Stavros Kromidas, PhD, works as an independent consultant for analytical chemistry, based in Blieskastel (Germany). For more than 20 years he has regularly held lectures and training courses on HPLC, and has authored numerous articles and several books on various aspects of chromatography. He is the founder of NOVIA GmbH, a provider of professional training and consulting in analytical chemistry, and served as its CEO until 2001.
Preface xv
About the Book xvii
Part I Optimization Strategies for Different Modes and Uses of HPLC1
1.1 2D-HPLC Method Development for Successful Separations3
Dwight R. Stoll, Ph.D.
1.1.1 Motivations for Two-Dimensional Separation 3
1.1.1.1 Difficult-to-Separate Samples 3
1.1.1.2 Complex Samples 4
1.1.1.3 Separation Goals 4
1.1.2 Choosing a Two-Dimensional Separation Mode 4
1.1.2.1 Analytical Goals Dictate Choice of Mode 5
1.1.2.2 Survey of Four 2D Separation Modes 5
1.1.2.3 Hybrid Modes Provide Flexibility 7
1.1.3 Choosing Separation Types/Mechanisms 8
1.1.3.1 Complementarity as a Guiding Principle 8
1.1.3.2 Pirok Compatibility Table 9
1.1.3.3 Measuring the Complementarity of Separation Types 9
1.1.4 Choosing Separation Conditions 11
1.1.4.1 Starting with Fixed First-Dimension Conditions 11
1.1.4.2 Starting from Scratch Flexible First-Dimension Conditions 13
1.1.4.3 Special Considerations for Comprehensive 2D-LC Methods 13
1.1.4.4 Rules of Thumb 13
1.1.5 Method Development Examples 14
1.1.5.1 Example 1 Use of LCLC to Identify an Impurity in a Synthetic Oligonucleotide 14
1.1.5.2 Example 2 Comprehensive 2D-LC Separation of Surfactants 14
1.1.6 Outlook for the Future 17
Acknowledgment 18
References 18
1.2 Do you HILIC? With Mass Spectrometry? Then do it Systematically23
Thomas Letzel
1.2.1 Initial Situation and Optimal Use of Stationary HILIC Phases 25
1.2.2 Initial Situation and Optimal Use of the Mobile HILIC Phase 28
1.2.2.1 Organic Solvent 28
1.2.2.2 Salts 31
1.2.2.3 pH Value 33
1.2.3 Further Settings and Conditions Specific to Mass Spectrometric Detection 35
1.2.4 Short Summary on Method Optimization in HILIC 36
References 36
1.3 Optimization Strategies in LCMS Method Development39
Markus M. Martin
1.3.1 Introduction 39
1.3.2 Developing New Methods for HPLCMS Separations 39
1.3.2.1 Optimizing the LC Separation 40
1.3.2.1.1 Optimizing for Sensitivity and Limit of Detection Which Column to Take? 40
1.3.2.1.2 Optimizing Resolution vs. Sample Throughput 41
1.3.2.1.3 MS-Compatible Eluent Compositions and Additives 43
1.3.2.2 Optimizing Ion Source Conditions 44
1.3.2.3 Optimizing MS Detection 47
1.3.2.4 Verifying the Hyphenated Method 48
1.3.2.5 Method Development Supported by Software-based Parameter Variation 49
1.3.3 Transferring Established HPLC Methods to Mass spectrometry 50
1.3.3.1 Transfer of an Entire HPLC Method to a Mass Spectrometer 51
1.3.3.2 Selected Analysis of an Unknown Impurity Solvent Change by Single-/Multi-Heartcut Techniques 52
Abbreviations 54
References 55
1.4 Chromatographic Strategies for the Successful Characterization of Protein Biopharmaceuticals57
Szabolcs Fekete, Valentina DAtri, and Davy Guillarme
1.4.1 Introduction to Protein Biopharmaceuticals 57
1.4.2 From Standard to High-Performance Chromatography of Protein Biopharmaceuticals 58
1.4.3 Online Coupling of Nondenaturing LC Modes with MS 62
1.4.4 Multidimensional LC Approaches for Protein Biopharmaceuticals 64
1.4.5 Conclusion and Future Trends in Protein Biopharmaceuticals Analysis 66
References 67
1.5 Optimization Strategies in HPLC for the Separation of Biomolecules73
Lisa Strasser, Florian Füssl, and Jonathan Bones
1.5.1 Optimizing a Chromatographic Separation 73
1.5.2 Optimizing the Speed of an HPLC Method 77
1.5.3 Optimizing the Sensitivity of an HPLC Method 79
1.5.4 Multidimensional Separations (See also Chapter 1.1) 80
1.5.5 Considerations for MS Detection (See also Chapter 1.3) 81
1.5.6 Conclusions and Future Prospects 83
References 84
1.6 Optimization Strategies in Packed-Column Supercritical Fluid Chromatography (SFC)87
Caroline West
1.6.1 Selecting a Stationary Phase Allowing for Adequate Retention and Desired Selectivity 88
1.6.1.1 Selecting a Stationary Phase for Chiral Separations 88
1.6.1.2 Selecting a Stationary Phase for Achiral Separations 90
1.6.2 Optimizing Mobile Phase to Elute all Analytes 93
1.6.2.1 Nature of the Cosolvent 93
1.6.2.2 Proportion of Cosolvent 94
1.6.2.3 Use of Additives 96
1.6.2.4 Sample Diluent 97
1.6.3 Optimizing Temperature, Pressure, and Flow Rate 97
1.6.3.1 Understanding the Effects of Temperature, Pressure, and Flow Rate on your Chromatograms 97
1.6.3.2 Optimizing Temperature, Pressure, and Flow Rate Concomitantly 99
1.6.4 Considerations on SFCMS Coupling 100
1.6.5 Summary of Method Optimization 101
1.6.6 SFC as a Second Dimension in Two-Dimensional Chromatography 102
1.6.7 Further Reading 102
References 103
1.7 Strategies for Enantioselective (Chiral) Separations107
Markus Juza
1.7.1 How to Start? 108
1.7.2 Particle Size 109
1.7.3 Chiral Polysaccharide Stationary Phases as First Choice 110
1.7.4 Screening Coated and Immobilized Polysaccharide CSPs in Normal-Phase and Polar Organic Mode 113
1.7.5 Screening Coated and Immobilized Polysaccharide CSPs in Reversed-Phase Mode 116
1.7.6 Screening Immobilized Polysaccharide CSPs in Medium-Polarity Mode 119
1.7.7 Screening Coated and Immobilized Polysaccharide CSPs under Polar Organic Supercritical Fluid Chromatography Conditions 120
1.7.8 Screening Immobilized Polysaccharide CSPs in Medium-Polarity Supercritical Fluid Chromatography Conditions 125
1.7.9 SFC First? 127
1.7.10 Are There Rules for Predicting Which CSP Is Suited for My Separation Problem? 127
1.7.11 Which Are the Most Promising Polysaccharide CSPs? 127
1.7.12 Are some CSPs Comparable? 129
1.7.13 No-Gos, Pitfalls, and Peculiarities in Chiral HPLC and SFC 132
1.7.14 Gradients in Chiral Chromatography 133
1.7.15 Alternative Strategies to Chiral HPLC and SFC on Polysaccharide CSPs 133
1.7.16 How Can I Solve Enantiomer Separation Problems Without Going to the Laboratory? 135
1.7.17 The Future of Chiral Separations Fast Chiral Separations (cUHPLC and cSFC)? 136
References 138
1.8 Optimization Strategies Based on the Structure of the Analytes141
Christoph A. Fleckenstein
1.8.1 Introduction 141
1.8.2 The Impact of Functional Moieties 142
1.8.3 Hydrogen Bonds 143
1.8.4 Influence ofWater Solubility by Hydrate Formation of Aldehydes and Ketones 146
1.8.5 Does Polar Equal Hydrophilic? 148
1.8.6 Peroxide Formation of Ethers 150
1.8.7 The pH Value in HPLC 151
1.8.7.1 Acidic Functional Groups 152
1.8.7.2 Basic Functional Groups 153
1.8.8 General Assessment and Estimation of Solubility of Complex Molecules 155
1.8.9 OctanolWater Coefficient 157
1.8.10 Hansen Solubility Parameters 160
1.8.11 Conclusion and Outlook 162
Acknowledgments 163
References 163
1.9 Optimization Opportunities in a Regulated Environment165
Stavros Kromidas
1.9.1 Introduction 165
1.9.2 Preliminary Remark 165
1.9.3 Resolution 167
1.9.3.1 Hardware Changes 167
1.9.3.1.1 Preliminary Remark 167
1.9.3.1.2 UHPLC Systems 168
1.9.3.1.3 Column Oven 168
1.9.3.2 Improving the Peak Shape 169
1.9.4 Peak-to-Noise Ratio 171
1.9.4.1 Noise Reduction 171
1.9.5 Coefficient of Variation, VC (Relative Standard Deviation, RSD) 171
References 176
Part II Computer-aided Optimization177
2.1 Strategy for Automated Development of Reversed-Phase HPLC Methods for Domain-Specific Characterization of Monoclonal Antibodies179
Jennifer La, Mark Condina, Leexin Chong, Craig Kyngdon, Matthias Zimmermann, and Sergey Galushko
2.1.1 Introduction 179
2.1.2 Interaction with Instruments 181
2.1.3 Columns 182
2.1.4 Sample Preparation and HPLC Analysis 183
2.1.5 Automated Method Development 184
2.1.5.1 Columns Screening 185
2.1.5.2 Rapid Optimization 186
2.1.5.3 Fine Optimization and Sample Profiling 188
2.1.6 Robustness Tests 188
2.1.6.1 Selection of the Variables 189
2.1.6.2 Selection of the experimental design 190
2.1.6.3 Definition of the Different Levels for the Factors 191
2.1.6.4 Creation of the Experimental Set-up 191
2.1.6.5 Execution of Experiments 192
2.1.6.6 Calculation of Effects and Response and Numerical and Graphical Analysis of the Effects 192
2.1.6.7 Improving the Performance of the Method 194
2.1.7 Conclusions 196
References 196
2.2 Fusion QbD® Software Implementation of APLM Best Practices for Analytical Method Development, Validation, and Transfer199
Richard Verseput
2.2.1 Introduction 199
2.2.1.1 Application to Chromatographic Separation Modes 200
2.2.1.2 Small- and Large-Molecule Applications 200
2.2.1.3 Use for Non-LC Method Development Procedures 200
2.2.2 Overview Experimental Design and Data Modeling in Fusion QbD 201
2.2.3 Analytical Target Profile 201
2.2.4 APLM Stage 1 Procedure Design and Development 202
2.2.4.1 Initial SampleWorkup 202
2.2.5 Chemistry System Screening 204
2.2.5.1 Starting Points Based on Molecular Structure and Chemistry Considerations 205
2.2.5.2 Trend Responses and Data Modeling 205
2.2.6 Method Optimization 207
2.2.6.1 Optimizing Mean Performance 207
2.2.6.2 Optimizing Robustness In Silico Monte Carlo Simulation 210
2.2.6.3 A FewWords About Segmented (Multistep) Gradients and Robustness 213
2.2.7 APLM Stage 2 Procedure Performance Verification 214
2.2.7.1 Replication Strategy 214
2.2.8 The USP<1210>Tolerance Interval in Support of Method Transfer 214
2.2.9 What is Coming Expectations for 2021 and Beyond 216
References 217
Part III Current Challenges for HPLC Users in Industry219
3.1 Modern HPLC Method Development221
Stefan Lamotte
3.1.1 Robust Approaches to Practice 222
3.1.1.1 Generic Systems for all Tasks 222
3.1.2 The Classic Reverse-phase System 225
3.1.3 A System that Primarily Separates According to Interactions 227
3.1.4 A system that Primarily Separates According to Cation Exchange and Hydrogen Bridge Bonding Selectivity 227
3.1.5 System for Nonpolar Analytes 228
3.1.6 System for Polar Analytes 228
3.1.7 Conclusion 230
3.1.8 The Maximum Peak Capacity 230
3.1.9 Outlook 231
References 231
3.2 Optimization Strategies in HPLC from the Perspective of an Industrial Service Provider233
Juri Leonhardt and Michael Haustein
3.2.1 Introduction 233
3.2.2 Research and Development 233
3.2.3 Quality Control 234
3.2.4 Process Control Analytics 235
3.2.5 Decision Tree for the Optimization Strategy Depending on the Final Application Field 237
3.3 Optimization Strategies in HPLC from the Perspective of a Service Provider The UNTIE® Process of the CUP Laboratories239
Dirk Freitag-Stechl and Melanie Janich
3.3.1 Common Challenges for a Service Provider 239
3.3.2 A Typical, Lengthy Project How it Usually Goes and How it Should not be Done! 239
3.3.3 How DoWe Make It Better? - The UNTIE® Process of the CUP Laboratories 241
3.3.4 Understanding Customer Needs 241
3.3.5 The Test of an Existing Method 242
3.3.6 Method Development and Optimization 243
3.3.7 Execution of the Validation 245
3.3.8 Summary 248
Acknowledgments 249
References 249
3.4 Optimization Strategies in HPLC251
Bernard Burn
3.4.1 Definition of the Task 252
3.4.2 Relevant Data for the HPLC Analysis of a Substance (see also Chapter 1.8) 252
3.4.2.1 Solubility 252
3.4.2.2 Acidity Constants (pKa) 257
3.4.2.2.1 Polarity of Acidic or Alkaline Substances (see also Chapter 1.8) 257
3.4.2.2.2 UV Spectra 259
3.4.2.2.3 Influence on the Peak Shape 259
3.4.2.2.4 Acid Constant Estimation 263
3.4.2.3 OctanolWater Partition Coefficient 263
3.4.2.4 UV Absorption 270
3.4.2.5 Stability of the Dissolved Analyte 272
3.4.3 Generic Methods 278
3.4.3.1 General Method for the Analysis of Active Pharmaceutical Ingredients 278
3.4.3.2 Extensions of the Range of Application 279
3.4.3.3 Limits of this General Method 279
3.4.3.4 Example, Determination of Butamirate Dihydrogen Citrate in a Cough Syrup 279
3.4.3.4.1 Basic Data 279
3.4.3.4.2 Expected Difficulties 279
3.4.3.4.3 HPLC Method 279
3.4.3.4.4 Example Chromatogram 279
3.4.4 General Tips for Optimizing HPLC Methods 279
3.4.4.1 Production of Mobile Phases 284
3.4.4.1.1 Reagents 284
3.4.4.1.2 Vessels and Bottles 285
3.4.4.1.3 Measurement of Reagents and Solvent 285
3.4.4.1.4 Preparation of Buffer Solutions 286
3.4.4.1.5 Filtration of Solvents and Buffer 286
3.4.4.1.6 Degassing of Mobile Phases 287
3.4.4.2 Blank Samples 287
3.4.4.3 Defining MeasurementWavelengths for UV Detection 288
3.4.4.4 UV Detection at LowWavelengths 288
3.4.4.4.1 Solvents 291
3.4.4.4.2 Acids and Buffer Additives 292
3.4.4.4.3 Drift at Solvent Gradients 294
3.4.4.5 Avoidance of Peak Tailing 295
3.4.4.6 Measurement Uncertainty and Method Design 302
3.4.4.6.1 Weighing in or Measuring 302
3.4.4.6.2 Dilutions 303
3.4.4.6.3 HPLC Analysis 304
3.4.4.6.4 Internal Standards 305
3.4.4.7 Column Dimension and Particle Sizes 305
Reference 309
Part IV Current Challenges for HPLC Equipment Suppliers311
4.1 Optimization Strategies with your HPLC Agilent Technologies313
Jens Trafkowski
4.1.1 Increase the Absolute Separation Performance: Zero Dead-Volume Fittings 314
4.1.2 Separation Performance: Minimizing the Dispersion 314
4.1.3 Increasing the Throughput DifferentWays to Lower the Turnaround Time 316
4.1.4 Minimum Carryover for Trace Analysis: Multiwash 317
4.1.5 Increase the Performance of What you have got Modular or Stepwise Upgrade of Existing Systems 318
4.1.6 Increase Automation, Ease of Use, and Reproducibility with the Features of a High-End Quaternary UHPLC Pump 319
4.1.7 Increase Automation: Let your Autosampler do the Job 321
4.1.8 Use Your System for Multiple Purposes: Multimethod and Method Development Systems 321
4.1.9 Combine Sample Preparation with LC Analysis: Online SPE 322
4.1.10 Boost Performance with a Second Chromatographic Dimension: 2D-LC (see also Chapter 1.1) 323
4.1.11 Think Different,Work with Supercritical CO2 as Eluent: SFC Supercritical Fluid Chromatography (see also Chapter 1.6) 324
4.1.12 Determine Different Concentration Ranges in One System: High-Definition Range (HDR) HPLC 325
4.1.13 Automize Even Your Method Transfer from other LC Systems: Intelligent System Emulation Technology (ISET) 326
4.1.14 Conclusion 327
References 328
4.2 To Empower the Customer Optimization Through Individualization329
Kristin Folmert and Kathryn Monks
4.2.1 Introduction 329
4.2.2 Define Your Own Requirements 329
4.2.2.1 Specification Sheet, Timetable, or Catalogue of Measures 329
4.2.2.2 Personnel Optimization Helps to make Better Use of HPLC 331
4.2.2.3 Mastering Time-Consuming Method Optimizations in a Planned Manner 332
4.2.2.4 Optimizations at Device Level do not Always have to Mean an Investment 332
4.2.3 An Assistant Opens Up Many New Possibilities 333
4.2.3.1 If the HPLC System must Simply be able to do more in the Future 333
4.2.3.2 Individual Optimizations with an Assistant 333
4.2.3.3 Automatic Method Optimization and Column Screening 334
4.2.3.4 A New Perspective at Fractionation, Sample Preparation, and Peak Recycling 335
4.2.3.5 Continuous Chromatography, a New Level of Purification 336
4.2.4 The Used Materials in the Focus of the Optimization 337
4.2.4.1 Wetted vs. Dry Components of the HPLC 337
4.2.4.2 Chemical Resistance ofWetted Components 338
4.2.4.3 Bioinert Components 340
4.2.4.3.1 Material Certification 340
4.2.5 Software Optimization Requires Open-Mindedness 340
4.2.6 Outlook 341
4.3 (U)HPLC Basics and Beyond343
Gesa Schad, Brigitte Bollig, and Kyoko Watanabe
4.3.1 An Evaluation of (U)HPLC-operating Parameters and their Effect on Chromatographic Performance 343
4.3.1.1 Compressibility Settings 343
4.3.1.2 Solvent Composition and Injection Volume 346
4.3.1.3 Photodiode Array Detector: Slit Width 348
4.3.2 Analytical Intelligence AI, M2M, IoT How Modern Technology can Simplify the Lab Routine 349
4.3.2.1 Auto-Diagnostics and Auto-Recovery to Maximize Reliability and Uptime 349
4.3.2.2 Advanced Peak Processing to Improve Resolution 350
4.3.2.3 Predictive Maintenance to Minimize System Downtime 353
References 354
4.4 Addressing Analytical Challenges in a Modern HPLC Laboratory355
Frank Steiner and Soo Hyun Park
4.4.1 Vanquish Core, Flex, and Horizon Three Different Tiers, all Dedicated to Specific Requirements 356
4.4.2 Intelligent and Self-Contained HPLC Devices 362
4.4.3 2D-LC for Analyzing Complex Samples and Further Automation Capabilities (see also Chapter 1.1) 363
4.4.3.1 Loop-based Single-Heart-Cut 2D-LC 364
4.4.3.2 Loop-based Multi-Heart-Cut 2D-LC 364
4.4.3.3 Trap-based Single-Heart-Cut 2D-LC for Eluent Strength Reduction 366
4.4.3.4 Trap-based Single-Heart-Cut 2D LCMS Using Vanquish Dual Split Sampler 367
4.4.4 Software-Assisted Automated Method Development 368
Abbreviations 374
References 374
4.5 Systematic Method Development with an Analytical Quality-by-Design Approach Supported by Fusion QbD and UPLCMS375
Falk-Thilo Ferse, Detlev Kurth, Tran N. Pham, Fadi L. Alkhateeb, and Paul Rainville
References 384
Index 385
