Des O Grady Thesis Multiscale Characterization Of Antisolvent Crystallization

1

MULTI-SCALE CHARACTERIZATION OF ANTI-SOLVENT CRYSTALLIZATION

Des O’Grady

December 15th 2008

School of Chemical and Bio-Process Engineering

PhD Viva

2

Introduction

Utilize a relatively neglected model system where sound chemical

engineering principles can be applied to improve understanding

Focus on key stages in the pharmaceutical drug development

lifecycle

Combine existing crystallization theory with in situ analytics and

modern models to improve understanding

Develop simple and effective techniques that can be used to

improve industrial crystallization

Implement a common sense scale-up protocol based on extensive

laboratory-scale characterization

3

Introduction 1

Chapter 1 – Introduction

Chapter 2 – Literature Review

Chapter 3 – Solubility

Chapter 4 – Mixing and MSZW

Chapter 5 – Monitoring and Growth

Chapter 6 – Scale-up

4

Chapter 3 – Solubility – Goals

Generate solubility data for model system

Investigate most suitable way to express anti-solvent solubility

Assess feasibility of different techniques and cross-validate each

method

Calibrate ATR-FTIR probe

Apply a theoretical model to measured solubility data

5

Simple Solubility Expression

0 10 20 30 40 50 60 70 800

0.1

0.2

0.3

0.4

0.5

0.6Solubility Data

Solute Concentration

anti-solvent %

g s

olu

te /

(g s

olv

ent

+ a

nti

-solv

ent)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Solubility Data

Solute Concentration

g anti-solvent / g solvent

g s

olu

te /

g s

olv

ent

Traditional vs. “anti-solvent free” solubility expression

1. 2.

6

Gravimetric Analysis

Two Gravimetric methods were used to measure solubility Solid analysis – mass of solute left in filter cake after drying Liquid Analysis – mass of solute remaining after filtrate was

evaporated

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Solid Analysis

Liquid Analysis

(g water/ g ethanol)

(g b

enzo

ic a

cid/

g e

thanol)

7

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Water Concentration (g water/ g ethanol)

Solu

bilit

y (

g b

enzo

ic a

cid/

g

eth

anol)

FBRM Analysis

“Polythermal” method was used to generate solubility information Solubility temperature was measured at a range of anti-solvent concentrations Anti-solvent concentration vs. solubility plot was then interpolated at 25ºC This method opens possibility of 3-dimensional solubility plot

15 20 25 300.0

0.1

0.2

0.3

0.4

0.5

0.6

0.70.90 (g water/g ethanol)

1.37 (g water/g ethanol)



Temperature (°C)

Solu

bilit

y g

benzo

ic a

cid/g

eth

anol

8

ATR-FTIR Solubility Measurement

Serial additions of solvent to saturated suspension at 25ºC Solubility point taken after 30 minute hold period Equilibrium achieved very quickly – dissolution kinetics are fast Potential for slow, continuous solvent addition to generate continuous solubility

curve

0 2000 4000 6000 8000 10000 120000

0.5

1

1.5

2

2.5

3

0

0.1

0.2

0.3

0.4

0.5

0.6Water Concentration

Benzoic Acid Concentration

Time (s)

Wate

r C

once

ntr

ati

on (

g/g

)

Benzo

ic A

cid C

once

ntr

ati

on

(g/g

)

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00.0

0.1

0.2

0.3

0.4

0.5

0.6

Water Concentration (g water/ g ethanol)

Solu

bilit

y (

g b

enzoic

acid

/ g

eth

anol)

Slight increase possibly due to temperature effect – heat of mixing

9

Overall Solubility Measurement

Good agreement between 3 methods Accuracy of generated solubility curve is validated Liquid Analysis systematically underestimated the solubility

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

ATR-FTIR Solubility

FBRM Solubiliy

Solid Analysis

Liquid Analysis

Water Concentration (g water / g ethanol)

g b

enzo

ic a

cid /

g e

thanol

10

UNIQUAC Model

UNIQUAC model follows observed solubility trends Predicts increase in solubility at low water concentrations

11

Introduction 1







12

Chapter 3 – Solubility – Conclusions An accurate solubility curve has been generated and validated

Liquid analysis underestimated solubility

Increase in solubility observed at low water concentrations

‘Anti-solvent free’ solubility expression simplifies analysis

MSZW and supersaturation simple to understand and define

Analogous to cooling crystallization

ATR-FTIR probe is calibrated

Calibration model accuracy within 2%

Supersaturation can be monitored during subsequent experiments

UNIQUAC model generated

Theoretical model fits measured data adequately

13

Introduction 1







14

Chapter 4 – MSZW & Mixing – Setup

Study the impact of key process

parameters on MSZW

Develop a model to account for differences

in the MSZW

Develop an agitation dependent

expression for the nucleation rate

Impact of Parameters on MSZW

16

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.50.0

0.1

0.2

0.3

0.4

475 rpm - wall addition location

Addition Rate (g water/s )

MS

ZW

(g w

ate

r/g e

thanol)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5

-0.1

0.0

0.1

0.2

0.3

0.4

475 rpm - impeller addition loca-tion

Addition Rate (g water/s )

MS

ZW

(g w

ate

r/g e

thanol)

Impact of agitation, addition rate and addition location on MSZW Experiments were performed in triplicate – error bars are 95% confidence

interval Some negative MSZW were observed – nucleation prior to saturation point Changing the addition location has the most significant impact

17

Chapter 4 – Mixing and MSZW – Interim Conclusions

Wall addition location results in significant variability

Variability worse at low agitation and fast addition rate

Negative MSZWs observed at low agitation

Typical widening of MSZW at high supersaturation generation rates not

observed

Impeller addition location results in little or no variability

MSZW widens with increasing supersaturation generation rate

Reducing agitation intensity results in a wider MSZW

Rate and degree of anti-solvent incorporation needs to be studied

Inadequate anti-solvent incorporation may result in locally high

supersaturation

A CFD model may help understand the differences between addition locations

18

CFD Model

CFD models show velocity in z-direction (up-down) at liquid surface Close to the wall the velocity is upward – hindering anti-solvent incorporation Close to the impeller the velocity is downward – facilitating anti-solvent incorporation These models provide a model for the observed results Nucleation is hydrodynamically limited when anti-solvent is added at the wall

325rpm

475rpm

impeller

impeller

wall wallimpeller

impeller

wall wall

19

Nucleation kinetics

Classical nucleation kinetics are modified for an anti-solvent system Only experimental data gathered at the impeller location is considered A non-linear regression is used to estimate kinetic parameters – including an

agitation parameter

-2.4 -2.2 -2 -1.8 -1.6 -1.4 -1.2 -1-9.0

-8.0

-7.0

-6.0

-5.0

-4.0

475rpm325rpm

ln (ΔAmax)

ln (

R)

kn = 1.9x10-3

n = 2.5 = 1.1

3.

4.

5.

xy

6.

20

Predicting MSZW

Good agreement between measured MSZW and predicted values Clearly impeller speed plays a critical role in nucleation kinetics This kinetic model allows MSZWs to be predicted under certain

hydrodynamic conditions

0 0.0010.0020.0030.0040.0050.0060.0070.0080.0

0.1

0.2

0.3

0.4

475 rpm

Addition Rate (g g-1 s-1)

Meta

sta

ble

Zone W

idth

(g g

-1)

kn = 1.9x10-3

n = 2.5 = 1.1

7.

8.

21

Chapter 4 – Mixing and MSZW - Conclusions

Agitation, addition location, and addition rate all impact the MSZW

A minor change in the feed location resulted in significant variability in the MSZW

To ensure process robustness a slow addition rate, high agitation and optimal feed

location should be chosen

The CFD model indicates that anti-solvent incorporation is the limiting step

Flow patterns in the vessel either facilitate or hinder anti-solvent incorporation

Possible to model larger vessels and locate optimal feed location upon scale-up

An agitation dependent nucleation model was developed

Model predictions fitted the experimental data adequately

Potential to predict MSZW under different mixing conditions at different scales

22

Introduction 1







23

Chapter 4 – Growth and Consistency - Goals

Identify conditions under which FBRM and

ATR-FTIR trends are repeatable

Understand crystallization mechanism with

FBRM and PVM

Combine ATR-FTIR supersaturation with

FBRM growth rate to elicit growth kinetics

Studying Process Consistency

24

ATR-FTIR measures the liquid phase concentration over time By combining concentration trends with know solubility values –

supersaturation may be monitored

0 600 1200 1800 2400 3000 36000.5

1.0

1.5

2.0

2.5

0.1

0.2

0.3

0.4

Water Run 1 Water Run 2Water Run 3 Benzoic Run 1

Time(s)

Wate

r C

once

ntr

ati

on (

g/g

)

Benzo

ic A

cid C

once

ntr

ati

on (

g/g

)

0 600 1200 1800 2400 3000 3600

-0.12

-0.09

-0.06

-0.03

0.00

0.03

0.06

run 1

run 2

run 3

Time (s)

Supers

atu

rati

on (

g/g

)

Studying Process Consistency

25

FBRM monitors the rate and degree of change to the particle count and dimension Crystal growth and nucleation is consistent across experiments FBRM trends indicate an initial primary nucleation event followed

by growth

0 600 1200 1800 2400 3000 36000

200

400

600

800

1000

1200

1400run 1

run 2

run 3

Time (s)

#/s

(1-1

0 m

icro

ns)

0 600 1200 1800 2400 3000 36000

100

200

300

400

500

600

run 1

run 2

run 3

Time (s)

#/s

(100-1

000 m

icro

ns)

Point of nucleation

Inflection point: primary nucleation complete

Nucleation zone

Growth zone

Understanding crystallization mechanism

PVM in situ images provide instant size and morphology information

Few fine crystals and little agglomeration after 30mins – growth dominates

Mechanism of primary nucleation followed by growth is somewhat validated

Needle width appears to be 20-80µm; Needle length appears to be 150- 500µm

Correlating FBRM and PVM

FBRM distributions taken after 30mins again highlight consistency Unweighted distribution may be a good track of crystal width –

mean~50µm

Square weighted distribution may be a good track of crystal length – mean~180µm

1 10 100 10000

1

2

3

4

5

6

7

8

run1 t = 30 mins

run2 t = 30 mins

Chord Length (microns)

#/s

square

weig

hte

d

1 10 100 1000 100000

10

20

30

40

50

60

70

80

90

100run1 t = 30 minsrun2 t = 30 minsrun3 t = 30 mins

Chord Length (microns)

#/s

Crystal width? Crystal length?

Estimating Growth Rate - FBRM

Crystal growth is tracked by trending the square weighted mean Considering the rate of change of this statistic a growth rate can be

calculated Growth is initially fast but slows over time as supersaturation is

consumed

1300 1800 2300 2800 3300 3800

-0.1

0.0

0.1

0.2

0.3run 1

run 2

run 3

Time (s)

Square

Weig

hte

d M

ean G

row

th

Rate

(m

icro

ns s

-1)

0 600 1200 1800 2400 3000 36000

50

100

150

200

250

300

350

400run 1

run 2

run 3

Time (s)

Square

Weig

hte

d M

ean C

hord

Length

(m

icro

ns)

Averaging over Three Runs

Supersaturation and growth rates are averaged over three runs Consistent smooth trends are generated These can be combined to generate growth rate kinetics

0 600 1200 1800 2400 3000 3600

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

Time (s)

Avera

ged S

upers

atu

rati

on (

g/g

)

0 600 1200 1800 2400 3000 3600

-0.1

-0.05

0

0.05

0.1

0.15

0.2

Time (s)

Avera

gaed G

row

th R

ate

(m

icro

ns

s-1

)

Overall Growth Rate Kinetics

Supersaturation is plotted against the FBRM growth rate to estimate kinetics The growth order of 1.1 is typical of organic systems

-0.005 0.000 0.005 0.010 0.015 0.020 0.025 0.0300

0.05

0.1

0.15

0.2

0.25

Experimental

Model

Supersaturation (g/g)

Gro

wth

Rate

MS

QW

( m

icro

ns s

-1) G = 7.8ΔC1.1

31

Chapter 5 – Monitoring and Growth - Conclusions

Suitable parameters were chosen to ensure a consistent process

ATR-FTIR showed consistency in desupersaturation

FBRM showed consistency in crystal nucleation and growth

Crystallization mechanisms were revealed using FBRM and validated by

PVM

FBRM shows an initial primary nucleation followed by slow crystal growth

PVM images after 30 mins confirm large well formed crystals with few fines

The unweighted and square weighted distributions track crystal width and length

respectively

In situ growth rate kinetics were estimated using ATR-FTIR and FBRM

Potential to implement feedback control using this method

Possible to include breakage, agglomeration, secondary nucleation terms in

model

32

Introduction 1







33

Chapter 6 – Scale-up – Setup

1. Impeller Addition Location 2. Wall Addition Location 3. PVM 4. FBRM 5.

Overflow

Choose suitable process parameters for large

scale batches to mimic lab scale results

Conserve particle size

Maintain a short cycle time

Achieve similar yield

Identify optimal addition locations using CFD

model

Scale-up vessel is geometrically dissimilar

Also has baffles and a different impeller

Study process consistency at scale using in

situ tools

How do FBRM trends compare between batches?

How doe FBRM trends compare between scales?

34

CFD Model – 70L

CFD models show velocity in z-direction (up-down) at liquid surface The optimal feed location changes depending on the liquid volume At low volume the optimal feed location is close to the wall At high volume the optimal feed location is close the impeller

32 L 64 L

wall

impeller

impeller

wall


Comparison of FBRM stats across batches Fines trends prove somewhat difficult to interpret at the start of each

run Probe coating was evident at the start of Runs 2 & 3 Inadequate mixing and significant segregation was evident during Run

1

0 500 1000 1500 2000 2500 3000 3500 40000

500

1000

1500

2000

2500

3000

Run 1

Run 2

Run 3

Time (s)

#/s

(1-1

0µ

m)

Probe coating


Comparison of stats across batches The coarse counts and mean square weight are both similar Growth kinetics are similar across all batches

0 500 10001500200025003000350040000

100

200

300

400

500

600

Run 1

Run 2

Run 3

Time (s)

#/s

(100-1

000 µ

m)

0 500 10001500200025003000350040000

50

100

150

200

250

300

350

Run 1

Time (s)

Mean S

quare

Weig

ht

(µm

)


FBRM endpoint comparison On the unweighted and square weighted distribution – endpoints

are comparable Run 1 appears to be slightly different – possibly due reduced

agitation intensity

1 10 100 10000

10

20

30

40

50

60

70

80

90

100

Run 1

Run 2

Run 3

Chord Length (µm)

#/s

1 10 100 10000

2

4

6

8

10

12

14

16

18Run 1

Run 2

Run 3

Chord Length (µm)

#/s


FBRM endpoint comparison FBRM trends indicate that the growth and nucleation kinetics are

similar However nucleation occurs earlier at the 70L scale

0 500 1000 1500 2000 2500 3000 3500 40000

100

200

300

400

500

600

Pilot-ScaleLab-Scale

Time (s)

#/s

(100-1

000)

0 500 1000 1500 2000 2500 3000 3500 40000

200

400

600

800

1000

1200

Pilot-ScaleLab-Scale

Time (s)

#/s

(1-1

0)


FBRM endpoint comparison On the unweighted and square weighted distribution – endpoints

are comparable Run 1 appears to be slightly different – possibly due reduced

agitation intensity

1 10 100 10000

5

10

15

20

25

30

500mL

70 L

Chord Length µm

#/s

(square

weig

hte

d)

1 10 100 10000

0.5

1

1.5

2

2.5

3

500mL

70 L

Chord Lenth µm

#/s

(unw

eig

hte

d)


PVM endpoint comparison PVM images at both scales are comparable

70L 500 mL

41

Introduction 1







CONCLUSIONS

42

Conclusion

Chapter 3 – Solubility Measurement for an Anti-

Solvent System Using Gravimetric Analysis, ATR-FTIR

and FBRM

Simple Solubility ExpressionNovel FBRM Solubility MethodCalibration of ATR-FTIR probe

Solubility Measurement using ATR-FTIR

Gravimetric Solubility MeasurementUNIQAC Solubility Model

Chapter 4 – The Effect of Mixing on the Metastable Zone

Width in Anti-solvent Crystallization

MSZW using FBRM and ATR-FTIRImpact of Process Conditions on

MSZWMSZW Robustness and

RepeatabilityCFD Model for Process

UnderstandingModified Nucleation Kinetics

Solubility Measurement for an Anti-solvent Crystallization System Using Gravimetric Analysis, ATR-FTIR and FBRM, Crystal Growth and Design, in press

The Effect of Mixing on the Metastable Zone Width and Nucleation Kinetics In the Anti-solvent Crystallization of Benzoic Acid, Chemical Engineering Research and Design, Transactions IChemE part A, 85 (7) 945-953, 2007

43

Overview

Chapter 5 – The Use of FBRM and ATR-FTIR to Monitor Anti-

solvent Crystallization and Estimate Growth Kinetics

Process Repeatability StudyChoosing Optimal Process

ParametersIn situ Monitoring of

SupersaturationIn Situ Monitoring of Growth Rate

In Situ Estimation of Growth Kinetics

Chapter 6 – Scale-Up of Anti-solvent Crystallization

Choose Optimal Process ConditionsCFD Modeling to Reduce

ExperimentsOptimization based on Initial

ResultsProcess Similarity Achieved

Between ScalesTo Be Submitted – Journal of Crystal Growth

To Be Submitted – Chemical Engineering Science

Des O Grady Thesis Multiscale Characterization Of Antisolvent Crystallization

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