Description

Book Synopsis
Process Analytical Technology explores the concepts of this technology and its application in the chemical and pharmaceutical industry from the point of view of the analytical chemist.

Trade Review
"Overall, this excellent compilation is highly recommended." (Organic Process Research and Development, January 2011)



Table of Contents

Preface to the Second Edition xvii

List of Contributors xix

List of Abbreviations xxi

1 Overview of Process Analysis and PAT 1
Jason E. Dickens

1.1 Introduction 1

1.1.1 Historical perspective 3

1.1.2 Business drivers 4

1.2 Execution of Process Analysis Projects 5

1.2.1 Wisdoms 5

1.2.2 Team structure 6

1.2.3 Project life cycle 6

1.2.4 Project scoping 9

1.2.5 Common challenges and pitfalls 10

1.3 Process Instrumentation 12

1.3.1 Process instrumentation types 12

1.3.2 Novel process instrumentation 12

1.4 Conclusions 13

1.5 Glossary of Acronyms and Terms 14

References 14

2 Implementation of Process Analytical Technologies 17
Robert Guenard and Gert Thurau

2.1 Introduction to Implementation of Process Analytical Technologies (PAT) in the Industrial Setting 17

2.1.1 Definition of process analytics 18

2.1.2 Differences between process analyzers and laboratory analysis 19

2.1.3 General industrial drivers for PA 19

2.1.4 Types of applications (R&D versus manufacturing) 20

2.1.5 Organizational considerations 20

2.2 Generalized Process Analytics Work Process 23

2.2.1 Project identification and definition 24

2.2.2 Analytical application development 26

2.2.3 Design, specify and procure 26

2.2.4 Implementation in production 28

2.2.5 Routine operation 29

2.2.6 Continuous improvement 30

2.3 Considerations for PAT Implementation in the Pharmaceutical Industry 30

2.3.1 Introduction 30

2.3.2 Business model 30

2.3.3 Technical differences 31

2.3.4 Regulatory Aspects of Process Analytics in the Pharmaceutical Industry –the Concept of Quality by Design 33

2.4 Conclusions 36

References 36

3 Process Sampling: Theory of Sampling – the Missing Link in Process Analytical Technologies (PAT) 37
Kim H. Esbensen and Peter Paasch-Mortensen

3.1 Introduction 37

3.2 Theory of Sampling – Introduction 39

3.2.1 Heterogeneity 41

3.2.2 Constitutional heterogeneity 41

3.2.3 Distributional heterogeneity 42

3.2.4 Structurally correct sampling 45

3.2.5 Incorrect sampling error 45

3.2.6 Increment delimitation error 45

3.2.7 Increment extraction error 46

3.2.8 Increment preparation error 46

3.2.9 Increment weighing error 47

3.2.10 Total sampling error 48

3.2.11 Global estimation error 48

3.3 Mass Reduction as a Specific Sampling Procedure 48

3.4 Fundamental Sampling Principle 51

3.5 Sampling – a Very Practical Issue 51

3.5.1 Sampling unit operations 52

3.5.2 Understanding process sampling: 0-D versus 1-D LOTS 52

3.5.3 Grab sampling – 0-D and 1-D 54

3.5.4 Correct process sampling: increment delimitation/extraction 56

3.5.5 PAT versus correct process sampling – what is required? 58

3.6 Reactors and Vessels – Identical Process Sampling Issues 60

3.6.1 Correct process sampling with existing process technology 62

3.6.2 Upward flux – representative colocated PAT sampling 62

3.6.3 Upstream colocated PAT sampler 64

3.7 Heterogeneity Characterization of 1-D lots: Variography 66

3.7.1 Process sampling modes 67

3.7.2 The experimental variogram 67

3.7.3 Sampling plan simulation and estimation of TSE 71

3.7.4 TSE estimation for 0-D lots – batch sampling 72

3.7.5 Corporate QC benefits of variographic analysis 73

3.8 Data Quality – New Insight from the TOS 75

3.9 Validation in Chemometrics and PAT 76

3.10 Summary 78

References 79

4 UV-visible Spectroscopy for On-line Analysis 81
Marcel A. Liauw, Lewis C. Baylor and Patrick E. O’Rourke

4.1 Introduction 81

4.2 Theory 82

4.2.1 Chemical concentration 82

4.2.2 Color 84

4.2.3 Film thickness 85

4.2.4 Turbidity 85

4.2.5 Plasmons/nanoparticles 85

4.3 Instrumentation 85

4.4 Sample Interface 86

4.4.1 Cuvette/vial 87

4.4.2 Flow cells 87

4.4.3 Insertion probe 87

4.4.4 Reflectance probe 89

4.5 Implementation 89

4.5.1 A complete process analyzer 89

4.5.2 Troubleshooting 89

4.6 Applications 91

4.6.1 Gas and vapor analysis 92

4.6.2 Liquid analysis 92

4.6.3 Solid analysis 96

4.6.4 Other applications 99

4.7 Detailed Application Notes 100

4.7.1 Gas and vapor analysis: toluene 100

4.7.2 Liquid analysis: breakthrough curves 101

4.7.3 Solids analysis: extruded plastic color 101

4.7.4 Film thickness determination: polymer 103

4.8 Conclusion 104

References 104

5 Near-infrared Spectroscopy for Process Analytical Technology: Theory, Technology and Implementation 107
Michael B. Simpson

5.1 Introduction 107

5.2 Theory of Near-infrared Spectroscopy 112

5.3 Analyser Technologies in the Near-infrared 114

5.3.1 Light sources and detectors for near-infrared analyzers 114

5.3.2 The scanning grating monochromator and polychromator diode-array 119

5.3.3 The acousto-optic tunable filter (AOTF) analyzer 123

5.3.4 Fourier transform near-infrared analyzers 127

5.3.5 Emerging technologies in process NIR analyzers 134

5.4 The Sampling Interface 136

5.4.1 Introduction 136

5.4.2 Problem samples: liquids, slurries and solids 142

5.4.3 The use of fiber optics 145

5.5 Practical Examples of Near-infrared Analytical Applications 147

5.5.1 Refinery hydrocarbon streams 148

5.5.2 Polyols, ethoxylated derivatives, ethylene oxide/propylene oxide polyether polyols 149

5.5.3 Oleochemicals, fatty acids, fatty amines and biodiesel 151

5.6 Conclusion 152

References 153

6 Infrared Spectroscopy for Process Analytical Applications 157
John P. Coates

6.1 Introduction 157

6.2 Practical Aspects of IR Spectroscopy 161

6.3 Instrumentation Design and Technology 163

6.4 Process IR Instrumentation 166

6.4.1 Commercially available IR instruments 167

6.4.2 Important IR component technologies 172

6.4.3 New technologies for IR components and instruments 176

6.4.4 Requirements for process infrared analyzers 178

6.4.5 Sample handling for IR process analyzers 185

6.4.6 Issues for consideration in the implementation of process IR 187

6.5 Applications of Process IR Analyzers 189

6.6 Process IR Analyzers: a Review 191

6.7 Trends and Directions 192

References 193

7 Raman Spectroscopy 195
Nancy L. Jestel

7.1 Attractive Features of Raman Spectroscopy 195

7.1.1 Quantitative information 195

7.1.2 Flexible sample forms and sizes used as accessed without damage 196

7.1.3 Flexible sample interfaces 196

7.1.4 Attractive spectral properties and advantageous selection rules 197

7.1.5 High sampling rate 197

7.1.6 Stable and robust equipment 198

7.2 Potential Issues with Raman Spectroscopy 198

7.2.1 High background signals 198

7.2.2 Stability 198

7.2.3 Too much and still too little sensitivity 199

7.2.4 Personnel experience 199

7.2.5 Cost 200

7.3 Fundamentals of Raman Spectroscopy 200

7.4 Raman Instrumentation 203

7.4.1 Safety 203

7.4.2 Laser wavelength selection 204

7.4.3 Laser power and stability 204

7.4.4 Spectrometer 205

7.4.5 Sample interface (probes) 206

7.4.6 Communications 208

7.4.7 Maintenance 209

7.5 Quantitative Raman 209

7.6 Applications 212

7.6.1 Acylation, alkylation, catalytic cracking, and transesterification 213

7.6.2 Bioreactors 213

7.6.3 Blending 214

7.6.4 Calcination 214

7.6.5 Catalysis 215

7.6.6 Chlorination 216

7.6.7 Counterfeit pharmaceuticals 217

7.6.8 Extrusion 218

7.6.9 Forensics 218

7.6.10 Hydrogenation 218

7.6.11 Hydrolysis 219

7.6.12 Medical diagnostics 219

7.6.13 Microwave-assisted organic synthesis 219

7.6.14 Mobile or field uses 220

7.6.15 Natural products 220

7.6.16 Orientation, stress, or strain 221

7.6.17 Ozonolysis 222

7.6.18 Polymerization 222

7.6.19 Polymer curing 224

7.6.20 Polymorphs (crystal forms) 225

7.6.21 Product properties 228

7.6.22 Purification: distillation, filtration, drying 229

7.6.23 Thin films or coatings 229

7.7 Current State of Process Raman Spectroscopy 230

References 231

8 Near-infrared Chemical Imaging for Product and Process Understanding 245
E. Neil Lewis, Joseph W. Schoppelrei, Lisa Makein, Linda H. Kidder and Eunah Lee

8.1 The PAT Initiative 245

8.2 The Role of Near-infrared Chemical Imaging (NIR-CI) in the Pharmaceutical Industry 246

8.2.1 Characterization of solid dosage forms 246

8.2.2 ‘A picture is worth a thousand words’ 247

8.3 Evolution of NIR Imaging Instrumentation 247

8.3.1 Spatially resolved spectroscopy – mapping 247

8.3.2 The infrared focal-plane array 247

8.3.3 Wavelength selection 248

8.3.4 The benefits of NIR spectroscopy 248

8.3.5 NIR imaging instrumentation 249

8.4 Chemical Imaging Principles 251

8.4.1 The hypercube 251

8.4.2 Data analysis 251

8.4.3 Spectral correction 252

8.4.4 Spectral preprocessing 253

8.4.5 Classification 253

8.4.6 Image processing – statistical 255

8.4.7 Image processing – morphology 257

8.5 PAT Applications 257

8.5.1 Content uniformity measurements – ‘self calibrating’ 258

8.5.2 Quality assurance – imaging an intact blister pack 260

8.5.3 Contaminant detection 261

8.5.4 Imaging of coatings – advanced design delivery systems 263

8.6 Processing Case Study: Estimating ‘Abundance’ of Sample Components 267

8.6.1 Experimental 268

8.6.2 Spectral correction and preprocessing 268

8.6.3 Analysis 268

8.6.4 Conclusions 273

8.7 Processing Case Study: Determining Blend Homogeneity Through Statistical Analysis 273

8.7.1 Experimental 273

8.7.2 Observing visual contrast in the image 274

8.7.3 Statistical analysis of the image 274

8.7.4 Blend uniformity measurement 276

8.7.5 Conclusions 276

8.8 Final Thoughts 277

Acknowledgements 278

References 278

9 Acoustic Chemometric Monitoring of Industrial Production Processes 281
Maths Halstensen and Kim H. Esbensen

9.1 What is Acoustic Chemometrics? 281

9.2 How Acoustic Chemometrics Works 282

9.2.1 Acoustic sensors 282

9.2.2 Mounting acoustic sensors (accelerometers) 283

9.2.3 Signal processing 284

9.2.4 Chemometric data analysis 284

9.2.5 Acoustic chemometrics as a PAT tool 284

9.3 Industrial Production Process Monitoring 285

9.3.1 Fluidized bed granulation monitoring 285

9.3.2 Pilot scale studies 286

9.3.3 Monitoring of a start-up sequence of a continuous fluidized bed granulator 291

9.3.4 Process monitoring as an early warning of critical shutdown situations 295

9.3.5 Acoustic chemometrics for fluid flow quantification 296

9.4 Available On-line Acoustic Chemometric Equipment 299

9.5 Discussion 301

9.5.1 Granulator monitoring 301

9.5.2 Process state monitoring 301

9.5.3 Ammonia concentration monitoring 301

9.6 Conclusions 302

References 302

10 Process NMR Spectroscopy: Technology and On-line Applications 303
John C. Edwards and Paul J. Giammatteo

10.1 Introduction 303

10.2 NMR Spectroscopy Overview 305

10.2.1 The NMR phenomenon 305

10.2.2 Time–domain-NMR: utilization of the FID and spin relaxation 309

10.2.3 High-resolution NMR: obtaining a spectrum with resolved chemical shift information 312

10.3 Process NMR Instrumentation 313

10.3.1 Spectrometer and magnet design 313

10.3.2 Sampling and experimental design 316

10.4 Postprocessing Methodologies for NMR Data 317

10.5 Advantages and Limitations of NMR as a Process Analytical Technology 320

10.5.1 Advantages 320

10.5.2 Limitations 321

10.6 On-line and At-line Applications 321

10.6.1 Time–domain NMR 322

10.6.2 High-resolution NMR: chemometric applications 323

10.7 Current Development and Applications 330

10.8 Conclusions 331

References 332

11 Fluorescent Sensing and Process Analytical Applications 337
Jason E. Dickens

11.1 Introduction 337

11.2 Luminescence Fundamentals 338

11.2.1 Luminescence nomenclature 338

11.2.2 Luminescence processes 338

11.2.3 Fluorophore classification 338

11.3 LIF Sensing Fundamentals 341

11.3.1 LIF sensing classification 341

11.3.2 Luminescence spectroscopy 342

11.3.3 LIF signal response function 343

11.4 LIF Sensing Instrumentation 343

11.4.1 LIF photometric instrument specification 345

11.4.2 LIF Instrument selection 347

11.5 Luminescent Detection Risks 347

11.6 Process Analytical Technology Applications 348

11.6.1 Petrochemical, chemical and nuclear field applications 349

11.6.2 Pharmaceutical PAT applications 349

11.7 Conclusions 350

References 351

12 Chemometrics in Process Analytical Technology (PAT) 353

Charles E. Miller

12.1 Introduction 353

12.1.1 What is chemometrics? 353

12.1.2 Some history 354

12.1.3 Some philosophy 355

12.1.4 Chemometrics in analytical chemistry? 355

12.1.5 Chemometrics in process analytical chemistry? 356

12.2 Foundations of Chemometrics 356

12.2.1 Notation 356

12.2.2 Some basic statistics 358

12.2.3 Linear regression 359

12.2.4 Multiple linear regression 361

12.2.5 Principal components analysis (PCA) 362

12.2.6 Design of experiments (DOE) 366

12.3 Chemometric Methods in PAT 368

12.3.1 Data preprocessing 369

12.3.2 Quantitative model building 377

12.3.3 Qualitative model building 389

12.3.4 Exploratory analysis 397

12.4 Overfitting and Model Validation 407

12.4.1 Overfitting and underfitting 407

12.4.2 Test set validation 408

12.4.3 Cross validation 410

12.5 Outliers 413

12.5.1 Introduction to outliers 413

12.5.2 Outlier detection and remediation 413

12.6 Calibration Strategies in PAT 416

12.6.1 The ‘calibration strategy space’ 417

12.6.2 Strategies for direct versus inverse modeling methods 418

12.6.3 Hybrid strategies 419

12.7 Sample and Variable Selection in Chemometrics 420

12.7.1 Sample selection 420

12.7.2 Variable selection 421

12.8 Troubleshooting/Improving an Existing Method 425

12.8.1 Method assessment 425

12.8.2 Model improvement strategies 425

12.9 Calibration Transfer and Instrument Standardization 426

12.9.1 Slope/intercept adjustment 428

12.9.2 Piecewise direct standardization (PDS) 428

12.9.3 Generalized least squares (GLS) weighting 429

12.9.4 Shenk–Westerhaus method 429

12.9.5 Other transfer/standardization methods 429

12.10 Chemometric Model Deployment Issues in PAT 430

12.10.1 Outliers in prediction 430

12.10.2 Deployment software 432

12.10.3 Data systems, and control system integration 432

12.10.4 Method updating 433

12.11 People Issues 433

12.12 The Final Word 434

References 434

13 On-line PAT Applications of Spectroscopy in the Pharmaceutical Industry 439
Brandye Smith-Goettler

13.1 Background 439

13.2 Reaction Monitoring 441

13.3 Crystallization 442

13.4 API Drying 443

13.5 Nanomilling 444

13.6 Hot-melt Extrusion 445

13.7 Granulation 446

13.7.1 Wet granulation 446

13.7.2 Roller compaction 449

13.8 Powder Blending 450

13.8.1 Lubrication 451

13.8.2 Powder flow 451

13.9 Compression 452

13.10 Coating 452

13.11 Biologics 453

13.11.1 Fermentation 453

13.11.2 Freeze-drying 454

13.12 Cleaning Validation 454

13.13 Conclusions 455

References 455

14 NIR spectroscopy in Pharmaceutical Analysis: Off-line and At-line PAT Applications 463
Marcelo Blanco Romía and Manel Alcalá Bernárdez

14.1 Introduction 463

14.1.1 Operational procedures 464

14.1.2 Instrument qualification 466

14.2 Foundation of Qualitative Method Development 466

14.2.1 Pattern recognition methods 467

14.2.2 Construction of spectral libraries 468

14.2.3 Identification and qualification 470

14.3 Foundation of Quantitative Method Development 471

14.3.1 Selection and preparation of samples 472

14.3.2 Preparation and selection of samples 473

14.3.3 Determination of reference values 474

14.3.4 Acquisition of spectra 474

14.3.5 Construction of the calibration model 475

14.3.6 Model validation 476

14.3.7 Prediction of new samples 476

14.4 Method Validation 476

14.5 Calibration Transfer 476

14.6 Pharmaceutical Applications 478

14.6.1 Identification of raw materials 478

14.6.2 Homogeneity 478

14.6.3 Moisture 480

14.6.4 Determination of physical parameters 481

14.6.5 Determination of chemical composition 483

14.7 Conclusions 485

References 486

15 Near-infrared Spectroscopy (NIR) as a PAT Tool in the Chemical Industry: Added Value and Implementation Challenges 493
Ann M. Brearley and Susan J. Foulk

15.1 Introduction 493

15.2 Successful Process Analyzer Implementation 494

15.2.1 A process for successful process analyzer implementation 494

15.2.2 How NIR process analyzers contribute to business value 497

15.2.3 Issues to consider in setting technical requirements for a process analyzer 498

15.2.4 Capabilities and limitations of NIR 499

15.2.5 General challenges in process analyzer implementation 500

15.2.6 Approaches to calibrating an NIR analyzer on-line 502

15.2.7 Special challenges in NIR monitoring of polymer melts 505

15.3 Example Applications 506

15.3.1 Monitoring monomer conversion during emulsion polymerization 506

15.3.2 Monitoring a diethylbenzene isomer separation process 508

15.3.3 Monitoring the composition of copolymers and polymer blends in an extruder 509

15.3.4 Rapid identification of carpet face fiber 512

15.3.5 Monitoring the composition of spinning solution 514

15.3.6 Monitoring end groups and viscosity in polyester melts 516

15.3.7 In-line monitoring of a copolymerization reaction 518

References 520

16 Future Trends for PAT for Increased Process Understanding and Growing Applications in Biomanufacturing 521
Katherine A. Bakeev and Jose C. Menezes

16.1 Introduction 521

16.2 Regulatory Guidance and its Impact on PAT 522

16.3 Going Beyond Process Analyzers Towards Solutions 524

16.3.1 Design of experiments for risk-based analysis 526

16.3.2 Sample and process fingerprinting with PAT tools 527

16.3.3 Design and Control Spaces 528

16.3.4 Chemometrics and process analysis 528

16.4 Emerging Application Areas of PAT 529

16.4.1 Biofuels 529

16.4.2 Biomanufacturing 530

16.5 New and Emerging Sensor and Control Technologies 531

16.5.1 Terahertz spectroscopy 531

16.5.2 Integrated sensing and processing 532

16.5.3 Dielectric spectroscopy 533

16.5.4 Process chromatography 533

16.5.5 Mass spectrometry 534

16.5.6 Microwave resonance 534

16.5.7 Novel sensors 535

16.5.8 Inferential sensors 536

16.6 Advances in Sampling: NeSSI 537

16.7 Challenges Ahead 537

16.7.1 Continuous process validation 538

16.7.2 Data challenges: data handling and fusion 539

16.7.3 Regulatory challenges 539

16.7.4 Enterprise systems for managing data 539

16.8 Conclusion 540

References 540

Index 545

Process Analytical Technology

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    A Hardback by Katherine A. Bakeev

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      Publisher: John Wiley & Sons Inc
      Publication Date: 20/04/2010
      ISBN13: 9780470722077, 978-0470722077
      ISBN10: 047072207X
      Also in:
      Chemistry

      Description

      Book Synopsis
      Process Analytical Technology explores the concepts of this technology and its application in the chemical and pharmaceutical industry from the point of view of the analytical chemist.

      Trade Review
      "Overall, this excellent compilation is highly recommended." (Organic Process Research and Development, January 2011)



      Table of Contents

      Preface to the Second Edition xvii

      List of Contributors xix

      List of Abbreviations xxi

      1 Overview of Process Analysis and PAT 1
      Jason E. Dickens

      1.1 Introduction 1

      1.1.1 Historical perspective 3

      1.1.2 Business drivers 4

      1.2 Execution of Process Analysis Projects 5

      1.2.1 Wisdoms 5

      1.2.2 Team structure 6

      1.2.3 Project life cycle 6

      1.2.4 Project scoping 9

      1.2.5 Common challenges and pitfalls 10

      1.3 Process Instrumentation 12

      1.3.1 Process instrumentation types 12

      1.3.2 Novel process instrumentation 12

      1.4 Conclusions 13

      1.5 Glossary of Acronyms and Terms 14

      References 14

      2 Implementation of Process Analytical Technologies 17
      Robert Guenard and Gert Thurau

      2.1 Introduction to Implementation of Process Analytical Technologies (PAT) in the Industrial Setting 17

      2.1.1 Definition of process analytics 18

      2.1.2 Differences between process analyzers and laboratory analysis 19

      2.1.3 General industrial drivers for PA 19

      2.1.4 Types of applications (R&D versus manufacturing) 20

      2.1.5 Organizational considerations 20

      2.2 Generalized Process Analytics Work Process 23

      2.2.1 Project identification and definition 24

      2.2.2 Analytical application development 26

      2.2.3 Design, specify and procure 26

      2.2.4 Implementation in production 28

      2.2.5 Routine operation 29

      2.2.6 Continuous improvement 30

      2.3 Considerations for PAT Implementation in the Pharmaceutical Industry 30

      2.3.1 Introduction 30

      2.3.2 Business model 30

      2.3.3 Technical differences 31

      2.3.4 Regulatory Aspects of Process Analytics in the Pharmaceutical Industry –the Concept of Quality by Design 33

      2.4 Conclusions 36

      References 36

      3 Process Sampling: Theory of Sampling – the Missing Link in Process Analytical Technologies (PAT) 37
      Kim H. Esbensen and Peter Paasch-Mortensen

      3.1 Introduction 37

      3.2 Theory of Sampling – Introduction 39

      3.2.1 Heterogeneity 41

      3.2.2 Constitutional heterogeneity 41

      3.2.3 Distributional heterogeneity 42

      3.2.4 Structurally correct sampling 45

      3.2.5 Incorrect sampling error 45

      3.2.6 Increment delimitation error 45

      3.2.7 Increment extraction error 46

      3.2.8 Increment preparation error 46

      3.2.9 Increment weighing error 47

      3.2.10 Total sampling error 48

      3.2.11 Global estimation error 48

      3.3 Mass Reduction as a Specific Sampling Procedure 48

      3.4 Fundamental Sampling Principle 51

      3.5 Sampling – a Very Practical Issue 51

      3.5.1 Sampling unit operations 52

      3.5.2 Understanding process sampling: 0-D versus 1-D LOTS 52

      3.5.3 Grab sampling – 0-D and 1-D 54

      3.5.4 Correct process sampling: increment delimitation/extraction 56

      3.5.5 PAT versus correct process sampling – what is required? 58

      3.6 Reactors and Vessels – Identical Process Sampling Issues 60

      3.6.1 Correct process sampling with existing process technology 62

      3.6.2 Upward flux – representative colocated PAT sampling 62

      3.6.3 Upstream colocated PAT sampler 64

      3.7 Heterogeneity Characterization of 1-D lots: Variography 66

      3.7.1 Process sampling modes 67

      3.7.2 The experimental variogram 67

      3.7.3 Sampling plan simulation and estimation of TSE 71

      3.7.4 TSE estimation for 0-D lots – batch sampling 72

      3.7.5 Corporate QC benefits of variographic analysis 73

      3.8 Data Quality – New Insight from the TOS 75

      3.9 Validation in Chemometrics and PAT 76

      3.10 Summary 78

      References 79

      4 UV-visible Spectroscopy for On-line Analysis 81
      Marcel A. Liauw, Lewis C. Baylor and Patrick E. O’Rourke

      4.1 Introduction 81

      4.2 Theory 82

      4.2.1 Chemical concentration 82

      4.2.2 Color 84

      4.2.3 Film thickness 85

      4.2.4 Turbidity 85

      4.2.5 Plasmons/nanoparticles 85

      4.3 Instrumentation 85

      4.4 Sample Interface 86

      4.4.1 Cuvette/vial 87

      4.4.2 Flow cells 87

      4.4.3 Insertion probe 87

      4.4.4 Reflectance probe 89

      4.5 Implementation 89

      4.5.1 A complete process analyzer 89

      4.5.2 Troubleshooting 89

      4.6 Applications 91

      4.6.1 Gas and vapor analysis 92

      4.6.2 Liquid analysis 92

      4.6.3 Solid analysis 96

      4.6.4 Other applications 99

      4.7 Detailed Application Notes 100

      4.7.1 Gas and vapor analysis: toluene 100

      4.7.2 Liquid analysis: breakthrough curves 101

      4.7.3 Solids analysis: extruded plastic color 101

      4.7.4 Film thickness determination: polymer 103

      4.8 Conclusion 104

      References 104

      5 Near-infrared Spectroscopy for Process Analytical Technology: Theory, Technology and Implementation 107
      Michael B. Simpson

      5.1 Introduction 107

      5.2 Theory of Near-infrared Spectroscopy 112

      5.3 Analyser Technologies in the Near-infrared 114

      5.3.1 Light sources and detectors for near-infrared analyzers 114

      5.3.2 The scanning grating monochromator and polychromator diode-array 119

      5.3.3 The acousto-optic tunable filter (AOTF) analyzer 123

      5.3.4 Fourier transform near-infrared analyzers 127

      5.3.5 Emerging technologies in process NIR analyzers 134

      5.4 The Sampling Interface 136

      5.4.1 Introduction 136

      5.4.2 Problem samples: liquids, slurries and solids 142

      5.4.3 The use of fiber optics 145

      5.5 Practical Examples of Near-infrared Analytical Applications 147

      5.5.1 Refinery hydrocarbon streams 148

      5.5.2 Polyols, ethoxylated derivatives, ethylene oxide/propylene oxide polyether polyols 149

      5.5.3 Oleochemicals, fatty acids, fatty amines and biodiesel 151

      5.6 Conclusion 152

      References 153

      6 Infrared Spectroscopy for Process Analytical Applications 157
      John P. Coates

      6.1 Introduction 157

      6.2 Practical Aspects of IR Spectroscopy 161

      6.3 Instrumentation Design and Technology 163

      6.4 Process IR Instrumentation 166

      6.4.1 Commercially available IR instruments 167

      6.4.2 Important IR component technologies 172

      6.4.3 New technologies for IR components and instruments 176

      6.4.4 Requirements for process infrared analyzers 178

      6.4.5 Sample handling for IR process analyzers 185

      6.4.6 Issues for consideration in the implementation of process IR 187

      6.5 Applications of Process IR Analyzers 189

      6.6 Process IR Analyzers: a Review 191

      6.7 Trends and Directions 192

      References 193

      7 Raman Spectroscopy 195
      Nancy L. Jestel

      7.1 Attractive Features of Raman Spectroscopy 195

      7.1.1 Quantitative information 195

      7.1.2 Flexible sample forms and sizes used as accessed without damage 196

      7.1.3 Flexible sample interfaces 196

      7.1.4 Attractive spectral properties and advantageous selection rules 197

      7.1.5 High sampling rate 197

      7.1.6 Stable and robust equipment 198

      7.2 Potential Issues with Raman Spectroscopy 198

      7.2.1 High background signals 198

      7.2.2 Stability 198

      7.2.3 Too much and still too little sensitivity 199

      7.2.4 Personnel experience 199

      7.2.5 Cost 200

      7.3 Fundamentals of Raman Spectroscopy 200

      7.4 Raman Instrumentation 203

      7.4.1 Safety 203

      7.4.2 Laser wavelength selection 204

      7.4.3 Laser power and stability 204

      7.4.4 Spectrometer 205

      7.4.5 Sample interface (probes) 206

      7.4.6 Communications 208

      7.4.7 Maintenance 209

      7.5 Quantitative Raman 209

      7.6 Applications 212

      7.6.1 Acylation, alkylation, catalytic cracking, and transesterification 213

      7.6.2 Bioreactors 213

      7.6.3 Blending 214

      7.6.4 Calcination 214

      7.6.5 Catalysis 215

      7.6.6 Chlorination 216

      7.6.7 Counterfeit pharmaceuticals 217

      7.6.8 Extrusion 218

      7.6.9 Forensics 218

      7.6.10 Hydrogenation 218

      7.6.11 Hydrolysis 219

      7.6.12 Medical diagnostics 219

      7.6.13 Microwave-assisted organic synthesis 219

      7.6.14 Mobile or field uses 220

      7.6.15 Natural products 220

      7.6.16 Orientation, stress, or strain 221

      7.6.17 Ozonolysis 222

      7.6.18 Polymerization 222

      7.6.19 Polymer curing 224

      7.6.20 Polymorphs (crystal forms) 225

      7.6.21 Product properties 228

      7.6.22 Purification: distillation, filtration, drying 229

      7.6.23 Thin films or coatings 229

      7.7 Current State of Process Raman Spectroscopy 230

      References 231

      8 Near-infrared Chemical Imaging for Product and Process Understanding 245
      E. Neil Lewis, Joseph W. Schoppelrei, Lisa Makein, Linda H. Kidder and Eunah Lee

      8.1 The PAT Initiative 245

      8.2 The Role of Near-infrared Chemical Imaging (NIR-CI) in the Pharmaceutical Industry 246

      8.2.1 Characterization of solid dosage forms 246

      8.2.2 ‘A picture is worth a thousand words’ 247

      8.3 Evolution of NIR Imaging Instrumentation 247

      8.3.1 Spatially resolved spectroscopy – mapping 247

      8.3.2 The infrared focal-plane array 247

      8.3.3 Wavelength selection 248

      8.3.4 The benefits of NIR spectroscopy 248

      8.3.5 NIR imaging instrumentation 249

      8.4 Chemical Imaging Principles 251

      8.4.1 The hypercube 251

      8.4.2 Data analysis 251

      8.4.3 Spectral correction 252

      8.4.4 Spectral preprocessing 253

      8.4.5 Classification 253

      8.4.6 Image processing – statistical 255

      8.4.7 Image processing – morphology 257

      8.5 PAT Applications 257

      8.5.1 Content uniformity measurements – ‘self calibrating’ 258

      8.5.2 Quality assurance – imaging an intact blister pack 260

      8.5.3 Contaminant detection 261

      8.5.4 Imaging of coatings – advanced design delivery systems 263

      8.6 Processing Case Study: Estimating ‘Abundance’ of Sample Components 267

      8.6.1 Experimental 268

      8.6.2 Spectral correction and preprocessing 268

      8.6.3 Analysis 268

      8.6.4 Conclusions 273

      8.7 Processing Case Study: Determining Blend Homogeneity Through Statistical Analysis 273

      8.7.1 Experimental 273

      8.7.2 Observing visual contrast in the image 274

      8.7.3 Statistical analysis of the image 274

      8.7.4 Blend uniformity measurement 276

      8.7.5 Conclusions 276

      8.8 Final Thoughts 277

      Acknowledgements 278

      References 278

      9 Acoustic Chemometric Monitoring of Industrial Production Processes 281
      Maths Halstensen and Kim H. Esbensen

      9.1 What is Acoustic Chemometrics? 281

      9.2 How Acoustic Chemometrics Works 282

      9.2.1 Acoustic sensors 282

      9.2.2 Mounting acoustic sensors (accelerometers) 283

      9.2.3 Signal processing 284

      9.2.4 Chemometric data analysis 284

      9.2.5 Acoustic chemometrics as a PAT tool 284

      9.3 Industrial Production Process Monitoring 285

      9.3.1 Fluidized bed granulation monitoring 285

      9.3.2 Pilot scale studies 286

      9.3.3 Monitoring of a start-up sequence of a continuous fluidized bed granulator 291

      9.3.4 Process monitoring as an early warning of critical shutdown situations 295

      9.3.5 Acoustic chemometrics for fluid flow quantification 296

      9.4 Available On-line Acoustic Chemometric Equipment 299

      9.5 Discussion 301

      9.5.1 Granulator monitoring 301

      9.5.2 Process state monitoring 301

      9.5.3 Ammonia concentration monitoring 301

      9.6 Conclusions 302

      References 302

      10 Process NMR Spectroscopy: Technology and On-line Applications 303
      John C. Edwards and Paul J. Giammatteo

      10.1 Introduction 303

      10.2 NMR Spectroscopy Overview 305

      10.2.1 The NMR phenomenon 305

      10.2.2 Time–domain-NMR: utilization of the FID and spin relaxation 309

      10.2.3 High-resolution NMR: obtaining a spectrum with resolved chemical shift information 312

      10.3 Process NMR Instrumentation 313

      10.3.1 Spectrometer and magnet design 313

      10.3.2 Sampling and experimental design 316

      10.4 Postprocessing Methodologies for NMR Data 317

      10.5 Advantages and Limitations of NMR as a Process Analytical Technology 320

      10.5.1 Advantages 320

      10.5.2 Limitations 321

      10.6 On-line and At-line Applications 321

      10.6.1 Time–domain NMR 322

      10.6.2 High-resolution NMR: chemometric applications 323

      10.7 Current Development and Applications 330

      10.8 Conclusions 331

      References 332

      11 Fluorescent Sensing and Process Analytical Applications 337
      Jason E. Dickens

      11.1 Introduction 337

      11.2 Luminescence Fundamentals 338

      11.2.1 Luminescence nomenclature 338

      11.2.2 Luminescence processes 338

      11.2.3 Fluorophore classification 338

      11.3 LIF Sensing Fundamentals 341

      11.3.1 LIF sensing classification 341

      11.3.2 Luminescence spectroscopy 342

      11.3.3 LIF signal response function 343

      11.4 LIF Sensing Instrumentation 343

      11.4.1 LIF photometric instrument specification 345

      11.4.2 LIF Instrument selection 347

      11.5 Luminescent Detection Risks 347

      11.6 Process Analytical Technology Applications 348

      11.6.1 Petrochemical, chemical and nuclear field applications 349

      11.6.2 Pharmaceutical PAT applications 349

      11.7 Conclusions 350

      References 351

      12 Chemometrics in Process Analytical Technology (PAT) 353

      Charles E. Miller

      12.1 Introduction 353

      12.1.1 What is chemometrics? 353

      12.1.2 Some history 354

      12.1.3 Some philosophy 355

      12.1.4 Chemometrics in analytical chemistry? 355

      12.1.5 Chemometrics in process analytical chemistry? 356

      12.2 Foundations of Chemometrics 356

      12.2.1 Notation 356

      12.2.2 Some basic statistics 358

      12.2.3 Linear regression 359

      12.2.4 Multiple linear regression 361

      12.2.5 Principal components analysis (PCA) 362

      12.2.6 Design of experiments (DOE) 366

      12.3 Chemometric Methods in PAT 368

      12.3.1 Data preprocessing 369

      12.3.2 Quantitative model building 377

      12.3.3 Qualitative model building 389

      12.3.4 Exploratory analysis 397

      12.4 Overfitting and Model Validation 407

      12.4.1 Overfitting and underfitting 407

      12.4.2 Test set validation 408

      12.4.3 Cross validation 410

      12.5 Outliers 413

      12.5.1 Introduction to outliers 413

      12.5.2 Outlier detection and remediation 413

      12.6 Calibration Strategies in PAT 416

      12.6.1 The ‘calibration strategy space’ 417

      12.6.2 Strategies for direct versus inverse modeling methods 418

      12.6.3 Hybrid strategies 419

      12.7 Sample and Variable Selection in Chemometrics 420

      12.7.1 Sample selection 420

      12.7.2 Variable selection 421

      12.8 Troubleshooting/Improving an Existing Method 425

      12.8.1 Method assessment 425

      12.8.2 Model improvement strategies 425

      12.9 Calibration Transfer and Instrument Standardization 426

      12.9.1 Slope/intercept adjustment 428

      12.9.2 Piecewise direct standardization (PDS) 428

      12.9.3 Generalized least squares (GLS) weighting 429

      12.9.4 Shenk–Westerhaus method 429

      12.9.5 Other transfer/standardization methods 429

      12.10 Chemometric Model Deployment Issues in PAT 430

      12.10.1 Outliers in prediction 430

      12.10.2 Deployment software 432

      12.10.3 Data systems, and control system integration 432

      12.10.4 Method updating 433

      12.11 People Issues 433

      12.12 The Final Word 434

      References 434

      13 On-line PAT Applications of Spectroscopy in the Pharmaceutical Industry 439
      Brandye Smith-Goettler

      13.1 Background 439

      13.2 Reaction Monitoring 441

      13.3 Crystallization 442

      13.4 API Drying 443

      13.5 Nanomilling 444

      13.6 Hot-melt Extrusion 445

      13.7 Granulation 446

      13.7.1 Wet granulation 446

      13.7.2 Roller compaction 449

      13.8 Powder Blending 450

      13.8.1 Lubrication 451

      13.8.2 Powder flow 451

      13.9 Compression 452

      13.10 Coating 452

      13.11 Biologics 453

      13.11.1 Fermentation 453

      13.11.2 Freeze-drying 454

      13.12 Cleaning Validation 454

      13.13 Conclusions 455

      References 455

      14 NIR spectroscopy in Pharmaceutical Analysis: Off-line and At-line PAT Applications 463
      Marcelo Blanco Romía and Manel Alcalá Bernárdez

      14.1 Introduction 463

      14.1.1 Operational procedures 464

      14.1.2 Instrument qualification 466

      14.2 Foundation of Qualitative Method Development 466

      14.2.1 Pattern recognition methods 467

      14.2.2 Construction of spectral libraries 468

      14.2.3 Identification and qualification 470

      14.3 Foundation of Quantitative Method Development 471

      14.3.1 Selection and preparation of samples 472

      14.3.2 Preparation and selection of samples 473

      14.3.3 Determination of reference values 474

      14.3.4 Acquisition of spectra 474

      14.3.5 Construction of the calibration model 475

      14.3.6 Model validation 476

      14.3.7 Prediction of new samples 476

      14.4 Method Validation 476

      14.5 Calibration Transfer 476

      14.6 Pharmaceutical Applications 478

      14.6.1 Identification of raw materials 478

      14.6.2 Homogeneity 478

      14.6.3 Moisture 480

      14.6.4 Determination of physical parameters 481

      14.6.5 Determination of chemical composition 483

      14.7 Conclusions 485

      References 486

      15 Near-infrared Spectroscopy (NIR) as a PAT Tool in the Chemical Industry: Added Value and Implementation Challenges 493
      Ann M. Brearley and Susan J. Foulk

      15.1 Introduction 493

      15.2 Successful Process Analyzer Implementation 494

      15.2.1 A process for successful process analyzer implementation 494

      15.2.2 How NIR process analyzers contribute to business value 497

      15.2.3 Issues to consider in setting technical requirements for a process analyzer 498

      15.2.4 Capabilities and limitations of NIR 499

      15.2.5 General challenges in process analyzer implementation 500

      15.2.6 Approaches to calibrating an NIR analyzer on-line 502

      15.2.7 Special challenges in NIR monitoring of polymer melts 505

      15.3 Example Applications 506

      15.3.1 Monitoring monomer conversion during emulsion polymerization 506

      15.3.2 Monitoring a diethylbenzene isomer separation process 508

      15.3.3 Monitoring the composition of copolymers and polymer blends in an extruder 509

      15.3.4 Rapid identification of carpet face fiber 512

      15.3.5 Monitoring the composition of spinning solution 514

      15.3.6 Monitoring end groups and viscosity in polyester melts 516

      15.3.7 In-line monitoring of a copolymerization reaction 518

      References 520

      16 Future Trends for PAT for Increased Process Understanding and Growing Applications in Biomanufacturing 521
      Katherine A. Bakeev and Jose C. Menezes

      16.1 Introduction 521

      16.2 Regulatory Guidance and its Impact on PAT 522

      16.3 Going Beyond Process Analyzers Towards Solutions 524

      16.3.1 Design of experiments for risk-based analysis 526

      16.3.2 Sample and process fingerprinting with PAT tools 527

      16.3.3 Design and Control Spaces 528

      16.3.4 Chemometrics and process analysis 528

      16.4 Emerging Application Areas of PAT 529

      16.4.1 Biofuels 529

      16.4.2 Biomanufacturing 530

      16.5 New and Emerging Sensor and Control Technologies 531

      16.5.1 Terahertz spectroscopy 531

      16.5.2 Integrated sensing and processing 532

      16.5.3 Dielectric spectroscopy 533

      16.5.4 Process chromatography 533

      16.5.5 Mass spectrometry 534

      16.5.6 Microwave resonance 534

      16.5.7 Novel sensors 535

      16.5.8 Inferential sensors 536

      16.6 Advances in Sampling: NeSSI 537

      16.7 Challenges Ahead 537

      16.7.1 Continuous process validation 538

      16.7.2 Data challenges: data handling and fusion 539

      16.7.3 Regulatory challenges 539

      16.7.4 Enterprise systems for managing data 539

      16.8 Conclusion 540

      References 540

      Index 545

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