crystallization process improvement driven by dynochem process modeling. flavien susanne

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Pfizer Confidential Crystallisation improvement driven by Dynochem process modelling Flavien Susanne Chemical Engineer Moussa Boukerche, Thomas Dupont

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Page 1: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Crystallisation improvement driven by Dynochem

process modelling

Flavien Susanne Chemical Engineer

Moussa Boukerche, Thomas Dupont

Page 2: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Introduction

Crystallisation is a critical stage in the manufacture of an Active

Pharmaceutical Ingredient (API) where key attributes such as purity

together with physical and mechanical properties of the crystals are set.

Particle size distribution, polymorphic form and crystal habit, have a

direct impact on downstream processing (e.g. filtration, drying and

powder processing) and ultimately on the performance of the drug

product

Page 3: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Outline

2 case studies to illustrate the use of Dynochem to

Improve API crystallisation

1. Distillation/crystallisation process by constant anti-solvent addition

Original process performed by strip and replace cycles

Limitation and physical property issues

Improvement by control of crystallisation parameters

2. Continuous crystallisation by distillation and anti-solvent addition

Original process performed by anti-solvent crystallisation

Limitation and physical property issues

Principle, Advantage and Improvement

Page 4: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Case study 1: original process

Main issue: reliability of particle size distribution

Multiple Strip and Replace cycles (7-9 cycles)

80:20 % w/w THF:water to >95% acetonitrile

Large volume of solvent required

Long cycle time, potential decomposition of API

Concentration

by distillationAddition of

anti-solvent

Page 5: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Limitation of the process

For each addition

Variation of composition and temperature

Sudden drop of solubility and increase of supersaturation when

addition is done

Uncontrolled increased of number of particle = uncontrolled

crystallisation

Page 6: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Results

Batch to batch variability

Crystallisation highly dependant to the process variability

Different particle size distribution and physical property

Page 7: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Crystallisation by continuous distillation/addition

Transfer from Strip and Replace addition to constant addition

Control of solubility evolution by avoiding sudden changes

0

10

20

30

40

50

60

70

80

0 100 200 300 400 500

g/L

mins

batch Solubility g/L

cst Solubility g/L

1st event of crystallisation

triggered by aliquot addition

2nd event of crystallisation

triggered by aliquot addition

Page 8: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Approach and principal

Improve efficiency

Better control of anti-solvent addition, less disruption of

temperature and composition

Better control of solubility and supersaturation

Benefit

Improvement of physical property

Additional benefit

Minimise solvent use

Cycle time

Concentration

by distillation

Addition of

anti-solvent

Addition of

anti-solvent distillation

Page 9: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Concentration of solvents and

component monitored by IR

RC1MP06: Reactor for

distillation

Weight of solvent

measured

Weight of distillate

recorded

Constant feed

Equipment for POC: RC1-MP06

Page 10: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

RC1-MP06 Characterisation

Specific to reactor

Geometry, material of construction, HTF used (flow rate, Cp)

First use of the UA Dynochem estimation

Series of calibration run at different volume followed by heat up, cool

down and distillation experiments for validation

Prediction based on heat transfer and heat loss of the reactor used

0

2

4

6

8

10

0 0.5 1 1.5

UA

(W

/K)

Volume (user units)

0.085

0.035

-0.1 -0.05 0 0.05 0.1

Heig

ht (m

)

0

5

10

15

20

25

30

35

0

10

20

30

40

50

60

70

80

90

Pro

ce

ss

fluid

Insid

e

film

Insid

e

fou

ling

Lin

ing

Wa

ll

Ou

tsid

e

fou

ling

Ou

tsid

e

film

Se

rvice

flu

id

Te

mp

era

ture

% r

esis

tan

ce

Page 11: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Temperature prediction

Liquid phase

Composition prediction

gas phase composition

prediction

Model in Dynochem and prediction

Page 12: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Control of crystallisation parameters

Calculation and prediction of solubility and supersaturation

The solubility of the mixture THF:water:acetonitrile as a function

of temperature was determined experimentally using 13-run D-

optimal design

The supersaturation was calculated from the solubility

Page 13: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

POC Results

Prediction of solvent evolution

Validation of the Proof Of Concept

Page 14: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

POC Results

Repeatability from batch to batch

Similar mono modal

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

Density

dis

trib

utio

nq3*

0.4 0.6 0.8 1.0 2 4 6 8 10 20 40 60 80 100 200

particle size / µm

Page 15: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

POC demonstrated in the lab using the RC1 reactor

automated 0.8L calorimeter reactor

Transfer to the Pilot Plant reactor, conical 250L type reactor with twin jacket.

Transfer to manufacture reactor, 1500L bottom dish reactor

Transfer to Large Scale

Page 16: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Model in Dynochem and prediction

Page 17: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Extract mathematical description of heat transfer using Dynochem

Jacket Reactor

TC

r (m)outside film

wall

lining inside film

oofwlifi hhhhhhU

1111111

Large scale reactor Characterisation

Page 18: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Measure heat up and cool down curves for different volumes and stirring

speeds

Analyze dynamics of reactors with respect to heat transfer

Calculation of resistance contribution for different reactors

From lab to

large scale

Large scale reactor Characterisation

Page 19: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Prediction heat transfer model specific to Pilot Plant reactor

Geometry, material of construction, HTF (flow rate and Cp)

Heat up and cool down experiment UA and Uloss

Jacket.Temperature (Imp) (C)

Bulk liquid.Temperature (Exp) (C)

Bulk liquid.Temperature (C)

exp1 95kg Tj=60°C

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 43.527 87.053 130.58 174.107 217.6330.0

14.0

28.0

42.0

56.0

70.0

Jacket.Temperature (Imp) (C)

Bulk liquid.Temperature (Exp) (C)

Bulk liquid.Temperature (C)

exp6 166.2kg Tj=60°C

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 33.873 67.747 101.62 135.493 169.3670.0

15.0

30.0

45.0

60.0

75.0

Jacket.Temperature (Imp) (C)

Bulk liquid.Temperature (Exp) (C)

Bulk liquid.Temperature (C)

exp4 130.4kg Tj=20°C

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 41.03 82.06 123.09 164.12 205.150.0

14.0

28.0

42.0

56.0

70.0

Jacket.Temperature (Imp) (C)

Bulk liquid.Temperature (Exp) (C)

Bulk liquid.Temperature (C)

exp5 130.4kg DT=30°C

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 21.97 43.94 65.91 87.88 109.850.0

30.0

60.0

90.0

120.0

150.0

Jacket.Temperature (Imp) (C)

Bulk liquid.Temperature (Exp) (C)

Bulk liquid.Temperature (C)

exp7 166.2kg Tj=20°C

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 35.707 71.413 107.12 142.827 178.5330.0

14.0

28.0

42.0

56.0

70.0

Large scale reactor Characterisation

Page 20: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Predictive model specific to the Pilot Plant reactor

Distillation trials partial reflux and N2 sweep effect

sumof f gasv olume (Exp) (L)

Bulk liquid.Temperature (Exp) (C)

Jacket.Temperature (Exp) (C)

v apour.THF (kg)

Jacket.Temperature (C)

Bulk liquid.Temperature (C)

sumof f gasv olume (L)

constant level trial

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 30.0 60.0 90.0 120.0 150.00.0

30.0

60.0

90.0

120.0

150.0

sumof f gas (Exp) (kg)

Bulk liquid.Temperature (Exp) (C)

Jacket.Temperature (Exp) (C)

sumof f gas (kg)

Jacket.Temperature (C)

Bulk liquid.Temperature (C)

exp11 distillation from batch exp

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 24.347 48.693 73.04 97.387 121.7330.0

30.0

60.0

90.0

120.0

150.0

sumof f gas (Exp) (kg)

Bulk liquid.Temperature (Exp) (C)

Jacket.Temperature (Exp) (C)

sumof f gas (kg)

Jacket.Temperature (C)

Bulk liquid.Temperature (C)

exp10 distillation test

Time (mins)

Pro

cess p

rofil

e (

see le

gend)

0.0 32.0 64.0 96.0 128.0 160.00.0

50.0

100.0

150.0

200.0

250.0

Different distillation conditions

Match between experimental data and prediction

Large scale reactor Characterisation

Page 21: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Process transfer

Constant feed of MeCN : Flow rate between 32L/hour

Volume contained at 150L ± 10%

Variation of Cp and density affecting variation of volume

Distillation time 13h

10h time saving compare to batch for same end point

>10% solvent saving

More accurate control of solubility and supersaturation

Page 22: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Prediction of solvent evolution

Validation of the model on large scale

0

20

40

60

80

100

0 200 400 600 800

% mass solvent

mins

THFmassratio (Exp)

watermassratio (Exp)

acetonitrilemassratio (Exp)watermassratio

acetonitrilemassratio

THFmassratio

sumoffgasvolume

sumoffgasvolume (Exp)

volume distillated

Case study 1: Results and Conclusions

Page 23: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Case study 1: Results and Conclusions

Repeatability from batch to batch

Process conducted in 250L and 1500L reactors

Page 24: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Outline

2 case studies to illustrate the use of Dynochem to

Improve API crystallisation

1. Distillation/crystallisation process by constant anti-solvent addition

Original process performed by strip and replace cycles

Limitation and physical property issues

Improvement by control of crystallisation parameters

2. Continuous crystallisation by distillation and anti-solvent addition

Original process performed by anti-solvent crystallisation

Limitation and physical property issues

Principle, Advantage and Improvement

Page 25: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Case study 2: original process

Main issue: reliability of particle size distribution

Anti-solvent crystallisation

65:35 % w/w heptanes:IPAc, 11mL/g

Long cycle time, low throughput

Physical property issues (high degree of secondary nucleation)

Addition of

anti-solvent

Page 26: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

• Varying composition/volume/supersaturation

• Deliver small primary particles(<20m) that are prone to

agglomeration

• 92% yield of recovery in >600min

• Throughput ~9kg/m3.hour

Results: standard crystallisation

0.000

0.025

0.050

0.075

0.100

0.125

0.150

0.175

0.200

0.225

0.250

0.275

0.300

0.325

0.350

0.375

0.400

0.425

0.450

0.475

0.500

0.525

0.550

0.575

0.600

0.625

0.650

0.675

0.700

0.725

0.750

0.775

0.800

0.825

0.850

0.875

0.900

0.925

De

nsity d

istr

ibu

tio

n q

3*

1 2 4 6 8 10 20 40 60 80 100 200 400 600 800

particle size / µm

Batch No.

703611/30

703611/26

703611/27

% < 21.5 µm

%

65.47

75.93

80.31

D[v,0.1]

µm

1.61

1.43

1.53

D[v,0.5]

µm

7.06

5.38

6.11

D[v,0.9]

µm

328.29

357.17

107.04

D[4,3]

µm

84.38

73.46

43.41

Pfizer, Materials Science, Sympatec HELOS (H1258)

UK-453061

Neil Dawson

21 JUL 2010

Primary particles

Controlled by

crystallization

primary particles

agglomerated

during drying

0.000

0.025

0.050

0.075

0.100

0.125

0.150

0.175

0.200

0.225

0.250

0.275

0.300

0.325

0.350

0.375

0.400

0.425

0.450

0.475

0.500

0.525

0.550

0.575

0.600

0.625

0.650

0.675

0.700

0.725

0.750

0.775

0.800

0.825

0.850

0.875

0.900

0.925

De

nsity d

istr

ibu

tio

n q

3*

1 2 4 6 8 10 20 40 60 80 100 200 400 600 800

particle size / µm

Batch No.

703611/30

703611/26

703611/27

% < 21.5 µm

%

65.47

75.93

80.31

D[v,0.1]

µm

1.61

1.43

1.53

D[v,0.5]

µm

7.06

5.38

6.11

D[v,0.9]

µm

328.29

357.17

107.04

D[4,3]

µm

84.38

73.46

43.41

Pfizer, Materials Science, Sympatec HELOS (H1258)

UK-453061

Neil Dawson

21 JUL 2010

Primary particles

Controlled by

crystallization

primary particles

agglomerated

during drying

Primary particles

agglomeration

Page 27: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Concept

Design new process to enable better crystallisation

Increase the seed surface to promote rate of growth

Control the rate of nucleation Vs rate of growth

Starting volume with high seed concentration

The crystallisation is generated by addition of anti-solvent and distillation

to the right concentration solvent/anti-solvent

Continuous distillation of azeotropic solution

Continuous crystallisation

Page 28: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Model in Dynochem and prediction

Page 29: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

Continuous crystallisation

Start

No flow

Preparation of seed bed

13g API in 65g heptanes and 32g

IPAc

solubility ~6g/L

Composition and concentration

stay constant

Large surface of seed

Promote growth

Page 30: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 31: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 32: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 33: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 34: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 35: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 36: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 37: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 38: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 39: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

P-9

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 40: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 41: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

API

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 42: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

API

Continuous crystallisation

Solution of

0.5g/min

6g/min IPAC

7.5g/min

heptanes

Flow in

Start of flow in

0.5g/min API

6g/min IPAc

7.5g/min heptanes

Start of vacuum at 80mbar

T= 25.5C

Distillation rate controlled by T

Heptanes: 4.1 – 6 g/min

IPAc: 3.65 – 5.3 g/min

Page 43: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Use of Dynochem prediction for distillation

Continuous crystallisation

API

API

Page 44: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Continuous Distillation/crystallisation

P-10

Liquors

E-6

Heptane

IPAc

Solid out

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

P-8

Advantage

Control of the crystallisation by modelling

Only one reactor required for the

crystallisation

Only half Heptane required for same

conditions

Green Chemistry approach

No additional investment

existing batch reactor can be used

4 plates columns

to recycle the

Heptane

API in

solution

Continuous crystallisation

Page 45: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

1.25

De

nsity d

istr

ibu

tio

n q

3*

0.6 0.8 1.0 2 4 6 8 10 20 40 60 80 100 200 400

particle size / µm

Batch No.

120782/109/1

120782/103/3

D[v,0.1]

µm

2.24

2.71

D[v,0.5]

µm

9.06

9.84

D[v,0.9]

µm

21.95

25.31

D[4,3]

µm

10.96

12.97

UK-453,061 API - Particle size distribution

Comparison of continuous crystallisation batches isolated in an AFD

Neil Dawson

•Constant supersaturation and composition: optimisation of

crystal growth

•Bigger particles (~25m) than typical batch size

•Particles can be grown bigger if processed longer

•Particles are not prone to agglomeration

•>90%yield of recovery

•Throughput : 36kg/m3.hour

Results: continuous crystallisation

Page 46: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Conclusion

Alternative to standard crystallisation process can be

developed

Dynochem was a fantastic tool to enable new

process crystallisation development

Dynochem makes innovative thinking possible and

easy!!!

Page 47: Crystallization process improvement driven by dynochem process modeling. Flavien Susanne

Pfizer Confidential

Acknowledgment

Thomas Dupont

Moussa Boukerche

Andrew Derrick

Julian Smith

Wilfried Hoffmann

Garry O’Connor