enabling technologies for the continuous manufacturing of ... · bernhardt l. trout director,...

Bernhardt L. Trout

Director, Novartis-MIT Center for Continuous Manufacturing

Professor, Department of Chemical Engineering, MIT

Enabling Technologies for the Continuous

Manufacturing of APIs: Continuous

Crystallization

2

Crystallization Process Development

Process Goals

• Purity

• Yield

• Average Size and Size Distribution

• Correct Polymorph or Pseudopolymorph

• Shape

3

Past Current > 2020

Disconnected process steps

Quality by Design

Process steps and their impact understood

Blue Sky Vision: Continuous Manufacturing

Seamlessly integrated and

well characterized processes

Road Map for Pharmaceutical Manufacturing Paradigm shifts in manufacturing and quality envisioned

Traditional

Manufacturing

4

Novartis-MIT Blue Sky Vision Integrated Continuous Manufacturing: A radical transformation

the ultra LEAN Manufacturing

From start of chemical synthesis through final pharmaceutical dosage form

MIT Massachusetts Institute of Technology

5

Our Definition of “Continuous” (ultra QbD)

Flow

Integration (end to end)

Systems approach

Integrated control strategy

6

Novartis-MIT Center for Continuous

Manufacturing

Phase 1 June 2007-May 2012

Phase 2 June 2012—June 2017

60 MIT students and post-docs

20 Novartis staff and 12 MIT Professors

from Chemical Engineering, Chemistry,

and Mechanical Engineering

Most research performed in each

professor’s lab

Dedicated facility for translational work.

7

MIT Continuous Manufacturing Facility

8

MIT Pilot Plant

Courtesy of NVS-MIT

Center

1

2 3 4 5

6

VIDEO

9

Tablets Produced in Integrated Process

10

Batch Versus Continuous Crystallization

Continuous Crystallization

• Built in flexibility for control

• Does not necessarily discharge at equilibrium

conditions

• Lower cost

• CSD is broad

• Polymorph Control?

Batch Crystallization

• Cleaning done between each batch

• Simplicity of equipment

• Narrower size distribution

• Higher cost

11

Novartis-MIT Center for Continuous Manufacturing

Important task: demonstration of end-to-end continuous manufacturing platform

Used to gain experience about integration and control

Involves multiple reactions, workup steps, crystallizations

Each crystallization presented unique challenges

12

Example 1: Optimization via Modeling of MIT Pilot Plant MSMPR

Courtesy of NVS-MIT

Center

1

2 3 4 5

6

VIDEO

13

Courtesy of NVS-MIT

Center

1

2 3 4 5

6

VIDEO

Example 1: Optimization via Modeling of MIT Pilot Plant MSMPR

14

Courtesy of NVS-MIT

Center

1

2 3 4 5

6

VIDEO

Example 1: Optimization via Modeling of MIT Pilot Plant MSMPR

15

Model for Multistage MSMPR

iiivsiT CCdLnLkM 1

3

g

s

sg

C

CCkG

b

s

sb

C

CCkB

0

Population Balance: Conservation equation for the number of crystals in a population

Mass Balance

Crystal Growth

Nucleation

ni: population density at stage i

ti: residence time at stage i

L: crystal size

Gi: crystal growth rate at stage i

B0: nucleation rate

MT i: Suspension density at stage i

C: steady state solute concentration

s: crystal density

kv : volume shape factor

Cs: equilibrium concentration

kg, g, kb, b: model parameters to

be estimated

1 iii

ii nndL

dnGt (1)

(2)

(3)

(4)

16

Kinetics Parameter Estimation

a) Convert the experimental values of CSD into Population

Density

b) Find the values of kg, g, kb, and b that minimize the objective

function F :

Fmax

0

2

exp )(min L

calc Lnn

Subject to equations (1) to (4)

where = [kg, g, kb , b ]

17

Modeling Work for Crystallization of Intermediate

Modeled how changing temperature and residence time of each stage affects purity and yield

200

300

400

500

600

70

75

80

85

90

95

200

3 0 0

4 0 0

5 0 0

6 0 0

Yie

ld,

%

Secon

d Stag

e Resi

dence

Time, m

inFirst Stage residence Time, min

71.40

74.18

76.95

79.73

82.50

85.28

88.05

90.83

93.60

Yie

ld %

Pu

rity

%

100.0

97.6 70

95

18

ALISKIREN (SPP-100) SALT C12(FUMARIC ACID)

+

C11 (SPP-100 FREE BASE)

a) HCl-gas, iPr2O

b) NaOH, Me-THF

OO

ONH2

OHHN NH2

O O

C11 92%

a) HCl-gas, iPr2O

b) NaOH, Me-THF

OO

ONH2

OHHN NH2

O O

C11 92%

. 1/2

Example 2: Tight Control of Continuous Aliskiren Reactive Crystallization

19

UV control of fumaric acid addition

C13 crystallization is very sensitive to fumaric acid/C11 ratio

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

0.3 0.5 0.7 0.9 1.1 1.3

C13 c

on

cn

etr

ati

on

in

th

e m

oth

er

liq

uo

r, m

ass/m

ass

Molar Ratio of fumaric acid/C11

ALISKIREN (SPP-100) SALT C12(FUMARIC ACID)

+

C11 (SPP-100 FREE BASE)

a) HCl-gas, iPr2O

b) NaOH, Me-THF

OO

ONH2

OHHN NH2

O O

C11 92%

a) HCl-gas, iPr2O

b) NaOH, Me-THF

OO

ONH2

OHHN NH2

O O

C11 92%

. 1/2

% C

13

(m

as

s/m

as

s)

Molar Ratio of fumaric acid/C11

20

Feed forward control

Dilute drug

substance

Water

absorption

column

Fumaric

acid feed

UV

flowcell

Reactive crystallization

Filter & wash

Solvent dilution

Density

flowcell

Drum dryer

Extrusion/ molding

Silicon dioxide

Vacuum dryer

Go P5

B

A

FR

F

21

UV control of fumaric acid addition

Tightly controlled Fumaric Acid addition by the control system can reach high yield with satisfactory crystal properties.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.5 1 1.5 2 2.5

FA

/C1

1 m

ola

r ra

tion,

Yie

ld

Time, day

Vessel 1_FA/C11 molar Ratio

Vessel 1_Yield

Vessel 2_FA/C11 molar Ratio

Vessel 2_Yield

fum

ari

c a

cid

/C11

; y

ield

Time, days

22

Starting from Isolated Freebase to final API

Continuous process- effectively telescoped into 2 steps(15 L pilot-plant scale crystallizer), 8 hours total residence time

First stage: simultaneous reaction and crystallization

Second stage: further growth and nucleation

Process Yield of 97%

Conti. Process results in significantly shorter processing time compared to batch

Example 2: Summary

There are limited studies on polymorphism in continuous crystallization

Polymorphism impacts product bioavailability and manufacturability

There are fundamental differences when moving from batch to continuous crystallization process:

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● Residence time distribution

● Steady state vs. Equilibrium

● Secondary nucleation

● Seeding Efficacy

Example 3: Control of Polymorphism in Continuous Crystallization

● No solvent mediated transformation

Polymorphism: α form (metastable), β form (stable)

Solvent: Water

Characterization: polymorph ratio (Raman, XRD), solute concentration (FTIR)

| Business Use Only 24

Case study: L-glutamic acid

α form β form

Studying the possibility to control polymorphism via manipulating stage temperature and residence time

• Residence time = 60 min, Temp = 25°C α form specific

• Polymorph specific MSMPR observed for the first time

| Business Use Only 25

*Mass Ratio= α form/ (α form + β form)

pure α form

Polymorph specific MSMPR achieved

| Business Use Only

Effect of temperature and residence time on polymorphism:

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T=25°C T=45°C

τ (min) 30 60 90 120 60 120

ML conc.

(g/kg solvent) 28.60 22.36 19.74 18.24 35.32 26.41

Polymorphism α form α form α form α form β form β form

Metastable Form Stable Form

Low Temp High Temp

Short RT Long RT

Control of steady state polymorphism

| Business Use Only

Experimental Design:

Single stage MSMPR (T = 25˚C, τ = 60min) the unseeded steady state contains pure α form

β polymorph seed added during startup:

Seeding is unable to alter the steady state polymorphism, the seeds are removed in several residence time

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Seed type β form β form β form

Seed mass 5% to MTeq 50% to MTeq 100% to MTeq

Final form α form α form α form

τwashout 4τ 7τ 9τ

Efficacy of seeding on Polymorphism

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Example 4: Heterogeneous Crystallization on Patterned Excipients

28 | Confidential

Chemical/

Biological

Synthesis

Continuous

CrystallizationTableting/

Encapsulation

API

Solution

Excipient

Continuous

Purification

API-Excipient

Composite Particles

Manufacturing process API-excipient composite particles

Widely tunable chemical, physical, and mechanical properties

Potential to enhance API bioavailability

Potential to control drug release profile

Applicable to multiple API forms

Streamlined downstream processing

Control over crystallization kinetics through heterogeneous nucleation

API properties masked by the excipient to simplify downstream process development

Advantages:

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Controlling API nucleation by tuning the nanopore shape

No pore 15nm 40nm

120nm 300nm The scale bar is 200nm

Polymer surfaces with

nanopores of various shapes

and sizes were fabricated by

Nanoparticle Imprint

Lithography (NpIL), as well as

Nanoimprint lithography (NIL)

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Growth

direction

100nm

Pores with crystals

(011

)

(100)

Empty pores

Aspirin: Crystal orientation suggests nucleation of (011) & (100) from the ledge

Scale bar is 100nm Why not (002) & (100)?

Crystal orientation verified by XRD

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Hetero-

nucleant Type

Induction

time

(τ, h)

Error

(h)

Linearity

(h)

Type A

(60° and 120°)

9.6 0.1 0.99

Type B

(80° and 100°)

13.6 0.3 0.98

Type C

(90°)

8.8 0.1 0.99

no polymer 42.7 0.8 0.99

no pattern 15.8 0.3 0.96

spheres 36.5 0.7 0.95

Nucleation of mefenamic acid in anisole on HPMC surfaces

Type A

60° and 120°

Type B

80° and 100° Type C

90°

absence of

nano-pores

spherical

nano-pores

-1.5

-1.0

-0.5

0.0

0.0 5.0 10.0 15.0 20.0

Ln (

P)

Time (h)

Type AType BType Cno polymerno patternspheres

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Publication List

1. Zhang, H.; Quon, J.; Alvarez, A. J.; Evans, J.; Myerson, A. S.; Trout, B.; Development of Continuous Anti-Solvent/Cooling

Crystallization Process using Cascaded Mixed Suspension, Mixed Product Removal Crystallizers, Organic Process

Research & Development, 2012, 16, 915–924.

2. Quon, J. L.; Zhang, H.; Alvarez, A.; Evans, J.; Myerson, A. S.; Trout, B. L.; Continuous Crystallization of Aliskiren

Hemifumarate; Crystal Growth & Design, 2012, 12, 3036–3044.

3. Wong, S. Y.; Tatusko, A. P.; Trout, B. L.; Myerson, A. S.; Development of Continuous Crystallization Processes Using a

Single-Stage Mixed-Suspension, Mixed-Product Removal Crystallizer with Recycle, Crystal Growth & Design, 2012, 12,

5701–5707.

4. Alvarez, A, Singh, A., and Myerson, A.S. (2011). Crystallization of Cyclosporine in a Continuous Multistage MSMPR

Crystallizer. Crystal Growth and Design 11, 4392-4400.

5. Wong, S.Y., Cui, Y., and Myerson, A.S., (2013). Contact Secondary Nucleation as a Means of Creating Seeds for

Continuous Tubular Crystallizers. Crystal Growth and Design 13, 2514-2521.

6. Haitao Zhang, Richard Lakerveld, Patrick L. Heider, Mengying Tao, Min Su, Christopher J. Testa, Alyssa N D'Antonio,

Paul I Barton, Richard D Braatz, Bernhardt L. Trout, Allan S. Myerson, Klavs F Jansen, James M. B. Evans* (2013).

Application of continuous crystallization in an integrated continuous pharmaceutical pilot plant. To be submitted.

7. Ferguson S., Ortner, F., Quon, J., Peeva, L., Livingston, A., Myerson, A.S., (2013). Use of Continuous MSMPR

Crystallization with Integrated Nanofiltration Membrane Recycle For Enhanced Yield and Purity in API Crystallization.

Crystal Growth and Design (in review).

8. Mascia, S., Heider, P.L., Zhang, H., Lakerveld, R., Benyahia, B., Barton, P.I., Braatz, R.D., Cooney, C.L., Evans, J.M.B.,

Jamison, T.,Jensen, K.F., Myerson, A.S., and Trout, B.L., (2013). End-to-End Continuous Manufacturing of

Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation. Angewandte Chemie International

Edition (in press).

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Acknowledgements

Allan Myerson, Richard Braatz, Paul Barton

Students, Postdocs, Staff Scientists

• Examples 1 & 2: Haitao Zhang, Justin Quon, Alejandro Alvarez, Richard Lakerveld, Sal Mascia, James Evans

• Example 3: Chris Lai Tsai-ta

• Example 4: Ying Diao, Vilamli Lopez-Mejias, Li Tan

Novartis Pharma

34

35

Thank you! Questions?

Back-up

Single Stage MSMPR: 25°C, τ=2hr

Seeding condition: 100% MTeq β seed

Polymorph transform: β α

| Business Use Only 38

Polymorph transformation in MSMPR

Pure β form α crystal found State transition

Case Study objectives:

• Study the effect of seeding

• Effect of process parameters (residence time, temperature) on steady state polymorphism and stability

Simulation methodology:

• Population balance equations (partial integro-differential equations)

• Mass balance between liquid and solids

• Method of characteristics solves PDE at steady state

• Obtain steady state yield and polymorphism

| Business Use Only 39 |Confidential

T=25°C

Cfeed

300 rpm

Polymorph dynamic simulation

Yield?

Polymorph ratio?

Single stage MSMPR, T= 25˚C and τ = 60min

Regardless of the seeding conditions, steady state

polymorphism remains unchanged (stable S.S.)

40

Simulation case 1: seeding efficacy

Dynamic Simulation Results

Different seed

concentration

Polymorph dominance at different 𝝉 was studied (25˚C):

Negligible β stable form at S.S. for 𝜏<400 mins

To reach > 50wt% stable form at S.S., 𝜏>800 mins (13 hrs)

41

Pure β

Pure α

Simulation case 2: residence time

Steady state polymorphism at different residence time

Dynamic simulation can be used to determine the S.S.

polymorphism and the S.S. stability

• Further investigate effect of temperature and residence time

• May be difficult to obtain desired form at short residence time (>13hrs

in the case of the commercial β L-glutamic acid)

Design MSMPR system to achieve desired polymorph (β

form) while reducing total residence time:

• Continuous seeding from MSMPR cascade

Metastable Form Stable Form

Low Temp High Temp

Short RT Long RT 13hrs

Stable form

dominated 42

Implications from polymorph simulations

T1 T2