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Using iCRaman, iC IR & iC FBRM to Us g C a a , C & C toUnderstand and Design an Anti-Solvent

Crystallization Process

Greg GervasioWenning Dai

4 June 2013

Outline

Project BackgroundProcess Analytical ObjectivesProcess Analytical ObjectivesForm Control & Onset of CrystallizationAnti-Solvent Crystallization Modeling

– Developing a simple Peak Height Model from 1 Experiment– Comparison of Polynomial, Multiple Linear regression and

iCQuant modelsCrystallization Kinetic Study

– Super saturation vs. Equilibrium– Particle Size Control

Scale UpConclusionsNext StepsNext Steps

Project Background

In licensed product with a poorly controlled final crystallization step.– Process consisted of dissolution of the API (Active Pharmaceutical Ingredient) in DMSO

(Dimethyl sulfoxide), Cooling to 20C then anti-solvent addition using IPA (Isopropyl alcohol). This resulted in large crystals with trapped solvents and poor flow ability that required post milling.

– By first intent GSK prefers a single solvent seeded crystallization with controlled particle size that does not require a milling stepthat does not require a milling step.

Conducted extensive solvent screen, about 30 solvents, ranging from water, alcohols, ketones, esters, ethers to solvents of aromatic, halogenated, hydrocarbon and dipolar aproticy p p

– Low solubility in almost all solvents

Lead solvents– DMSO with IPA as an anti-solvent

Aq eo s MeCN (Acetonitrile) To be sed as a back p process d e to lo er ield than that of– Aqueous MeCN (Acetonitrile) To be used as a back up process due to lower yield than that of the DMSO/IPA system

Low volume drug, therefore high yield of last stage is of important

Form controlT f f th f id f d Th fi l t b b t h t l– Two forms of the free acid were found. The final process must be robust enough to assure only the desired Form 1 is produced.

Proposed New Crystallization Process

Dissolution of Intermediate in DMSO at 80OCClarifying filtrationClarifying filtrationCool to 70OCSeed then age for 1 Hr.Controlled IPA addition over 2HrsCool to 20OCAge for 1HrFilter and wash with IPA

Process Analytical Objectives

Use PAT to confirm robust crystallization process– Onset of nucleation (seeding window)– Onset of nucleation (seeding window)

FBRM - used to determine the point of auto nucleation– Confirm desired Form during crystallization

Raman sed to monitor Form d ring the cr stalli ation processRaman - used to monitor Form during the crystallization process– API concentration relative to equilibrium concentration

DATR - used to model the saturated equilibrium API concentration at various anti solvent levelsvarious anti-solvent levels.DATR - used to monitor the dissolved APIDATR –also used to monitor the anti-solvent level

P ti l i t l– Particle size controlFBRM - used to study the particle size distribution through the crystallization

Form Control & Onset of Crystallization

Onset of Crystallization– Determine Applicable Time Window for Seeding by FBRM– Determine Applicable Time Window for Seeding by FBRM

Form Control– Collect Raman spectra of both Forms 1 and 2 solids and solution– Investigate form formation during API crystallization by Raman

Onset of Crystallization

900 000

1,000.000

700.000

800.000

900.000

500.000

600.000

10-1

50 m

icro

ns

Critical to add seeds as soon as possible after reaching 70OC

300.000

400.000

Cou

nts

100.000

200.000

50 Counts-

-5 0 5 10 15 20 25 30 35 40 45 50 55 60Minutes from reaching 70C or IPA addition

Raman Reference Spectra

Form 2

160000

180000

200000

120000

140000 Form 11631Cm-1

1608Cm-1

API Form 1

API Form 2

120000

140000

80000

100000

Dissolved in DMSO

API in Solution

60000

80000

100000

40000

60000

DMSO1618Cm-1

20000

40000

60000

20000

40000

1520153015401550156015701580159016001610162016301640165016601670168016901700

RamanShift (cm-1)

Kaiser Optical Systems / METTLER TOLEDO

Raman Monitoring for FormFour Experiments No Form 2 Formation

1630

632.5

1635

22000

24000

26000

80

90

1630

632.5

1635

120

140

25000

27500

30000

Tested two types of milled seeds and levels of impurities

Ref:FBRM counts

Ref:IPA ml

Peak Center

Smooth

Ref:Tr

1615

617.5

1620

622.5

1625

627.5

10000

12000

14000

16000

18000

20000

30

40

50

60

70

Ref:[mL]

Ref:[°C]

Ref:FBRM Counts

Peak Center

1615

617.5

1620

622.5

1625

627.5

60

80

100

12500

15000

17500

20000

22500

25000

1605

607.5

1610

612.5

1615

0

2000

4000

6000

8000

0

10

20

30

00:00:00 01:00:00 02:00:00 03:00:00 04:00:00 05:00:00 06:00:00 07:00:00 08:00:00Relative Time


1605

607.5

1610

612.5

1615

0

20

40

2500

5000

7500

10000

00:00:00 01:00:00 02:00:00 03:00:00 04:00:00 05:00:00 06:00:00 07:00:00 08:00:00Relative Time


Ref:[mL]622.5

1625

627.5

1630

632.5

1635

100

120

140

17500

20000

22500

25000

27500

30000

Ref:[mL]622.5

1625

627.5

1630

632.5

1635

60

70

80

90

100

20000

22500

25000

27500

30000

32500

[ ]

Ref:[°C]

Ref:FBRM Counts

Peak Center

607 5

1610

612.5

1615

617.5

1620

20

40

60

80

2500

5000

7500

10000

12500

15000

[ ]

Ref:[°C]

Ref:FBRM Counts

Peak Center

607 5

1610

612.5

1615

617.5

1620

10

20

30

40

50

5000

7500

10000

12500

15000

17500

1605

607.5

00

2500

00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 24:00:0Relative Time


1605

607.5

0

2500

00:00:00 01:00:00 02:00:00 03:00:00 04:00:00 05:00:00 06:00:00Relative Time


A ti l t C t lli ti M d liAnti-solvent Crystallization Modeling

Developing Simple Peak Height ModelsUsing Just 1 Experiment

First monitor Crystallization to see if peaks can be resolvedDevelop a Calibration Set Over Constant Temperature Portion ofDevelop a Calibration Set Over Constant Temperature Portion of Crystallization

– Start with a saturated DMSO/API solution, collect grab sample and measure IR at various anti-solvent levelsmeasure IR at various anti-solvent levels.

– Develop API solubility vs. anti-solvent level curve– Develop API concentration calibration– Develop anti-solvent calibration

Not required if anti-solvent level can be linked into iCIR

Typical 2Hr Anti-Solvent Addition

DMSO Peak

1.2

1.4

Peak Height to 2pt baseline (780, 1800cm-1)

00:48:53

01:21:53

01:51:53

02:18:53

02:51:53

0.8

1.0

p ( )

02:51:53

03:30:53

03:50:53

04:35:53

0.4

0.6 API PeakIPA Peak

0.2

0.0

80085090095010001050110011501200125013001350140014501500155016001650170017501800

Wavenumber (cm-1)

METTLER TOLEDO

Typical 2Hr Anti-Solvent Addition

70

80

0.30

0.351.6

Calibrate over constant temperature

API

DMSO

IPA

50

60

0.20

0.25

1.2

1.4 Seeds Added

DMSO dilutionIPA

Ref:Tr

30

40

0.10

0.15

0 8

1.0

Start IPAAPI peak

10

20

0.00

0.05

0.6

0.8

10:00:00 AM1/18/2013

11:00:00 AM1/18/2013

12:00:00 PM1/18/2013

1:00:00 PM1/18/2013

2:00:00 PM1/18/2013

3:00:00 PM1/18/2013

4:00:00 PM1/18/2013

5:00:00 PM1/18/2013

Absolute TimeAbsolute Time

METTLER TOLEDO

Collecting Solubility and Calibration Data

100

50

60

0.30

0.35

Actual API

Actual IPA

60

80

30

40

0.20

0.25

API/DMSO

IPA/(IPA + DMSO)

40

60

20

30

0.10

0.15

20

0

10

0.00

0.05

00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 24:00:00 28:00:00

Relative TimeRelative Time

METTLER TOLEDO

Un-calibrated

CurveExpert Was Used For All Correlations

Correlate %IPA to Solubility of the API in mg/ml CurveExpert

Known IPA addition vs. LC analysis

Correlate %IPA to Solubility of the API in mg/mlCurveExpert

STD 0 595937STD 0.595937

API mg/ml vs. Peak HeightCurveExpert 2rd Order Polynomial Model

%IPA vs. Peak HeightCurveExpert 3rd Order Polynomial Model

%IPA vs. IPA/(IPA+DMSO) AUCurveExpert 2rd Order Polynomial Model

Calibration Results

100

120

50

60

Actual API

Actual IPA

API Poly mg/ml60

80

30

40

IPA Poly

Pred API Sol

40

60

20

30

20

0

10

00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 24:00:00 28:00:00


METTLER TOLEDO

Comparison of Modeling MethodsCan we do better?

Polynomial curve fitting PkHt or Pk Ratio– Simple and regression can be made on a single experiment– Simple and regression can be made on a single experiment.

Multiple Linear Regression of all 3 Pk Hts– Uses more information

Partial Least Squares (iCQuant)– Requires multiple experiments

Curve Expert used for Multiple Linear Regression

iCQuant

Comparison of Modeling Methods

Calibration Set Validation Set

API IPA API IPAPolynomialRegression

Bias 0.00 0.00 -1.08 0.38

STD 0.52 0.16 1.98 0.74

Multiple Linear Regression Bias -0.0045 -0.001 -1.66 -0.32

STD 0.53 0.29 2.57 1.16

iCQuant1 Experiment2 Factors

Bias -0.0004 -0.0005 -1.13 0.61

STD 0 71 0 11 3 93 1 08acto s STD 0.71 0.11 3.93 1.08

iCQuantUsing all 4 Experiments6 F t

Bias 0.0002 0.00004 NA NA

6 Factors STD 1.13 0.36 NA Na

API Crystallization Kinetics Study y y– IPA Addition Rate

1Hr Addition Polynomial Calibration

100

120

50

60

80

Actual API

Actual IPA

API Poly

80

100

30

40

60

70

Calibration at constant temperature

IPA Poly

Pred API Sol

Ref:Tr

40

60

20

30

40

50

0

20

0

10

20

30

00:00:00 01:00:00 02:00:00 03:00:00 04:00:00 05:00:00 06:00:00 07:00:00


METTLER TOLEDO


50

60

120

140

70

80

Actual API

Actual IPA

API Poly

30

40

80

100

50

60

OutlierIPA Poly

Pred API SOl

Ref:Tr20

30

40

60

30

40

0

10

0

20

10

20

00:00:00 01:00:00 02:00:00 03:00:00 04:00:00 05:00:00 06:00:00 07:00:00


METTLER TOLEDO


120

140

50

60

70

80

Actual API

Actual IPA

API Poly

80

100

30

40

50

60

IPA Poly

Pred API Solubility

Ref:Tr

40

60

20

30

30

40

0

20

0

10

10

20

00:00:00 01:00:00 02:00:00 03:00:00 04:00:00 05:00:00 06:00:00 07:00:00 08:00:00 09:00:0


METTLER TOLEDO

3h IPA Addition

IPA additionIPA addition

Blue – Just seeded, 70CGreen – Started IPA addition, 70CRed – End of IPA addition, 70CGrey – Prior to isolation, 20C

Primarily Growth During the IPA addition

Chord Length Distributions Comparison

1h IPA addition

2h IPA addition

3h IPA addition

IPA Addition Rate Effects on API Particle Size Distributions

E i t IPA dditi F X10 ( ) X50 ( ) X90 ( )Experiment IPA additiontime (h)

Form X10 (um) X50 (um) X90 (um)

Batch 1 1 Form 1 21.2 38.2 66.8

Batch 2 2 Form 1 22.9 42.3 73.9

Batch 3 3 Form 1 20.3 38.1 67.7

Microscopy

N21437-82-P1, 1h IPA addition N21437-83-P1, 2h IPA addition

N21437-84-P1, 3h IPA addition

The Plant Scale-UpDMSO/IPA Recrystallization Process Diagram

ChCharge intermediate

and DMSO to a dissolution

Heat until complete

dissolution (78C 82C)

Clarifying filtration to a crystallizer

reactor (78C-82C) y

Cool to 70C, add seed then age

Dose anti-solvent IPA at 70 C over 2

Cool slurry to 20 C, age for >1 hr, seed, then age

for 1 hrIPA at 70 C over 2

hrsisolate and dry at 70C overnight

A robust seeded-crystallization-process for free acid (Form 1) was successfully demonstrated at the Pilot Plant settings for up to 5 kg.

Pilot Plant API Batch Summary

Batch Number Particle Size Form Yield (%)

Batch 1 n/a Form 1 92Batch 1 n/a Form 1 92

Batch 2 X10 = 25.0 um, X50 = 46.1 um, X90 = 80.1 um

Form 1 87

Batch 3 X10 = 23.5 um, X50 = 45.6 um, X90 = 81.0 um

Form 1 81

Batch 4 X10 = 28.6 um, X50 = 50.0 um, X90 = 84.7 um

Form 1 81

Batch 5 X10 = 24 4 um X50 = 49 5 Form 1 81Batch 5 X10 24.4 um, X50 49.5 um, X90 = 89.5 um

Form 1 81

Batch 6 X10 = 23.7 um, X50 = 43.7 um X90 = 76 1 um

Form 1 83um, X90 = 76.1 um

DMSO/IPA Crystallization Processes Comparison

Current Legacy Note on Legacy Process Process Process

DMSO 8 volume 6.5 volume API supersaturated in

SODMSO

Seeding Step Yes no Risk of formation of metal stableof metal stable form(s) and poor impurity purging

Particle size seeding Wet milling Limited capability control

g g p yof wet milling in manufacture sites

Product superior ok Good flowability of flowability API is of important

for formulation

Conclusions

Process– Seed at 70C and wait until concentration approaches equilibrium– Seed at 70C and wait until concentration approaches equilibrium

concentration/flat lines.– Crystallization is addition rate dependent

Primarily growth during Anti Solvent addition– Primarily growth during Anti-Solvent addition– No apparent particle size difference from 1-3Hr addition rate– Good scale up to Pilot Plant

Crystallization Monitoring– Easy 1 experiment calibration using Peak Heights and polynomial

equations

Next step

Process– Seed Size & Loading Effects on Particle Size Distribution– Seed Size & Loading Effects on Particle Size Distribution– Anti Solvent addition point

Modeling– Repeat Calibration Experiment with Pilot Plant 45P

Use increased path length DATR probeCollect more solubility data pointsExtend calibration range past end pointsAdd temperature compensation

– Collect enough experiments to try iCQuantCalibration less step addition using IR or possibly only FBRM

Questions?

Acknowledgments

Thank you for your attentionMettler Toledo for all their support and invitationMettler Toledo for all their support and invitationGSK Particle Generation, Control & Engineering GSK Pilot Plant

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