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Computational Pharmaceutical Solid State Chemistry

ISBN: 978-1-119-22919-3
424 pages
May 2016
Computational Pharmaceutical Solid State Chemistry (1119229197) cover image

Description

This book is the first to combine computational material science and modeling of molecular solid states for pharmaceutical industry applications.

•    Provides descriptive and applied state-of-the-art computational approaches and workflows  to guide pharmaceutical solid state chemistry experiments and to support/troubleshoot API solid state selection
•    Includes real industrial case examples related to application of modeling methods in problem solving
•    Useful as a supplementary reference/text for undergraduate, graduate and postgraduate students in computational chemistry, pharmaceutical and biotech sciences, and materials science
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Table of Contents

List of Contributors xiii

Preface xvii

Editor’s biography xix

1 Computational Pharmaceutical Solid‐State Chemistry: An Introduction 1
Yuriy A. Abramov

1.1 Introduction 1

1.2 Pharmaceutical Solid‐State Landscape 2

1.2.1 Some Definitions 2

1.2.2 Impact of Solid‐State Form on API and Product Properties 4

1.2.3 Challenges of Pharmaceutical Industry Related to Solid Form Selection 6

1.3 Pharmaceutical Computational Solid‐State Chemistry 8

1.4 Conclusions 9

Acknowledgment 10

References 10

2 Navigating the Solid Form Landscape with Structural Informatics 15
Peter T. A. Galek, Elna Pidcock, Peter A. Wood, Neil Feeder, and Frank H. Allen

2.1 Introduction 15

2.2 The Csd System 17

2.3 Hydrogen‐Bond Propensity: Theory and Applications to Polymorphism 18

2.3.1 Methodology 18

2.3.2 Case Study 1: Ritonavir 19

2.4 Hydrogen‐Bond Landscapes: Developing the Propensity Approach 21

2.4.1 Methodology 21

2.4.2 Case Study 2: Metastable versus Stable Form of Piroxicam 22

2.4.3 Case Study 3: Exploring the Likely Hydrogen‐Bond Landscape of Axitinib (Inlyta®) 25

2.5 Informatics‐Based Cocrystal Screening 25

2.5.1 Methodology 25

2.5.2 Case Study 4: Paracetamol 26

2.5.3 Case Study 5: AMG 517 – Sorbic Acid Cocrystal 29

2.6 Conclusions and Outlook 32

References 33

3 Theoretical Hydrogen‐Bonding Analysis for Assessment of Physical Stability of Pharmaceutical Solid Forms 37
Yuriy A. Abramov

3.1 Introduction 37

3.2 Experimental Scales of H‐Bonding Basicity and Acidity 39

3.2.1 In Solution Phase 39

3.2.2 In Solid‐State Phase 40

3.3 Theoretical Study of H‐Bonding Strength in Solution and in Solid State 40

3.3.1 Supermolecular Approach 41

3.3.2 Descriptor‐Based Approaches 41

3.3.3 Solid‐State H‐bonding Strength 42

3.4 Application to Solid Form Selection 47

3.4.1 Examples of Theoretical H‐Bonding Analysis to Support Solid Form Selection 48

3.4.2 Consideration of Limitations of Hydrogen‐Bonding Propensity Approach 50

3.5 Conclusion 52

Acknowledgment 53

References 53

4 Improving Force Field Parameters for Small‐Molecule Conformation Generation 57
Dmitry Lupyan, Yuriy A. Abramov, and Woody Sherman

4.1 Introduction 57

4.2 Methods 62

4.3 Results and Discussion 66

4.3.1 Close S⋯O Interactions 66

4.3.2 Halogen X⋯O Interactions 75

4.3.3 Generalization of the Approach to Other Interactions 77

4.3.4 An Improved OPLS Force Field (OPLS2) 80

4.4 Conclusion 81

References 82

5 Advances in Crystal Structure Prediction and Applications to Pharmaceutical Materials 87
Graeme M. Day

5.1 Introduction 87

5.1.1 Motivation 88

5.2 Crystal Structure Prediction Methodologies 89

5.2.1 Molecular Geometry 89

5.2.2 Crystal Structure Searching 99

5.2.3 Structure Ranking 102

5.3 Applications of Crystal Structure Prediction 105

5.3.1 Crystal Structure Determination 106

5.3.2 Solid Form Screening 108

5.4 Summary 110

References 110

6 Integrating Computational Materials Science Tools in Form and Formulation Design 117
Joseph F. Krzyzaniak, Paul A. Meenan, Cheryl L. Doherty, Klimentina Pencheva, Suman Luthra, and Aurora Cruz‐Cabeza

6.1 Introduction 117

6.2 From Molecule to Crystal Structure 119

6.2.1 Single Crystal Structure 120

6.2.2 Structural Analysis 120

6.2.3 Molecular Packing and HB Geometry Analyses 122

6.2.4 Full Interaction Maps 123

6.2.5 Crystal Structure Prediction 124

6.3 From Crystals to Particles 131

6.4 From Particles to Dosage Forms 134

6.4.1 Structural Investigation of Crystal Surfaces and Structure Dehydration 137

6.4.2 Structural Investigations of Crystal Surfaces and Chemical Stability 139

6.5 Conclusion 141

Acknowledgments 142

References 142

7 Current Computational Approaches at Astrazeneca for Solid‐State and Property Predictions 145
Sten O. Nilsson Lill, Staffan Schantz, Viktor Broo, and Anders Broo

7.1 Introduction 145

7.2 Polymorphism 146

7.3 Conformer Search 157

7.4 Molecular Perturbations to Achieve Solubility for Gpr119 Ligands 158

7.5 Solid‐State Nuclear Magnetic Resonance and Azd8329 Case Study 163

7.6 Ccdc Tools 168

7.7 Tautomerism 169

7.8 Conclusions 170

Acknowledgments 170

References 170

8 Synthonic Engineering: From Molecular and Crystallographic Structure to the Rational Design of Pharmaceutical Solid Dosage Forms 175
Kevin J. Roberts, Robert B. Hammond, Vasuki Ramachandran, and Robert Docherty

8.1 Introduction 175

8.2 The Crystal 177

8.2.1 Crystallography 177

8.2.2 Crystal Chemistry and Crystal Packing of Drug Molecules 179

8.2.3 Deconstructing the Supra‐Molecular Interactions in Bulk – Intrinsic Synthons 181

8.3 Morphology and Surface Structure 185

8.3.1 Nucleation and the Crystal Growth Process 185

8.3.2 Particle Morphology and Surface Structure 186

8.3.3 Crystal Morphology Prediction 188

8.3.4 Deconstructing the Supra‐Molecular Interactions at Surfaces – Extrinsic Synthons 190

8.3.5 Grid Searching – Probing Inter‐molecular Interactions at Surfaces and Environments 190

8.4 The Crystallisation Perspective 191

8.4.1 Nucleation, Surface Energies and Directed Polymorphism 191

8.4.2 The Impact of Solvent on Morphology 194

8.4.3 The Impact of Impurities on Morphology 196

8.5 The Drug Product Perspective 197

8.5.1 Excipient Compatibility 197

8.5.2 Inhaled Drug Delivery Design 199

8.5.3 Mechanical Properties 201

8.5.4 Dissolution 203

8.6 Summary and Future Outlook: Synthonic Engineering Particle Passport and the Future of the Drug Product Design 205

Acknowledgements 207

References 207

9 New Developments in Prediction of Solid‐State Solubility and Cocrystallization Using Cosmo‐Rs Theory 211
Christoph Loschen and Andreas Klamt

9.1 Introduction 211

9.2 Cosmo‐Rs 212

9.3 Prediction of Drug Solubility Using Cosmo‐Rs 215

9.4 Solubility Prediction with Multiple Reference Solvents 218

9.5 Melting Point and Fusion Enthalpy Qspr Models 221

9.6 Cocrystal Screening 225

9.7 Solvate Formation 229

9.8 Summary 231

References 231

10 Modeling and Prediction of Solid Solubility by Ge Models 235
Larissa P. Cunico, Anjan K. Tula, Roberta Ceriani, and Rafiqul Gani

10.1 Introduction 235

10.2 Framework 236

10.2.1 Thermodynamic Basis 238

10.2.2 The Necessary Property‐Related Information for Solid Solubility Prediction and the Developed Databases 238

10.2.3 SLE Thermodynamic Consistency Tests 241

10.2.4 SolventPro 252

10.3 Conclusion 259

References 260

11 Molecular Simulation Methods to Compute Intrinsic Aqueous Solubility of Crystalline Drug‐Like Molecules 263
David S. Palmer and Maxim V. Fedorov

11.1 Introduction 263

11.2 Definitions of Solubility 264

11.3 Solubility and Thermodynamics 264

11.3.1 Solubility and Free Energy of Solution 264

11.3.2 Computation of Solubility from the Thermodynamic Cycle of Solid to Supercooled Liquid to

Aqueous Solution 265

11.3.3 Computation of Solubility from the Thermodynamic Cycle of Solid to Gas Phase to Aqueous Solution 267

11.4 Calculation of ΔGhyd 269

11.4.1 Implicit Continuum Solvent Models 270

11.4.2 Explicit Solvent Models: Atomistic Simulations 270

11.4.3 Explicit Solvent Models: Molecular Theories of Liquids 271

11.5 Calculation of ΔGsub 275

11.5.1 Crystal Polymorphism 275

11.5.2 Crystal Structure Prediction 275

11.5.3 Calculation of ΔGsub 276

11.5.4 Calculation of ΔHsub 276

11.5.5 Calculation of ΔSsub 277

11.5.6 Other Methods to Compute ΔGsub 278

11.6 Experimental Data 279

11.7 Conclusion and Future Outlook 280

Acknowledgments 280

References 280

12 Calculation of Nmr Tensors: Application to Small‐Molecule Pharmaceutical Solids 287
Luís Mafra, Sérgio Santos, Mariana Sardo, and Heather Frericks Schmidt

12.1 Ssnmr Spectroscopy: A Short Introduction 287

12.2 The Chemical Shielding Tensors: Fundamentals 288

12.3 Computational Approaches to the Calculation of Chemical Shift Tensors in Solids 290

12.3.1 Cluster Approach 290

12.3.2 Periodic Approach 291

12.3.3 Pitfalls and Practical Considerations 292

12.4 NICS 294

12.5 Case Studies Combining Experimental and Computational Nmr Methods 294

12.5.1 N MR Assignment of Polymorphs Aided by Computing NMR Parameters 295

12.5.2 Calculated vs Experimental Chemical Shift Tensors Using Different NMR Methods 302

12.5.3 Studying Crystal Packing Interactions 312

12.5.4 Employing Chemical Shifts for Crystal Structure Elucidation/Determination 315

12.6 Summary 325

References 326

13 Molecular Dynamics Simulations of Amorphous Systems 331
Bradley D. Anderson and Tian‐Xiang Xiang

13.1 Introduction 331

13.2 Md Simulation Methodology 332

13.3 Polymer Properties—Md Simulation Versus Experiment 334

13.3.1 Glass Transition Temperature (Tg) 334

13.3.2 Amorphous Structure and Dynamics 337

13.4 Hydrogen Bonding Patterns, Water Uptake, and Distribution in Amorphous Solids 342

13.4.1 Poly(d,l)lactide 343

13.4.2 Polyvinylpyrrolidone 345

13.4.3 Hydroxypropylmethylcellulose Acetate Succinate (HPMCAS) 347

13.4.4 Amorphous Indomethacin 350

13.5 Amorphous Drug–Polymer Blends 354

13.5.1 Molecular Interactions Probed by MD Simulation 354

13.5.2 Solubility and Miscibility Prediction 357

13.5.3 Molecular Mobility and Small‐Molecule Diffusion in Amorphous Dispersions 361

13.5.4 Plasticization by Water Clusters 365

13.6 Summary 367

References 368

14 Numerical Simulations of Unit Operations in Pharmaceutical Solid Dose Manufacturing 375
Ekneet Kaur Sahni, Shivangi Naik, and Bodhisattwa Chaudhuri

14.1 Introduction 375

14.2 Numerical Method 376

14.2.1 Contact Drying in an Agitated Filter Dryer 376

14.2.2 Coating in a Conventional Pan Coater 378

14.2.3 Modeling of milling in a Wiley Mill 379

14.3 Experimental Method for Milling 380

14.4 Results and Discussion 380

14.4.1 Simulation of Contact Drying 380

14.4.2 Simulation of Tablet Coating 384

14.4.3 Simulation of Size Fragmentation (Milling) 387

14.5 Summary and Conclusions 391

References 392

Index 395

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Author Information

Yuriy A. Abramov, PhD, is a Senior Principal Scientist with over 14 years of experience in computational sciences in drug discovery and development with Pfizer, Inc., in Groton, CT, USA. He holds a PhD in Physical Chemistry from the D. Mendeleev University of Chemical Technology of Russia and Karpov Institute of Physical Chemistry in Moscow.
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