printing unit.
Figure 16.4 A proposed approach for a continuous manufacturing line combining inkjet deposition of the active substance and flexographic deposition of a functional film coating on top of the active substance.
Figure 16.5 A theophylline formulation printed on the paper substrate. Upper Left: Pseudo colored image of the original set of samples (concentration of the drug is increasing in each printed area from left to right). Upper Right: PCA contour 2D plot of the original image with a marked square of selected pixels of interest. Lower: 2D score plot showing clustering of similar pixels, contribution of each PC and the corresponding data swarm of the chosen area of interest.
Figure 16.6 The functional materials (FunMat) printer at Åbo Akademi University. This is used as a laboratory-scale modular prototype printer that can be operated in a continuous manner and can be used sequentially in up to six different printing units (gravure, flexo, coating, ink-jet, lamination).
Figure 16.7 Diagram of a typical FDM/FFF extruder (modified from [58]).
Chapter 17: Development of Liquid Dispensing Technology for the Manufacture of Low Dose Drug Products
Figure 17.1 Overview of the LDT process for the manufacture of low-dose and potent API.
Figure 17.2 Bi-concave carrier tablet substrate,
Figure 17.3 Photograph of an LDT tablet showing the deposited, dry film.
Figure 17.4 Laboratory LDT machine.
Figure 17.5 GMP pilot LDT machine.
Figure 17.6 Commercial scale LDT machine.
Figure 17.7 Laboratory simulator of commercial LDT machine.
Figure 17.8 Transport element with RFID tag.
Figure 17.9 In-flight droplet image.
Figure 17.10 In-flight droplet calibration check reticule.
Figure 17.11 Two dispenser reproducibility from the commercial machine.
Figure 17.12 Two dispenser process capability from the commercial machine.
Figure 17.13 Inert carrier tablet incoming quality inspection.
Figure 17.14 Wet dose verification.
Figure 17.15 Dry dose NIR imaging.
Figure 17.16 Pad printed marking of LDT tablets.
Figure 17.17 Three examples (a, b, c) of commercial batch release screens.
Figure 17.18 Stainless steel holder and piston/cylinder assembly.
List of Tables
Chapter 1: Continuous Manufacturing: Definitions and Engineering Principles
Table 1.1 Unit operations relevant to continuous pharmaceutical manufacturing
Chapter 2: Process Simulation and Control for Continuous Pharmaceutical Manufacturing of Solid Drug Products
Table 2.1 Process systems engineering (PSE) tools for process development. PSE tools in order of chronological development that can be used for process development
Table 2.2 Unit operations commonly used in continuous pharmaceutical manufacturing
Table 2.3 Types of models used in the solid drug product manufacturing process
Chapter 5: Continuous Crystallisation
Table 5.1 Key stages, aims and consideration for selection of conditions during continuous crystallisation
Table 5.2 A number of empirical nucleation rate expressions
Table 5.3 Commonly used crystal growth rate expressions
Table 5.4 Comparison of product yield and purity. Summarised from [89]
Table 5.5 Comparison of the MSMPR with recycle and three-stage MSMPR cooling crystallisation for cyclosporine [31]
Table 5.6 Summary of types of PAT implementation for continuous crystallisation
Table 5.7 PAT techniques for monitoring continuous crystallisation
Table 5.8 Summary of off line chemical and physical analytical techniques of value in the characterisation of pharmaceutical solids produced from crystallisation processes
Chapter 6: Continuous Fermentation for Biopharmaceuticals?
Table 6.1 Comparison of the three cultivation modes
Table 6.2 Model inputs, disturbances and states for a typical fermentation process
Table 6.3 A short review of commercial continuous perfusion cultures for biopharmaceuticals produced from mammalian cell culture
Chapter 7: Integrated Continuous Manufacturing of Biopharmaceuticals
Table 7.1 Cell culture products and reactor types for manufacturing of biopharmaceuticals by perfusion and continuous culture (data from Pollok and Farid [60] and Desai [17])
Table 7.2 Categories of continuous chromatography methods for downstream processing of biopharmaceuticals
Table 7.3 Most common precipitants for the precipitation of proteins and their industrial application
Table 7.4 Summary of single use bioreactors for production of biopharmaceuticals
Chapter 11: Continuous Processing in the Pharmaceutical Industry: Status and Perspective
Table 11.1 Cell culture process comparison (courtesy of John Bonham-Parker)
Table 11.2 Factors of economic success
Chapter 13: End to End Continuous Manufacturing: Integration of Unit Operations
Table 13.1 Average nucleation induction times, their standard deviations and
r
2
values for cooling crystallization of aspirin in ethanol conducted at supersaturation ratios of
S
= 1.8 and
S
= 2.4. Reprinted with permission from [40]. Copyright 2015 American Chemical Society
Chapter 14: Methodology for Economic and Technical Comparison of Continuous and Batch Processes to Enhance Early Stage Decision-making
Table 14.1 Detailed analysis to determine the OEE, based on the impacting factors
Table 14.2 Major criteria for feasibility and risk evaluation (modified from [7])
Table 14.3 Risk scores for flowability in comparison to a given proces
Table 14.4 The Lang factors (
f
) for different plant operations
Table 14.5 Examples of factors for the calculation of process chain costs
Table 14.6 Process evaluation sheet resulting from comparative process evaluation
Chapter 16: Perspectives of Printing Technologies in Continuous Drug Manufacturing
Table 16.1 Characteristics of 3D manufacturing (modified from Berman [55])
Table 16.2 FDM, FDMet, and FDC process variables (modified from Agarwala
et al
. [59])
Chapter 17: Development of Liquid Dispensing Technology for the Manufacture of Low Dose Drug Products
Table 17.1 Clinical campaign release testing results
Table 17.2 Differences between the pilot scale and commercial scale machines
Table 17.3 Critical quality attributes (CQAs) and control strategy
Advances in Pharmaceutical Technology
A Wiley Book Series
Series Editors:
Dennis Douroumis, University of Greenwich, UK
Alfred Fahr, Friedrich-Schiller University of Jena, Germany
Jürgen Siepmann, University of Lille, France
Martin Snowden, University of Greenwich, UK
Vladimir Torchilin, Northeastern University, USA
Titles in the Series
Hot-Melt Extrusion: Pharmaceutical Applications
Edited by Dionysios Douroumis
Drug Delivery Strategies for Poorly Water-Soluble Drugs
Edited by Dionysios Douroumis and Alfred Fahr
Computational Pharmaceutics: Application of Molecular Modeling in Drug Delivery
Edited by Defang Ouyang and Sean C. Smith
Pulmonary Drug Delivery: Advances and Challenges
