Crystallization of Organic Compounds E-Book

Hsien-Hsin Tung

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 701

Veröffentlichungsjahr: 2023

Beschreibung

Crystallization of Organic Compounds Practical resource covering applications of crystallization principles with methodologies, case studies, and numerous industrial examples for emphasis Based on the authors' hands-on experiences as process engineers, through the use of case studies and examples of crystallization processes, ranging from laboratory development through manufacturing scale-up, Crystallization of Organic Compounds guides readers through the practical applications of crystallization and emphasizes strategies that have proven to be successful, enabling readers to avoid common pitfalls that can render standard procedures unsuccessful. Most chapters feature multiple examples that guide readers, step by step, through the crystallization of active pharmaceutical ingredients (APIs), including an analysis of the major methods of carrying out crystallization operations, their strengths and potential issues, as well as numerous examples of crystallization processes from development through manufacturing scale. Advancements in the field of crystallization have been integrated throughout the book in the newly revised Second Edition to ensure the content adequately reflects current state-of-the-art industrial know-hows and practice. The new edition also adds chapters addressing downstream operations after the crystallization, including filtration/washing and drying, together with industrial use cases. Crystallization of Organic Compounds includes detailed information on: * Solubility and solid behavior, covering phase rule, polymorph, salt/co-crystal, chiral resolution and in-silico solubility prediction; and kinetics, covering seed, supersaturation, nucleation, crystal growth and model-based experimental design * Critical issues in the crystallization practice, covering oiling out, seeding/wet-milling, agglomeration/aggregation, mixing scale-up and quality-by-design principles * Cooling, anti-solvent, evaporation and reactive crystallization process design, covering batch and continuous operations with industrial examples * Special applications, covering crystallization with ultrasound, reaction selectivity enhancement, and computation fluid dynamics, and solid dispersion With highly practical coverage of the subject, Crystallization of Organic Compounds is an essential resource for engineers and chemists involved with the development, scaling, or operation of crystallization process in the pharmaceutical and fine chemical industries, particularly those with degrees in chemical engineering and chemistry.

Leseprobe

Table of Contents

Cover

Title Page

Copyright Page

Preface

Chapter 1: Introduction to Crystallization

1.1 CRYSTAL PROPERTIES AND POLYMORPHS (CHAPTERS 2 AND 3)

1.2 NUCLEATION AND GROWTH KINETICS (CHAPTER 4)

1.3 MIXING AND SCALE‐UP (CHAPTER 5)

1.4 CRITICAL ISSUES AND QUALITY BY DESIGN (CHAPTER 6)

1.5 CRYSTALLIZATION PROCESS OPTIONS (CHAPTERS 7–10)

1.6 DOWNSTREAM OPERATIONS (CHAPTERS 11 AND 12)

1.7 SPECIAL APPLICATIONS (CHAPTER 13)

Chapter 2: Properties

2.1 SOLUBILITY

2.2 SUPERSATURATION, METASTABLE ZONE, AND INDUCTION TIME

2.3 OIL, AMORPHOUS, AND CRYSTALLINE STATES

2.4 POLYMORPHISM

2.5 SOLVATE

2.6 SOLID COMPOUND, SOLID SOLUTION, AND SOLID MIXTURE

2.7 INCLUSION AND OCCLUSION

2.8 ADSORPTION, HYGROSCOPICITY, AND DELIQUESCE

2.9 CRYSTAL MORPHOLOGY

2.10 PARTICAL SIZE DISTRIBUTION AND SURFACE AREA

Chapter 3: Polymorphism

3.1 PHASE RULE

3.2 PHASE TRANSITION

3.3 PREDICTION OF CRYSTAL STRUCTURE AND ITS FORMATION

3.4 SELECTION AND SCREENING OF CRYSTAL FORMS

3.5 EXAMPLES

Chapter 4: Kinetics

4.1 SUPERSATURATION AND RATE PROCESSES

4.2 NUCLEATION

4.3 CRYSTAL GROWTH AND AGGLOMERATION

4.4 NUCLEATE/SEED AGING AND OSTWALD RIPENING

4.5 DELIVERED PRODUCT: PURITY, CYSTAL FORM, SIZE AND MORPHOLOGY, AND CHEMICAL AND PHYSICAL STABILITY

4.6 DESIGN OF EXPERIMENT (DOE)—MODEL‐BASED APPROACH

4.7 MODEL‐FREE FEEDBACK CONTROL

Chapter 5: Mixing and Crystallization

5.1 INTRODUCTION

5.2 MIXING CONSIDERATIONS AND FACTORS

5.3 MIXING EFFECTS ON NUCLEATION

5.4 MIXING EFFECTS ON CRYSTAL GROWTH

5.5 MIXING DISTRIBUTION AND SCALE‐UP

5.6 CRYSTALLIZATION EQUIPMENT

5.7 PROCESS DESIGN AND EXAMPLES

Chapter 6: Critical Issues and Quality by Design

6.1 QUALITY BY DESIGN

6.2 BASIC PROPERTIES

6.3 SEED

6.4 SUPERSATURATION

6.5 MIXING AND SCALE—SELECTION OF EQUIPMENT AND OPERATING PROCEDURES

6.6 STRATEGIC CONSIDERATIONS FOR CRYSTALLIZATION PROCESS DEVELOPMENT

6.7 SUMMARY OF CRITICAL ISSUES

Chapter 7: Cooling Crystallization

7.1 BATCH OPERATION

7.2 CONTINUOUS OPERATIONS

7.3 PROCESS DESIGN—EXAMPLES

Chapter 8: Evaporative Crystallization

8.1 INTRODUCTION

8.2 SOLUBILITY DIAGRAMS

8.3 FACTORS AFFECTING NUCLEATION AND GROWTH

8.4 SCALE‐UP

8.5 EQUIPMENT

8.6 PROCESS DESIGN AND EXAMPLES

Chapter 9: Anti‐solvent Crystallization

9.1 OPERATION

9.2 IN‐LINE MIXING CRYSTALLIZATION

9.3 PROCESS DESIGN AND EXAMPLES

Chapter 10: Reactive Crystallization

10.1 INTRODUCTION

10.2 CONTROL OF PARTICLE SIZE

10.3 KEY ISSUES IN ORGANIC REACTIVE CRYSTALLIZATION

10.4 CREATION OF FINE PARTICLES—IN‐LINE REACTIVE CRYSTALLIZATION

10.5 PROCESS DESIGN AND SCALE‐UP

Chapter 11: Filtration

11.1 INTRODUCTION

11.2 BASIC PROPERTIES

11.3 KINETICS

11.4 PROCESS DESIGN AND SCALE‐UP

Chapter 12: Drying

12.1 INTRODUCTION

12.2 BASIC PROPERTIES

12.3 KINETICS

12.4 PROCESS DESIGN AND SCALE‐UP

Chapter 13: Special Applications

13.1 INTRODUCTION

13.2 CRYSTALLIZATION WITH SUPERCRITICAL FLUIDS

13.3 RESOLUTION OF STEREO‐ISOMERS

13.4 WET MILLS IN CRYSTALLIZATION

13.5 COMPUTATIONAL FLUID DYNAMICS IN CRYSTALLIZATION

13.6 SOLID DISPERSION—CRYSTALLINE AND/OR AMORPHOUS DRUGS

13.7 PROCESS DESIGN AND EXAMPLES

References

Index

End User License Agreement

List of Tables

Chapter 3

Table 3.1 Difference of lattice energy and solubility among polymorphs and ...

Table 3.2 A partial list of acid counterion candidates for salt screening....

Table 3.3 A partial list of base counterion candidates for salt screening....

Table 3.4 A partial list of amino acid counterion candidates for salt scree...

Table 3.5 A partial list of coformer candidates for co‐crystal screening.

Table 3.6 Solubility (mg/ml) of Indomethacin Forms I, II, and III in aqueou...

Table 3.7 Solubility of sulindac Forms I and II in ethyl acetate.

Table 3.8 Dissolution of sulindac Forms I and II in 29.3%

n

‐propanol‐water....

Table 3.9 Hygroscopicity study with HCl salt of Example 3.6 at room tempera...

Table 3.10 Solubility study in water with HCl salt of Example 3.6.

Chapter 4

Table 4.1 First‐order growth rate constants (fluidized bed versus CSTR crys...

Table 4.2 Crystal form conversion time with and without high shear.

Table 4.3 Effect of extent of seed or initial nucleation on final crystal p...

Table 4.4 Nucleation and crystal growth rate in different solvent systems....

Chapter 5

Table 5.1 Mixing in crystallizers for pharmaceutical processes.

Table 5.2 Mixing intensity landscape of different methods.

Table 5.3 Glass‐lined impellers and their methods of attachment.

Table 5.4 Recommended minimum

V

f

/V

t

for selected geometries for turbulent f...

Table 5.5 Particle size data among different commercial sites.

Table 5.6 Comparison of mixing indexes among factories.

Chapter 6

Table 6.1 Characteristics of generation of supersaturation.

Chapter 7

Table 7.1 Experimental conditions and results of crystallization.

Table 7.2 Solubility of the R

/

S‐Ibuprofen‐S‐Lysine in ethanol

/

water 97

/

3 so...

Table 7.3 Results of resolution of Ibuprofen lysinate.

Table 7.4 Experimental conditions and results of polymorphs.

Table 7.5 First‐order growth rate constants (fluidized bed versus CSTR crys...

Table 7.6 Rate constants for crystal breakage (slurry concentration).

Chapter 8

Table 8.1 Comparison of process options.

Chapter 9

Table 9.1 Conditions and results of slurry and crystallization experiments....

Table 9.2 Modification of antisolvent addition.

Table 9.3 Input and output variable for design of experiments.

Table 9.4 Impact of solvent ratio, temperature, and concentration on produc...

Table 9.5 “DFP” plasma level.

Chapter 10

Table 10.1 Impact of experimental conditions on residual solvent in the cak...

Table 10.2 Comparison of performance between original and modified process....

Chapter 11

Table 11.1 Types of material used as filter medium.

Table 11.2 Filtration cake resistance ranking.

Table 11.3 Residual t‐BuOH and DMSO in the final API cake.

Table 11.4 Design of slurry/wash composition.

Table 11.5 Residual t‐BuOH and DMSO in the cake.

Chapter 12

Table 12.1 Brittleness index versus size reduction after hammer milling....

Table 12.2 Assessment of particle fracture and agglomeration tendency.

Table 12.3 Drying profile and particle behaviors during drying.

Table 12.4 Characteristics of different dryer.

Table 12.5 Residual acetone level in the laboratory investigation.

Chapter 13

Table 13.1 Experimental results of the original process versus the two‐filt...

Table 13.2 Freeze crystallization cycles (all acetone levels).

Table 13.3 Imipenem crystallinity and phase behavior of acetone

/

water.

Table 13.4 API crystallinity in ASD and hybrid solid dispersion.

List of Illustrations

Chapter 2

Figure 2.1 Free energy‐composition phase diagram.

Figure 2.2 Solubility of lovastatin in different solvent mixtures as a funct...

Figure 2.3 Solubility of lovastatin as a function of solvent composition.

Figure 2.4 Atypical solubility behavior reaching a maximum at a certain solv...

Figure 2.5 Impact of impurities on solubility.

Figure 2.6 Impact of chemical structure on the solubility of lovastatin (com...

Figure 2.7 NRTL‐SAC prediction of solubility for Lovastatin Simvastatin, Eto...

Figure 2.8 Comparison of predicted and measured Lovastatin solubility—predic...

Figure 2.9 Experimental glass transition temperature (

T

g

) profiles (left plo...

Figure 2.10 Solubility and metastable zone width.

Figure 2.11 Free energy‐composition phase diagram for metastable zone region...

Figure 2.12 Solution concentration profile during crystallization.

Figure 2.13 Expanded map on metastable zone width.

Figure 2.14 Formation of oil droplets of a highly supersaturated solution.

Figure 2.15 Formation of amorphous solid after aging of oil droplets.

Figure 2.16 Formation of crystalline solid.

Figure 2.17 (a) Solubility, miscibility, and

T

g

curves of solid dispersion. ...

Figure 2.18 Solubility curves of monotropic and enantiotropic polymorphs.

Figure 2.19 Solubility of form I and III polymorphs of a reverse transcripta...

Figure 2.20 Conversion of forms I and III mixture to form I after aging.

Figure 2.21 Solubility diagram of solvate and non‐solvate at different tempe...

Figure 2.22 Solubility of anhydrous solid and monohydrate of ibuprofen lysin...

Figure 2.23 Anhydrate versus monohydrate crystals of ibuprofen‐lysinate.

Figure 2.24 Phase diagram for the case of solid compound.

Figure 2.25 Phase diagram for the case of solid solution.

Figure 2.26 Solubilities of chemically similar APIs: lovastatin and simvasta...

Figure 2.27 Crystal cavity and crystal aggregates.

Figure 2.28 Adsorption of R‐ibu‐S‐Lys on S‐Ibu‐S‐lys.

Figure 2.29 Vapor–solid adsorption isotherm.

Figure 2.30 Residual ethanol level in the wet cake during drying.

Figure 2.31 Needle‐like, plate‐like, and cube‐like crystals.

Figure 2.32 Heat/cool/wet mill cycles for improvement of crystal aspect rati...

Figure 2.33 Particle size distribution functions,

Q

(

x

),

dQ

(

x

), and

q

(

x

).

Chapter 3

Figure 3.1 Crystal unit cell diagram, caffeine as model compound.

Figure 3.2 Caffeine molecule orientation in unit cell (looking down the

C

‐ax...

Figure 3.3 (a) and (b) Crystal energy landscape for isocaffeine (a) and caff...

Figure 3.4 Free energy profile as a function of nucleus/cluster size.

Figure 3.5 Energy barrier of

α

and

β

crystals

Figure 3.6 Nucleation rate of

α

and

β

crystals.

Figure 3.7 Hydrogen bonding network in crystal structure of co‐crystals.

Figure 3.8 Degradation pathway of Ritonavir—the ester bond is hydrolized, an...

Figure 3.9 DTA for indomethacin Forms I and II (left) and I and III (right)....

Figure 3.10 DTA for sulindac Forms I and II.

Figure 3.11 Solubility and dissolution for sulindac.

Figure 3.12 DSC thermograms for losartan before (curve A) and after (curve B...

Figure 3.13 Solubility data for losartan.

Figure 3.14 XRPD patterns of Forms I and II of Proscar (Finasteride).

Figure 3.15 DSC profiles of Forms I and II of Proscar (Finasteride).

Figure 3.16 DSC profiles of ibuprofen lysinate.

Figure 3.17 Cyclic DSC for ibuprofen lysinate (heat/cool cycle).

Figure 3.18 The XRPD patterns (left) and the TG curves (right) of forms Type...

Figure 3.19 Additional XRPD patterns of anhydrous forms.

Figure 3.20 XRPD patterns for compound A, Forms I and II.

Figure 3.21 Solid‐state NMR for compound A, (a) Forms I and (b) Form II (*re...

Figure 3.22 DSC thermogram for compound A, Forms I and II.

Figure 3.23 XRPD patterns for compound A, Forms III and IV.

Figure 3.24 Solid‐state NMR for compound A, (a) Forms III and (b) Form IV.

Figure 3.25 Solubility data for compound A, Forms I and II in

t

‐butyl acetat...

Figure 3.26 XRPD patterns for prednisolone

t‐

butylacetate.

Figure 3.27 Experimental and calculated XRPD patterns of Form I hydrate (lef...

Figure 3.28

Block A

is hydrate;

Block B

shows water presence on crystal surf...

Figure 3.29 DTA and

T

g

curve for phthalusulfaithiazole.

Figure 3.30 Thermal decomposition pathway for phthalusulfaithiazole.

Chapter 4

Figure 4.1 Effect of supersaturation on growth rate and particle size.

Figure 4.2 Mechanisms of nucleation.

Figure 4.3 Contributions to Gibbs free energy for homogeneous embryo formati...

Figure 4.4 Effect of supersaturation on free energy of cluster formation.

Figure 4.5 Stress on surface molecules in a cluster or crystal can alter its...

Figure 4.6 A schematic representation of the solution depletion in the vicin...

Figure 4.7 Nucleation on a foreign particle for different wetting angles.

Figure 4.8 Measurement of nucleation kinetics for barium sulfate.

Figure 4.9 Measurement of nucleation kinetics and induction time for lovasta...

Figure 4.10 Effect of supersaturation on growth characteristics of MgSO

4

·7H

2

Figure 4.11 A schematic representation of dendrite coarsening.

Figure 4.12 Effect of agitator speed on the secondary nucleation rate for st...

Figure 4.13 Surface structure of a growing crystal: (a) one attachment, (b) ...

Figure 4.14 Formation of a two‐dimensional critical nucleus on a crystal sur...

Figure 4.15 A screw dislocation in a simple cubic crystal. AB, BC are disloc...

Figure 4.16 Development of a growth spiral starting from a screw dislocation...

Figure 4.17 Examples of spiral crystal growth.

Figure 4.18 Distinct adsorption sites for additives and impurities: (a) kink...

Figure 4.19 Low levels of impurity can affect crystal morphology: three view...

Figure 4.20 Shown is 2.5‐order growth for a pharmaceutical compound solubili...

Figure 4.21 Mechanism of aggregation/agglomeration.

Figure 4.22 Crystallization with (left) and without (right) agglomeration.

Figure 4.23 Fluidized bed crystallizer growth rate test apparatus.

Figure 4.24 Size and number intervals for computation of population density....

Figure 4.25 Graphic representation of the population balance of the MSMPR cr...

Figure 4.26 Summary of semi‐logarithmic population density plots and potenti...

Figure 4.27 Methods of seed generation and corresponding size ranges.

Figure 4.28 Generic diagram showing a crystallizer with an external recircul...

Figure 4.29 Typical crystal shapes.

Figure 4.30 Cooling profiles and mass ratio of three experiments.

Figure 4.31 In silico screening of seed impact on crystallization.

Figure 4.32 Microscopic photos of crystals under different supersaturation—2...

Chapter 5

Figure 5.1 Relationship between mixing time and scale.

Figure 5.2 Relationship between agitator rpm and crystallizer volume, under ...

Figure 5.3 Impact of mixing intensity on de‐agglomeration: agglomerates with...

Figure 5.4 Impact of mixing intensity on particle breakage/attrition.

Figure 5.5 Reaction yield as a function of the reaction Da number; mixing se...

Figure 5.6 Particle size as a function of a crystallization Da number (the r...

Figure 5.7 Schematic representation of concentration gradients from bulk sol...

Figure 5.8 Impact of mixing intensity on crystal growth.

Figure 5.9 Comparison of mixing uniformity (using micro‐mixing time) of diff...

Figure 5.10 Comparison of mixing uniformity (using micro‐mixing time) of dif...

Figure 5.11 Typical stirred vessel crystallizer.

Figure 5.12 GlasLock

®

glass‐lined steel impellers.

Figure 5.13 Cryo‐Lock

®

impellers.

Figure 5.14 ElcoLock

®

and fixed impellers

®

impellers.

Figure 5.15 Configuration of a single stage rotor/stator mixer—top view (lef...

Figure 5.16 Fluidized bed crystallizer and dissolver.

Figure 5.17 Impinging jet crystallizer.

Figure 5.18 Mean particle size data as a function of tip speed with varying ...

Figure 5.19 Vessel fill‐up volume among factories.

Chapter 6

Figure 6.1 Four types of supersaturation generation.

Figure 6.2 Effect of time of addition of an anti‐solvent or reagent on super...

Figure 6.3 Effect of supersaturation on nucleation, growth, and nucleate par...

Figure 6.4 Comparison of the growth rate of hexamethylene tetramine crystals...

Chapter 7

Figure 7.1 Solution concentration time profile.

Figure 7.2 Nucleation versus supersaturation.

Figure 7.3 Natural cooling versus linear and controlled cooling.

Figure 7.4 Effect of impurities on conversion of crystal forms.

Figure 7.5 Typical flow pattern for a continuous crystallizer.

Figure 7.6 Feedforward

/

feedback crystallizer control.

Figure 7.7 (a–c) Flow patterns in mixed suspension crystallizers.

Figure 7.8 Simplified information flow for an MSMPR crystallizer.

Figure 7.9 Cascade operation.

Figure 7.10 Flow in an Oslo cooling crystallizer.

Figure 7.11 Product from seeding and cooling process (200×).

Figure 7.12 Steep temperature‐solubility slope for a desired intermediate.

Figure 7.13 Flow in a mixing elbow.

Figure 7.14 Product crystals (200×).

Figure 7.15 Profiles of total particle counts.

Figure 7.16 Profiles of mean particle size.

Figure 7.17 Profile of total particle counts during cool‐down.

Figure 7.18 Profile of mean particle size (area‐based) during cool‐down.

Figure 7.19 Particle size distribution of lab and factory materials at the e...

Figure 7.20 Final particle size using 1 and 5 wt% seed.

Figure 7.21 Final particle size before and after sonication.

Figure 7.22 Resolution of ibuprofen with S‐lysine.

Figure 7.23 Solubility phase diagram.

Figure 7.24 Flowsheet of preferential crystallization.

Figure 7.25 Flowsheet of crystallization with control crystal form.

Figure 7.26 Typical flow pattern for continuous stirred tank separation of s...

Figure 7.27 Typical flow pattern for fluidized bed separation of stereoisome...

Figure 7.28 Unsonicated crystals (left); sonicated (right).

Figure 7.29 Crystals entering (left) and leaving (right) a flow sonication u...

Figure 7.30 Factory fluidized bed crystallizers.

Chapter 8

Figure 8.1 Concentration profiles for crystallization by evaporation as a fu...

Figure 8.2 Concentration profiles for crystallization by evaporation when th...

Figure 8.3 Concentration profiles for crystallization by evaporation when th...

Figure 8.4 A standard jacketed stirred tank with baffles and an overhead con...

Figure 8.5 A standard jacketed stirred tank for evaporative crystallization ...

Figure 8.6 A concentration profile for uncontrolled crystallization by evapo...

Figure 8.7 A concentration profile for a controlled crystallization by evapo...

Figure 8.8 Crystals of batch‐mode crystallization (a) as a slurry and (b) as...

Figure 8.9 Crystals of semi‐continuous crystallization (a) as a slurry and (...

Figure 8.10 Microscopic photo of crystals (left: ethanolate, right: hydrate)...

Figure 8.11 Distillation mode—forward addition (left) and reverse addition (...

Figure 8.12 Sticky gums on the crystallizer wall and phase inversion mechani...

Chapter 9

Figure 9.1 Concentration profiles for normal addition of anti‐solvent to bat...

Figure 9.2 Concentration profile for reverse addition (solute solution to an...

Figure 9.3 Addition rate profile for linear (curve A) and programmed (curve ...

Figure 9.4 Solubility and supersaturation profiles for the linear and optimu...

Figure 9.5 Profile of factory material crystallized with a CBT at low impell...

Figure 9.6 Profile of a lab run crystallized with a PBT, using an appropriat...

Figure 9.7 Typical crystalline product in Example 9.1 before changes in mixi...

Figure 9.8 Typical crystalline product in Example 9.1 after changes in impel...

Figure 9.9 Molecular structures of RRR and SSR isomers.

Figure 9.10 Solubility of RRR and SSR at 20°C in aqueous ethanol in pure sol...

Figure 9.11 Supernatant concentration of RRR and SSR isomers at different so...

Figure 9.12 Scanning electron microscopic photographs of crystals for Exampl...

Figure 9.13 Flow sheet of the antisolvent addition procedure Option 1.

Figure 9.14 Antisolvent addition procedure for Option 2.

Figure 9.15 Effect of crystal size on filtration rate for Option 3. The data...

Figure 9.16 Effect of percentage of fines on filtration rate for Option 3. T...

Figure 9.17 Microscopic photo of crystals for Option 1 (left, normal additio...

Figure 9.18 Microscopic photo of crystals for Example 9.4, Option 4 (DMF/IPA...

Figure 9.19 PSD of crystals for Example 9.4, Option 4 (forward vs reverse ad...

Figure 9.20 A common flow diagram for impinging jet crystallization.

Figure 9.21 Impinging jet crystallization has very high volumetric productiv...

Figure 9.22 Impinging jet crystallization—surface area versus supersaturatio...

Figure 9.23 (a) Photomicrographs of equal surface area products obtained by ...

Figure 9.24 Chemical structure of DFP, an API candidate utilizing impinging ...

Figure 9.25 Schematic of the impinging jet crystallizer showing the option t...

Figure 9.26 Microscopic photos of (a) direct jet and (b) recycle jet crystal...

Figure 9.27 Surface area as a function of supersaturation. The higher the su...

Figure 9.28 PSD of the same compound (DFP) crystallized by impinging jet com...

Figure 9.29 Process flow diagram of in situ wet seed and particle generation...

Figure 9.30 PLM images of crystals generated by the in situ wet seed/particl...

Figure 9.31 Agglomerated particles with wide variation of particle size dist...

Figure 9.32 Nonagglomerated particles with uniform and robust particle size ...

Chapter 10

Figure 10.1 Schematic representation of addition modes for reagents in react...

Figure 10.2 Schematic representation of reagent addition time (overall time ...

Figure 10.3 Impinging jet crystallization apparatus.

Figure 10.4 Size distribution of calcium oxalate crystallized at (a) 2 and (...

Figure 10.5 Photographs of impingement planes in a free jet (a) at feed velo...

Figure 10.6 Size distribution of sodium cefuroxime crystallized by conventio...

Figure 10.7 (a) Needles from the reactive crystallization (b) Crystals after...

Figure 10.8 (a) Crystals showing a bimodal distribution during crystallizati...

Figure 10.9 (a) Bimodal distribution from the original process showing fines...

Figure 10.10 Reagent addition time effect on the supersaturation experienced...

Figure 10.11 Flowchart for the simultaneous addition of stream A containing ...

Figure 10.12 Microscopic photo of crystals. Some layering of crystals is app...

Figure 10.13 Residual solvent in the cake as a function of the ratio of time...

Figure 10.14 Simultaneous addition with wet milled heel seed.

Figure 10.15 Crystals from the original process and the revised process afte...

Chapter 11

Figure 11.1 Classification of filtration operations.

Figure 11.2 Filtration and washing steps—Step 1: solid–liquid separation, St...

Figure 11.3 Driving force in filtration/washing.(

Note

:

P

1

 > 

P

2

for pot‐typ...

Figure 11.4 Filtration resistance—cake and medium.

Figure 11.5 Filtrate concentration profiles (curves

a

,

b

,

c

) during filtrati...

Figure 11.6 Cake wash with channeling and mother liquor left‐over.

Figure 11.7 Effect of wet cake saturation level on washing efficiency.

Figure 11.8 Particle image and size distribution before and after the washin...

Figure 11.9 Filtrate impurity profile after each wash.

Figure 11.10 Impurity concentration in the filtrate after each wash.

Figure 11.11 Filtration profile of

t

/

V

over

V

, under different

∆P

.

Figure 11.12 Filtration rate vs. slurry settling rate.

Figure 11.13 (a) Filtration operation—agitated filter. (b) Filtration operat...

Chapter 12

Figure 12.1 V–L equilibrium of acetone, water, and heptane.

Figure 12.2 Water vapor pressure and water activity.

Figure 12.3 Hydration behavior of different hydrates under different humidit...

Figure 12.4 Stress–strain relationship.

Figure 12.5 Relationship between granule wetness and granule size/torque. Op...

Figure 12.6 Relationship between formation of large agglomerates, torque val...

Figure 12.7 (a) Torque and wetness relationship of three different particle ...

Figure 12.8 Drying profiles: induction, constant rate, and falling rate stag...

Figure 12.9 Drying profiles with different nitrogen sweep modes.

Figure 12.10 Impact of mixing energy and cake wetness on fracturing, agglome...

Figure 12.11 Dryers with different mixing/blending patterns.

Figure 12.12 Residual solvents versus wet cake weight (top) and wet cake LOD...

Figure 12.13 Starting material.

Figure 12.14 Comparison of particle agglomeration/fracturing behavior of rot...

Chapter 13

Figure 13.1 Solubility curve in aqueous solution showing the width of the me...

Figure 13.2 Flowsheet for Example 13.1; feed preparation and crystallization...

Figure 13.3 (a) The very large cubic crystals have grown in aqueous solution...

Figure 13.4 Photomicrographs of antibiotic crystals; the sharpness of the cr...

Figure 13.5 Concentration profiles for a consecutive–competitive reaction sh...

Figure 13.6 Effect of the solubility of the desired product,

R

, in the react...

Figure 13.7 Effect of the addition time of reagent

B

on the yield

/

selectivit...

Figure 13.8 Chemical reaction of Example 13.3.

Figure 13.9 Flowsheet of the original process of Example 13.3.

Figure 13.10 Solubility of Mono and Iso in the toluene mother liquor of Exam...

Figure 13.11 Flowsheet of the two‐filtration process with recycle of second ...

Figure 13.12 (a) DMSO and active carbon absorption isotherms at room tempera...

Figure 13.13 Chemical structure of imipenem.

Figure 13.14 DSC thermograms for 10, 20, and 30% acetone

/

water solutions.

Figure 13.17 DSC thermograms for 30% acetone

/

water and imipenem

/

NaHCO

3

in a ...

Figure 13.18 Relationship between the degree of crystallinity of imipenem an...

Figure 13.19 Flowsheet of stereoisomer resolution systems.

Figure 13.20 (a) Fluidization behavior of particular solids in a (liquid) fl...

Figure 13.21 (a) The histogram plots the actual column data versus the ideal...

Figure 13.22 (a) Sonicators located at the bottom of the column. (b) Fines g...

Figure 13.23 The sonicator is an external circulation loop.

Figure 13.24 The calculations for the particles in a fluidized bed.

Figure 13.25 (a) Different relative scales of some actual fluidized bed crys...

Figure 13.26 Comparison of dissolution profile of hybrid solid dispersion an...

Figure 13.27 Microscope images of ASD samples before and after dispersed in ...

Figure 13.28 Microscopic Images of hybrid samples before and after dispersed...

Figure 13.29 DSC profiles of physical mixture, ASD and hybrid solid dispersi...

Guide

Cover Page

Title Page

Copyright Page

Preface

Table of Contents

Begin Reading

References

Index

WILEY END USER LICENSE AGREEMENT

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Crystallization of Organic Compounds

An Industrial Perspective

Second Edition

Hsien‐Hsin TungEdward L. PaulMichael MidlerJames A. McCauley

Copyright © 2023 by the American Institute of Chemical Engineers, Inc. All rights reserved.

A Joint Publication of the American Institute of Chemical Engineers and John Wiley & Sons, Inc.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.

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Library of Congress Cataloging‐in‐Publication Data:Names: Tung, Hsien‐Hsin, 1955‐ author. | Paul, Edward L., author. | Midler, Michael, 1936‐2023, author. | McCauley, James A. (Chemical engineer), author. | John Wiley & Sons, publisher.Title: Crystallization of organic compounds : an industrial perspective / Hsien‐Hsin Tung, Edward L. Paul, Michael Midler, James A. McCauley.Description: Second edition. | Hoboken, New Jersey : Wiley, [2024] | Includes index.Identifiers: LCCN 2023015060 (print) | LCCN 2023015061 (ebook) | ISBN 9781119879466 (hardback) | ISBN 9781119879473 (adobe pdf) | ISBN 9781119879480 (epub)Subjects: LCSH: Crystallization–Industrial applications. | Pharmaceutical chemistry. | Pharmaceutical industry.Classification: LCC TP156.C7 T86 2024 (print) | LCC TP156.C7 (ebook) | DDC 615/.19–dc23/eng/20230520LC record available at https://lccn.loc.gov/2023015060LC ebook record available at https://lccn.loc.gov/2023015061

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Preface

With the supporting feedback received over these years after the first edition, the goal of the second edition of this book inherits the same as the first edition. The first is to facilitate the understanding of crystallization fundamental properties and the impact of these properties on crystallization process development. The second is to improve problem solving ability through actual industrial examples under real process constraints.

In the second edition, the fundamental knowledges and key examples from the first edition are retained. New learnings are incorporated to reflect the current practice and potential future direction. These include a deeper knowledge on the phase behavior between drugs and solvents/excipients and in silico solubility prediction and screening (Chapter 2); formation of stable/metastable polymorphs via equilibrium and kinetic factors and conformer screening of salt/cocrystal and chiral resolution (Chapter 3); in situ seed generation via wet mill, model‐based crystal growth/nucleation parameter estimation, and process optimization (Chapter 4); CFD simulation, mixing scale‐up, and quality‐by‐design/process control strategy (Chapters 5 and 6); updated examples of anti‐solvent/evaporation/reactive crystallization (Chapters 8, 9, and 10); and API/excipient coprocessing of amorphous and crystalline solid dispersion composite (Chapter 13). Additionally, in the second edition, new chapters on filtration and drying downstream operations (Chapters 11 and 12) are added to address the final isolation aspects of solid properties after the crystallization.

During the period in preparing the second edition, two of our authors, Drs. Ed Paul and Mike Midler, passed away. However, their passion and dedication will continue to stay through this book.

Finally, as cited in the first edition, Matthew: 12:33, “Either declare the tree good and its fruit is good, or declare the tree rotten and its fruit is rotten, for a tree is known by its fruit.” It continues to be our hope that you, as readers, will find the second edition of this book useful for your works. If so, this will be the nicest reward for us.

Hsien‐Hsin Tung,Edward L. Paul,Michael Midler,James A. McCauley

Chapter 1Introduction to Crystallization

Crystallization has been the most important separation and purification process in the pharmaceutical industry throughout its history. Many parallels exist in the fine chemicals industry as well. Over the past several decades, the study of crystallization operations has taken on even higher levels of importance, because of several critical factors that require increased control of the crystallization process. These levels of control require better understanding of the fundamentals as well as of the operating characteristics of crystallization equipment, including the critical issue of scale‐up.

In the pharmaceutical industry, the issue of better control, desirable in and of itself, is reinforced by the need to satisfy the regulatory authorities that a continuing supply of active pharmaceutical ingredients (APIs) of high and reproducible quality and bioavailability can be delivered for formulation and finally to the patient. The “product image” (properties, purity, etc.) of this medicine must be the same as that used in the clinical testing carried out to prove the product’s place in the therapeutic marketplace. Some additional comments on critical issues, quality‐by‐design, and regulatory issues are included later in this chapter (Section 1.4).

The issues noted above that require increased control, relative to previous practice, include the following:

Final bulk drug substances must be purified to high levels that are increasingly quantifiable by new and/or improved analytical methods.

Many drugs now require high levels of achievement and maintenance of chirality.

Physical attributes of the bulk drug substance, i.e. crystallinity, amorphism, crystal forms, and particle size distribution (PSD), must be better controlled to meet formulation needs for bioavailability, stability, and reproducibility needs.

Increased demands are being made for achievement and maintenance of crystal morphology.

Increasingly complex molecular structures with higher molecular weights are being processed.

The biotechnology sector has increased the use of precipitation of macromolecules for purification and isolation of noncrystalline materials.

Added to this list is the assertion, based on operating experience, that crystallization and its downstream operations including filtration and drying can be difficult to scale‐up without experiencing changes in physical attributes and impurity rejection. Regulatory requirements for final bulk drug substances, as noted above, now include the necessity for duplication of physical attributes including PSD, bulk density, and surface area within narrow ranges when scaling from pilot plant to manufacturing scale.

When compared to the development of models and methods for other unit operations, it is obvious that crystallization and its downstream operations have not been generalized to the degree that has been accomplished for distillation, extraction, adsorption, etc. This situation is changing rapidly, however, with increasing research now being carried out at academic and industrial centers on crystallization fundamentals to model and predict solubility, polymorph, nucleation, growth rates, and mixing as well as other key properties, such as hydration, dehydration, particle attrition, and agglomeration in drying.

Control of crystallization processes requires modulation of either nucleation or growth, or, as is most often the case, both modes of crystal development simultaneously. Each operation must be evaluated to determine which of the process objectives is the most critical from the point of view of overall outcome, in order to determine whether nucleation or growth should be the dominant phase. The number and size of nuclei initially formed, or equivalently seeded, can dominate the remainder of the operation. However, it is generally agreed that nucleation can be trickier to control, since there are several factors that can play a role in the conditions for nucleation onset, nucleation rate, and number of crystals generated before growth predominates.

The demand for increasing control of physical attributes for final bulk pharmaceuticals has necessitated an integration in emphasis from control of initial nucleation as seed to control of growth for the rest of crystallization. This trend is also finding application for control of purity and improved downstream handling for both intermediates and final bulk products. The obvious critical factors then become seeding and control of supersaturation. Quantification of these factors for each process is essential for development of a scalable process.

For downstream filtration/washing and drying, it would require control of both equilibrium and kinetic variables. If mixture of solvents is used for cake washing, fractionation of residual solvent in the wet cake during drying can lead to solvent entrapment in the final dry cake. Improper humidity level during drying of hydrate can also induce dehydration risk. Simultaneous particle attrition and agglomeration would also require a good balance among process operating parameters, cake wetness, particle physical properties, etc. Cake homogeneity has always been a challenge upon scale‐up. Again, a sound knowledge of these factors is essential for development of a scalable process.

The purpose of this book is to outline the challenges that must be met and the methods that have been and continue to be developed to meet these requirements to develop reproducible operations and to design equipment in which these goals can be realized.

The four conventional crystallization operations (Chapters 7, 8, 9, and 10) and downstream operations (Chapters 11 and 12) will be discussed in terms of their strengths and weaknesses in achieving specific process objectives. In addition, methods of augmenting the conventional processing methods will be included with emphasis on the enhanced control that is often necessary to achieve the specific objectives.

This book also includes chapters on the properties of organic compounds (Chapter 2), polymorphism (Chapter 3), the kinetics of crystallization (Chapter 4), mixing and scale‐up in crystallization (Chapter 5), and critical issues and quality by design (Chapter 6). Selected Topics (Chapter 13) contain areas of current crystallization research and development we thought worth mentioning and also some unique crystallization processes that have special features to be considered in process development. To assist in the thought process for organization of a new crystallization process, and to address the quality‐by‐design and control strategy topics, Chapter 6 specifically contains a suggested protocol for development and scale‐up of a crystallization operation.

1.1 CRYSTAL PROPERTIES AND POLYMORPHS (CHAPTERS 2 AND 3)

Basic crystal properties include solubility, supersaturation, metastable zone width, induction time, oil, amorphous solid, polymorphism, solvate, occlusion, morphology and PSD, and so on. Clearly, in order to properly design and optimize crystallization processes, along with downstream operations to generate desired solids, it is essential to have a sound understanding of these properties.

For pharmaceuticals and special organic chemicals, solution crystallization, in which solvents are used, is the primary method of crystallization compared to other crystallization techniques such as melt and supercritical crystallization. Therefore, the goal of these chapters is to introduce basic properties of solution and crystals related to solution crystallization and subsequent downstream operations. The relevance of these basic properties to crystal qualities and crystallization operations will be highlighted with specific examples.

Some properties are more clearly defined than others. For example, solubility is defined as the amount of solid in equilibrium with the solvent. Solubility can affect the capacity of the crystallization process, and its ability to reject undesired compounds and minimize loss in the mother liquor. In addition, solubility varies widely from compound to compound or solvent to solvent. On the other hand, there are properties that are much less characterized or understood. For example, the mechanism and condition for the formation of oil or amorphous solid remain less clear. The composition of oil and amorphous solid can be variable, and certainly can contain a much higher level of impurities than that in the crystalline solid, which leads to a real purification challenge. In addition, oil or amorphous solid generally is less stable and can create critical issues in drug formulation and storage stability. In recent years, some amorphous organic compounds are formulated using amorphous solid dispersion technique which contains polymeric or other non‐active ingredients to maintain the amorphous state of the organic compounds over sufficient shelf life. The amorphous state of compounds can improve the bioavailability over that of the corresponding crystalline compounds. But special attentions are required on design and processing to ensure both chemical and physical stability of the compounds.

One property of a crystalline compound is its ability to form polymorphs, that is, more than one crystal form for the same molecular entity. The phenomenon of polymorphism plays a critical role in the pharmaceutical industry. It affects every phase of drug development, from initial drug discovery to final clinical evaluation, including patent protection and competition in the market. A critical challenge is the early identification of possible polymorphs. A relevant property of a crystalline compound is the possibility to form salts or cocrystals with the same active ingredient. Similar to the case of polymorph, salt and cocrystals can have different physical and chemical properties from the original compound. Chapters 2 and 3 will address these key issues.

1.2 NUCLEATION AND GROWTH KINETICS (CHAPTER 4)

Meeting crystal product specifications with a robust, repeatable process requires careful control and balancing of nucleation and growth kinetics. Careful structuring of the environment can dictate the fundamental mechanisms of nucleation and crystal growth and their resultant kinetics. Undesired polymorphs can be often minimized or eliminated by suitable control of rate processes.

One important industrial implication of nucleation is generation of wet seed. Under high mixing condition and supersaturation, the resulting nuclei via primary nucleation and/or secondary nucleation can serve as seed and act as a wet‐seed generation platform. This wet seed possesses theoretical and practical advantages over dry seed generated by dry milling techniques. The wet seed can contain less defects than that of the dry (milled) seed, due to simultaneous seed annealing in wet condition. The concern about long‐term storage stability of seed is nonexistent. The size of nuclei can be manipulated by controlling the mixing environment and supersaturation. Also, the amount of seed can be a control variable. Interestingly through actual industrial observation of applying wet‐seed generation platform, the likelihood of discovering and generating the most stable crystal form in the early phase of drug development seems to improve drastically. It is hypothesized that the kinetics of metastable form conversion to stable form is much accelerated under the high mixing intensity environment versus the typical crystallization environment in the laboratory which is under low mixing intensity.

Understanding of the possible nucleation and crystal growth kinetics for desired (and undesired) compounds can lead the process development effort on a considerably shorter path to success. Applying fundamental models and determining these kinetic factors through design of experiment (DOE) approach enable in silico simulation for what‐if scenarios quickly. It can greatly improve the process understanding, reduce the process development efforts, and ensure success upon scale‐up and commercialization. Alternatively, applying process analytical technology to monitor the nucleation and crystal growth kinetics without the modeling can also be applied. The PAT measurement determines the crystallization kinetics in real time and adjusts the operating parameter through selected feedback control algorithm. A reliable PAT instrument would be very beneficial for the model‐free approach.

1.3 MIXING AND SCALE‐UP (CHAPTER 5)

While many crystallization processes, including downstream filtration and drying, can tolerate a wide range in mixing quality and intensity, many engaged in development do not examine the effect of mixing on their process until forced to do so by problems in scale‐up, or even possibly at lab scale. The result is, at best, loss of time and effort.

Transport of momentum, mass, and energy, all affected by mixing can be critical for success in many crystallization processes, especially so with complex organic compounds. Momentum transport can influence slurry homogeneity, impact nucleation, shear damage, agglomerate formation, and discharge of slurry. Mass transport can affect the uniformity of supersaturation (micro‐, meso‐, and macro‐mixing), and in reactive crystallization can affect, even at the molecular level, the resultant reaction and subsequent supersaturation pattern. Energy transport has a direct effect on heat transfer, for example drying, and proper mixing can minimize or avoid encrustation on the heat transfer surfaces.

From the industrial perspective, mixing would be considered to be the sole critical factor upon scale‐up. Since mixing affects multiple variables simultaneously, it can be complex to evaluate the mixing impact on the scale‐up due to potentially nonlinear and/or conflicting trends from different considerations. It can be beneficial to consider different mixing criteria separately, i.e. mixing time, mixing intensity, and mixing pattern/distribution, then evaluate the overall impact of mixing on the process performance.

An adaptation of the Damkoehler number (Da) is a useful concept for evaluating the impact of mixing time. It is the ratio of the characteristic mixing time to its corresponding process time (nucleation induction time, crystal growth/supersaturation release time, reaction time, etc.). Studies of these times and the resulting predicted Damkoehler number in a laboratory setting can provide evidence of possible scale‐up problems.

The effects of mixing intensity on, for example surface films in crystal growth, and micro‐mixing time (local homogeneity) when adding antisolvent or reagent, are examined in Chapter 5. The mixing pattern of varying options (impeller design, vessel geometry—e.g. fluidized bed, contoured bottom), external re‐circulation loops, etc. are also discussed. Computational fluid dynamics (CFD) is increasingly being utilized to analyze mixing systems, particularly the stirred vessels commonly used for crystallizer operation. Case of CFD simulation is presented in Chapter 5.

1.4 CRITICAL ISSUES AND QUALITY BY DESIGN (CHAPTER 6)

1.4.1 Critical Issues

Difficulty in control of crystallization processes and downstream operations in general can be exacerbated when working with complex organic compounds. The solids of these complex organic compounds can have complex behavior, for example amorphous solid, polymorphs, solvate/hydrate, humidity, and temperature environment. This can be even worse when attempting to develop a nucleation‐dominated kinetic‐driven process, which even in the best of circumstances can potentially operate over a very wide range of supersaturation, depending on small changes such as varying amounts of very low level impurities.

Organic compounds are subject to agglomeration/aggregation effects and even worse, to “oiling out.” All of these can potentially result in undesired trapping of solvent and/or impurities in the final crystal. Oiling out, of course, can completely inhibit the formation of a crystalline phase thereby resulting in a gum or amorphous solid. Agglomeration or aggregation (as well as attrition) can occur not only during the crystallization but also during the drying. These phenomena are discussed qualitatively in Chapter 6.

Crystalline processes often provide initially a seed bed for crystal growth. The wet‐seed generation approach, as mentioned in Section 1.2 and Chapter 4, possesses many advantages over dry seeding. Seed crystals directly affect final crystal form and purity, particularly in avoiding formation of “undesired” crystals, such as chiral resolution. Seed particle size and amount directly affects final product particle size. For a growth‐dominant crystallization process, it would be straightforward to estimate the final product particle size and shape based upon the seed size, amount, and shape. When attempting to control particle size and shape of final product, an excessive number of seed nuclei can limit the upper range of achievable product particle size or morphology. For case like that, optimal processes with externally or internally generated wet seed often requires some level of seed conditioning for modifications of seed size and morphology. Principles for such conditioning are discussed in Chapter 6 and in some of the examples.

1.4.2 Design of Experiment

The need for controlled crystallization methods and equipment is required not only to meet internal standards, as indicated by consistency for intermediates and particularly for APIs, but also to meet regulatory requirements. These requirements include controls on both chemical purity and physical attributes.

For APIs, critical quality attributes (CQAs) are set by the “biobatch” model for clinical evaluation. The specifications can include chemical purity, mean particle size, PSD, and other appropriate physical attributes. The term “biobatch” refers to the regulatory requirement of identifying a particular batch, normally a pilot scale batch used in clinical trials, as the defining standard for physical and chemical attributes that must be reproduced at the manufacturing scale to be acceptable for sale. The critical process controls (CPCs) for the process, which includes critical process parameters (CPPs) and critical in‐process controls or analysis (IPCs or IPAs), are defined to ensure that the process can consistently manufacture APIs meeting the specifications. The CPCs, once established, must be met on scale‐up to the manufacturing facility. In addition, the process must be operated within the range of design space established. Development of a crystallization and downstream process must include determination of realistic and reproducible ranges for both the CPPs and the IPCs.

With the advancement of online measurement techniques such as focused beam reflective measurement (FBRM) and Fourier transform infrared (FTIR), it is possible to obtain hundreds of data points of PSD and solution concentration (i.e. supersaturation) information during one single crystallization experiment. Applying design of experiment principle with focus on nucleation and crystal growth phenomena, respectively, just a few model‐based experiments can reliably estimate these crystallization parameters, which in return afford rapid in silico screening of various crystallization scenarios. This model‐based QbD approach offers deep fundamental understanding and significant savings on experimental effort and time for the development and optimization of crystallization processes. Examples will be given in Chapter 4.

Based upon a similar concept, using simple PAT tool such as liquid refractive index, vapor phase humid meter, the model‐based QbD can also provide deeper knowledge and control of downstream filtration/washing and drying performance. Some cases are provided in Chapters 12 and 13.

It can be asserted that one of the most difficult processes to scale‐up successfully is crystallization. Methods to achieve control of nucleation and growth are keys to development, and the degree to which they are successfully applied can determine the difference between success and failure on scale‐up. It is to this fundamental problem that this book is addressed, combining critically important teachings from the literature with personal experience of the authors and their colleagues in a variety of crystallization and downstream operations.

1.5 CRYSTALLIZATION PROCESS OPTIONS (CHAPTERS 7–10)

The following is a qualitative discussion of several of the procedures that are used to create and maintain conditions under which crystallization can be carried out. These procedures create supersaturation by different methods and utilize seeding to varying degrees. The procedures are classified by the manner in which supersaturation is generated.

The equally critical issues of when to seed and how much seed to use are introduced in each classification. The amount of seed can vary from the extremes of none to “massive” and include the familiar classifications of “pinch” to hopefully avoid complete nucleation, “small” (<1%) to hopefully achieve some growth, “large” (5–10%) to improve the probability of growth, and “massive” (the seed is the product in a continuous or semicontinuous operation) to provide maximum opportunity for all growth. The amount of seed can also be critical in control of polymorphs and hydration/solvation.

The important and developing methods of online measurement of solution concentration and particle size and count are adding powerful tools to aid in control of crystallization operations both in experimentation and manufacturing operations. These methods will also be discussed in the context of their utilization.

1.5.1 Cooling (Chapter 7)

1.5.1.1 Batch Operation

Cooling a solution from above its solubility temperature can be performed in a variety of ways depending on the system and the criticality of the desired result. Natural cooling as determined by the heat transfer capability of the crystallizer is the simplest method but results in varying supersaturation as the cooling proceeds. This may or may not be detrimental to the process, depending on the nucleation and growth rate characteristics of the particular system. Natural uncontrolled cooling has the potential to decrease the temperature rapidly enough to pass through the metastable region and reach the spontaneous nucleation region before seeding can be effective. Spontaneous nucleation can be non‐predictive from batch to batch; a major problem with potential to cause “oiling out,” agglomeration and/or fine particles; a larger PSD; and occlusion of solvent and impurities. A secondary disadvantage to uncontrolled cooling can be accumulation of crystal scale on the cooling surface caused by low temperatures at the wall. Accumulation of a scale layer can be triggered by nucleation on the cold surface followed by growth on the thickening scale. This encrustation can severely limit the cooling rate, as well as cause major issues of nonuniformity in the product.

When high supersaturation is not acceptable, temperature cooling strategies can be utilized to match the cooling rate with the increasing surface area. These rates were derived by Mullin and Nyvlt (1971) and further derived by Mullin (1993) and are very useful in control of supersaturation. They prescribe cooling rates that are much slower at the outset than natural cooling in order to maintain supersaturation in or close to the growth region when the crystal surface area for growth is low. Cooling rate can be increased as the surface area increases. An added benefit of this method is the potential to reduce encrustation by limiting temperature differences across the jacket. In theory, encrustation can be eliminated if the temperature difference between the cooling fluid and the crystallizing mixture is less than the width of the metastable zone (Mersmann 2001, pp.437 ff).

A further refinement of this strategy is described by Jones and Mullin (1974), in which a seed age is added as a further aid in limiting the development of supersaturation thereby reducing nucleation and promoting growth.

As with all crystallization options, the most critical factor is seeding. One issue is determining the seed point. If the seed is added at a temperature above the solubility, some or all of it can dissolve. If the seed is added at a temperature too far below saturation, the product may have already nucleated. This issue, determining the point of seeding, is common to crystallization by cooling, solvent removal by concentration, and by anti‐solvent addition. The application of in situ seed generation approach greatly removes the sensitivity of seeding supersaturation via primary and secondary nucleation. To control the nucleation event consistently, a portion of (or all) the batch can be subject to a high mixing intensity environment under supersaturation. The resulting nuclei serve as slurry seed for the remaining batch for crystallization. The rate of nucleation and size of nuclei can be manipulated via controlling mixing intensity environment as an independent variable, as well as supersaturation. As a result, the nucleation event can be controlled with a much higher degree of certainty in comparison to the conventional “non‐predictable” primary nucleation event.

Online, in situ instrumentation to measure product composition has been developed to successfully determine the seed point, and is being utilized in increasing number of crystallization operations. Image analysis or photographic methods may be useful in determining the presence of nuclei >5 microns but would be too late to determine the point of seeding. These methods can be used, however, to determine if seeding was successful and to observe whether or not excessive nucleation has occurred. Incorporation of an age period at constant temperature after seeding can also help normalize the nucleation/growth ratio.

Heat/cool temperature cycling is a common and powerful technique for improvement of crystal morphology in cooling crystallization. It can be easily adopted into evaporative, anti‐solvent, and reactive crystallization as well. As per authors’ experience, this technique has a higher impact in improving the final crystal morphology, if applied at the seed generation stage instead of at the end of crystallization stage. At the end of each cooling cycle, an additional wet‐milling operation such as sonification or homogenizer can be applied to break the longest dimension of crystals and reduce the aspect ratio. Cases will be presented throughout the book.

Crystallization by cooling may not be feasible when polymorphs are stable at different temperatures within the cooling range. Cooling through these regions of stability can result in mixed morphologies or a change from one polymorph to another. Uncontrolled nucleation can also be a major issue in achieving a uniform product when polymorphs are possible. A constant temperature process with either a high level of seed or “massive” seed may be required to achieve selection of the desired polymorph. Hydrates and solvates may also be subject to these considerations in crystallization processes. Polymorphism is the subject of Chapter 3.

1.5.1.2 Continuous Operation

The difficulties in batch‐to‐batch variation discussed above for batch cooling methods can be largely overcome by utilizing continuous operation to achieve both control of low levels of supersaturation and operation with “massive” amounts of seed. This technology is widely practiced for high volume products but finds less application in the pharmaceutical industry because of lower volumes and campaigned operations in which continuous operations are more difficult to justify. However, in some examples discussed below, there is no alternative to continuous operation to achieve the separation and purification required.

A primary example is the resolution of optical isomers by continuous crystallization in fluid beds. Control of low supersaturation by control of the temperature difference between the continuous feed and the seed bed is critical to maintaining an essentially all‐growth regime in which the individual isomers grow on their respective seeds in separate crystallizers. The seed beds in both crystallizers are “massive” in relation to the amount of racemic solution passing through in order to present sufficient seed area to maintain low supersaturation. Uncrystallized isomers in the overhead streams are recycled to dissolve additional racemic feed. Crystal size is maintained by sonication. See Examples 7.6 and 13.6 for a discussion of resolution of optical isomers by continuous crystallization.

This special case illustrates the power of continuous cooling processes with “massive” seed to reject impurities that have the potential to crystallize at equilibrium. Batch cooling to achieve this separation of optical isomers is not a practical alternative because the resolution is not based on equilibrium solubility. The time required for batch cooling would result in the nucleation of the undesired isomer when any practical amount of product is to be harvested in each cycle.