new technologies for holistic pharmaceutical creation€¦ · holistic pharmaceutical process...

Paul Barton, Richard Braatz, Steve Buchwald, Klavs Jensen, Allan Myerson, and Bernhardt L. Trout

Raymond F. Baddour, ScD, (1949) Professor of Chemical Engineering, MIT

Director, Novartis-MIT Center for Continuous Manufacturing

New Technologies for Holistic Pharmaceutical Creation

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Current State

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Current State

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Compare with the 1950’s

1950’s Today

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRw&url=http://www.nordmark-pharma.de/en/company/milestones.html&ei=yEvqVJiAM4yZgwTzsICwAQ&psig=AFQjCNG8pFCGApR6Azf_vOZgHLmB63ziTw&ust=1424727321057335

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Compare with Automotive industry

1950’s Today

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Pharmaceutical Products

Discovery Development Manufacturing

Current approach

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Product Development: Compare with the Electronics Industry

Need to develop product and process together!

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Holistic Pharmaceutical Process Development


Old approach

Discovery incl. Developability,

Manufacturability Development Manufacturing

New approach: break down the barriers

more up front loading of research new technologies

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Aggregation Is a Major Quality Issue: Development

Often high concentrations are desired, 200 mg/ml+.

Desired shelf life 1-2 years.

11 11

Cell Culture Harvest

Low-pH Viral Inactivation

Viral Filtration

Protein A Capture

Polishing Step(s)

Formulation

Fill/Finish

0.5% to 25% of the product can be in the form of soluble/insoluble aggregates due

to high fermentation titer and elevated temperatures

Harsh elution and viral inactivation conditions can induce extensive

soluble/insoluble aggregation formation

Aggregates place an enormous burden on downstream purification steps due to clogging and separation difficulties

Formulation development is a costly and time consuming task, address aggregation

Product can have a relatively short shelf life if high concentrations are required

Gottschalk, U., ed. Process Scale Purification of Antibodies. 2009

Aggregation Is a Major Quality Issue: Manufacturing

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Step Unit Operation Yield Total

Yield 1 Centrifugation 85% 85% 2 Depth Filtration 85% 72% 3 UF/DF 95% 69% 4 Protein A Chrom. 90% 62% 5 Virus Inactivation 98% 61%

6 Ion Exchange

Chrom. 95% 58% 7 Polishing Chrom. 95% 55% 8 Viral Filtration 98% 54% 9 UF/DF 98% 52%

10 Steril Filtration 98% 51%

Typical yields range from 40% to 75%

Most product loss occurs during cell culture harvest (Steps 1-3) • Yield can be improved if

product does not form insoluble aggregates

Downstream purification (Steps 6-7) yields and costs can be improved if aggregation is kept at a minimum during prior steps

Gottschalk, U., ed. Process Scale Purification of Antibodies. 2009

Aggregation Is a Major Quality Issue: Manufacturing

13

Development and Manufacturing Issues: Address During Discovery!

Protein aggregation is the most common and most problematic form of protein degradation

Aggregation Immunogenicity

High concentration monomeric

antibody solution, 200 mg/ml +

Manufacturing failure

Limitation on product delivery route

storage

Altered serum half-life

Reduction of functional activity

Hydrophobic-hydrophobic interactions drive aggregation

Develop methodology to detect and engineer out.

14

Hydrophobicity scale mapped onto antibody structure

• There are many hydrophobic residues that are exposed

Hydrophobic

Hydrophilic

Hydrophobicity scale

There are many exposed hydrophobic residues on the protein surface.

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SAP identifies exposed hydrophobic patches

• RED regions are highly hydrophobic dynamically exposed patches

• BLUE regions are highly hydrophilic dynamically exposed patches

Hydrophobic

Hydrophilic

SAP scale SAP scale Hydrophobicity scale

SAP at

R=5Å

SAP at

R=10Å

+0.5

-0.5

+0.5

-0.5

RED regions are highly hydrophobic dynamically exposed patches. BLUE regions are highly hydrophilic dynamically exposed patches.

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Mutation of SAP predicted aggregation prone regions

4 sites with high SAP values selected for mutations.

These sites are mutated to more hydrophilic residues.

variants generated

A1: L235K

A2: I253K

A3: L309K

A4: L235K L309K

A5:L234K L235K

SAP scale

+0.5

I253

L234

L309

L235 Mutational sites

engineered

-0.5

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Validation of SAP Technology

Reduction in aggregation was measured by SEC-HPLC All mutants lead to decrease in aggregation

A1: L235K

A2: I253K

A3: L309K

A4: L235K L309K

A5: L234K L235K

Temperature = 58 °C Concentration = 150 mg/mL 20 mM His buffer

Chennamsetty, N. et al., PNAS 2009.

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Create “Biobetters” with Enhanced Stabilities

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mAbs Patent Expiry

US sales

Formulation Dosage Delivery

Rituxan (Genentech)

2015 $2.6B Liquid 10 mg/mL

650 mg / week IV infusion

Herceptin (Genentech)

2015 $1.4B Solid 21 mg/mL

140-420 mg / 1-3 weeks

IV infusion

Avastin (Genentech)


700 mg / 2 weeks

IV infusion

Erbitux (Bristol-Myers Squibb)


430 mg / week IV infusion

Rituxan, Avastin, Herceptin, and Erbitux have been selected as targets based on their current formulation, and delivery routes, their high SAP values, and their patent expiry date.

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Application of SAP Technology to Rituxan®

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Rituxan Fab region with aggregation hotspots in Red

Spatial Aggregation Propensity Study of Rituxan

L178H

A9L & I10L

Y101H*

V59L

Y101H*

L153L V3L

Front Back Probe Radius = 5 Å

*Located in the CDR-H3 Loop

Antigen Binding Region Hinge

region Hinge region

SAP scale

+0.5

-0.5

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Aggregation propensity of Rituxan® Variants

N° 1 2 3 4 5 6 7

Chain L L L L L H H

Res. # 3 9 10 59 153 178 101

Residue Val Ala Ile Val Leu Leu Tyr

Mut. Gln Ser Ser Ser Asp Ser Ser

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Binding Affinity of Rituxan® Variants

• Binding to CD20: None of the mutations

outside of the function one in the CDR influence

antigen binding Mutation affecting

functionality Frac

tion

Antig

en b

ound

[Ab] (nM)

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Viscosity ranking of mAbs using SCM

The above dataset includes IgG1, IgG2 and IgG4. Viscosities of 100 mg/ml mAb were measured under

heterogeneous conditions.

0

50

100

150

200

250

300

350

400

0 500 1000 1500 2000 2500

Visc

osity

[mPa

-s]

SCM Prediction

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Old approach





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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

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Our Definition of “Continuous” (ultra QbD)

Flow

Integration (end to end)

Systems approach

Integrated control strategy

“Continuous” = Quality

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DATA DERIVED FROM TRIAL-N-ERROR EXPERIMENTATION

DECISIONS BASED ON UNIVARIATE APPROACH

MVDA MODELS EMPIRICAL UNDERSTANDING

MECHANISTIC UNDERSTANDING

1st Principles

Process Understanding Pyramid: Understanding Quality

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Comparing Design Space and Feedback Control (both consistent with Quality by Design) Braatz group

Design-space methods: • Strategy based on operation

within a fixed parameter space • Applicable to each continuous

process unit operation • Complicated to apply to an entire

integrated pharmaceutical manufacturing plant

• Feedback methods: • Control strategy based on

feedback to a “parameter space”

• Easier to scale up • Design space does not need to

be exhaustively validated a priori

• Necessary for integrated manufacturing

By enabling the manufacturing of higher quality product, feedback control is preferable for real-time release

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Integrated control implemented on continuous pilot plant

S. Mascia, P.L. Heider, H. Zhang, R. Lakerveld, B. Benyahia, P.I. Barton, R.D. Braatz, C.L. Cooney, J.M.B. Evans, T.F. Jamison, K.F. Jensen, A.S. Myerson, and B.L. Trout. End-to-end continuous manufacturing of pharmaceuticals: Integrated synthesis, purification, and final dosage formation. Angewandte Chemie, 52(47), 12359-12363, 2013

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Integrated control implemented on continuous pilot plant from Richard Braatz and Paul Barton

D2

D1

R2

R1LC LC

M1 M2 S1

C1 C2

W1

LC LC

C3 C4

LC

LC LC

S3S4 W2

M3 M4

M5

S5 S6 E1 CS

CAT

A

B

S2

S1

S3

S1

PU1

PU2

PU4

PU3

S1

S1

S1

C

D

E

S1

EX1

EX2FP

LC

S1

FCsp

FT

FCsp

spsp

sp

FCsp

CC FT

CTFC

FCsp

TC

sp

spsp

FCsp

DCsp

sp

S1RC CC sp

DC

LC

sp

1CATA B I+ ←→

1 2 BPI C I P+ → +

2I E API+ →

First-principles dynamic models were built for each unit operation (UO) as they were developed

Models were validated and then placed into a plant-wide simulation

Plant simulation used to design UO & plantwide control strategy

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Integrated control implemented on continuous pilot plant from Richard Braatz and Paul Barton

Met all purity specs in Summer 2012

Currently designing controls for a biologic drug manufacturing process (BioMAN)

D2

D1

R2

R1LC LC

M1 M2 S1

C1 C2

W1

LC LC

C3 C4

LC

LC LC

S3S4 W2

M3 M4

M5

S5 S6 E1 CS

CAT

A

B

S2

S1

S3

S1

PU1

PU2

PU4

PU3

S1

S1

S1

C

D

E

S1

EX1

EX2FP

LC

S1

FCsp

FT

FCsp

spsp

sp

FCsp

CC FT

CTFC

FCsp

TC

sp

spsp

FCsp

DCsp

sp

S1RC CC sp

DC

LC

sp

1CATA B I+ ←→

1 2 BPI C I P+ → +

2I E API+ →

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Focus on New Technologies

Want leaps in improvement, not incremental steps.

Exploit new technological opportunities that come with “Continuous,” while also overcoming new challenges.

Open up mental frameworks for mindset change.

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Examples of New Continuous Technologies Quality

Chemistry

Crystallization: API on Excipient

Direct Processing to Final Dosage Form

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Chemistry



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Minimize isolation and handling of sensitive aryl hydrazine intermediates Tandem multistep process decreases synthetic manipulation necessary Low catalyst loadings and mild reaction conditions Methodology used in CHAD (WSJ) as an alternative route for an unstable ArNHNH2 intermediate

Pd-Catalyzed Cross-Coupling with Hydrazine in Continuous Flow: Functionalized Heterocycles: Steve Buchwald Group

DeAngelis, A.; Wang, D. H.; Buchwald, S. L. Angew. Chem. Int. Ed. 2013, 52, 3434

Safety: Hydrazine-transition metal or

hydrazine-oxidant combinations present a significant explosion hazard

Hydrazine is highly toxic

Flow Advantages: By utilizing continuous flow

technology, the safety issues are decreased

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Chemistry



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Goal and Challenges

•How can a given substrate be selected for a given API? •How can “secondary nucleation” and other bulk nucleation events be avoided?

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Challenges

•How can “secondary nucleation” and other bulk nucleation events be avoided?

•Need more gentle stirring. •Need to control supersaturation more carefully.

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Continuous Fluidized Bed Crystallizer (FBC)

Must set and control very carefully the supersaturation ratio.

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4 Liter Vessel

3 peristaltic pumps

Nicolet 6700 FTIR

from Thermo Electron

Custom built glass

crystallization column from Ace Glass

ZnSe Dipper 210

Immersion Probe from

Axiom Analytical

• Gentle mixing

• Recycle

• Tight control of concentration

Continuous Fluidized Bed Crystallizer (FBC)

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Operation of FBC: Quality Control via Model

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Resulting Crystals

API : Acetaminophen Excipient: D-Mannitol

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Concentration Profile + Loading Control

Run #1

Run #Ending Temperature

(°C)Starting Concentration

(mg ACE / g EtOH)Excipient Size

(m2/g)Steady State Concentration

(mg ACE / g EtOH)Steady State

SupersaturationDrug

Loading

1 15 196.4 0.0343 176.2 0.024 17.41 12 196.4 0.0343 166.6 0.028 23.5

2 15 196.5 0.0976 175.8 0.021 17.82 12 196.5 0.0976 169.8 0.047 21.7

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Direct Compression and Friability Testing

• Direct Compression • Needed to add MCC and MgSt • Friability test accepted! (< 1%)

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Dissolution

0

20

40

60

80

100

0 20 40 60 80

Wei

ght %

Dis

solv

ed

TIme (minutes)

Criteria: Not less than 80% of Acetaminophen is dissolved in 30 minutes: Passed!

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Chemistry



49

Controlling API nucleation by tuning the nanopore shape in polymer excipients

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

Control of Morphology and Polymorph + Processing

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

Crystal orientation verified by XRD

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From Films to Tablets: Equipment with IMA

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Electrospinning of Drug and Excipient

Dissolve drug and polymer in solvent

1) 2) Electrospin to produce fibers

3) Process mat into tablets

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Nano-Crystallization in Emulsions in Hydrogel Particles (Prof. Pat Doyle)

Eral et. al. Crystal Growth & Design, 14, 2073 (2014)

Hydrated Particles Dried Particles Light Microscopy SEM of Nano-crystals

Direct Compression

CaCl2 recycle

56



Old approach





58

Automated screening and optimization with discrete variables : Klavs Jensen group

Brandon Reizman

Online HPLC Analysis

Reagent A Reagent B Reagent C Online

Reacted Slugs Mixing Zone Reactor

Real-time Feedback Algorithm

Inert Carrier Phase

Manipulation of Discrete and

Continuous Variables

Choose New Expts that Minimize

Uncertainty in Optimum x3

x2 x1

xk

xl

yp

f(x,y)

Construct Discrete Variable

Response Surfaces

x* Optimal

Experiment

Initialize with Standard Design of Expts

x3

x2

x1

59

Traditional optimization treats discrete and continuous variables separately: Klavs Jensen group

But this is problematic when discrete and continuous variables interact

With the one-variable-at-a-time approach, a screen at low T would miss identifying B as the better discrete variable With enumeration, we may waste many

experiments resolving the maximum for B

T

Yiel

d

A

B

Screen Here?

x1 x3

x2 One variable at a time…

y2

y1

Enumerate everything!

For continuous variables For discrete variables

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Automated screening platform with feedback: Klavs Jensen group

Choose New Expts that Minimize

Uncertainty in Optimum x3

x2 x1

xk

x

yp

f(x,y)

Construct Discrete Variable

Response Surfaces

x* Optimal

Experiment

Initialize with Standard Design of Expts

x3

x2

x1

66

Suzuki-Miyaura cross-coupling optimization in presence of unstable boronic acid and product: Jensen group

+2 equiv DBU in THF

Palladacycle-Ligand?

T = 30oC-110oCtres = 1 min-10 min

1.5 equivN N

Loading = 0.5%-2.5%

5:1 THF:H2O

B(OH)2

BocN

Cl

BocN

Catalyst Max Yield* Optimal TON Symbol XPhos OMs 99% 88.7 SPhos OMs 95% 65.0 RuPhos OMs 90% 61.7 XPhos Cl 88% 42.2 XantPhos OMs 73% 29.0 PCy3 OMs 54% 31.7 PPh3 OMs 34% 18.7 PtBu3 OMs 27% 15.6

Optimum TON Conditions 1.0% XPhos OMs T = 97ºC tres = 4.7 min TON = 88.7 Yield* = 90%

0

200

400

600

0.51

1.52

2.53

40

60

80

100

120

tres (s)

Loading (mol%)

T (o C

)

0

20

40

60

80

100

120

TON *-Based on aryl halide conversion

Engaging the Broader Community

69

CM Meeting at MIT—May 20-21, 2014 Next meeting September, 2016

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International Symposium on Continuous Manufacturing of Pharmaceuticals

~200 Attendees from Industry, Regulatory (FDA, EMA), Academia, Equipment Vendors

8 White Papers Presented—Audience/Panel Discussion

Published in J. Pharm. Sci, March, 2015

Keynote address: Janet Woodcock, Head of CDER, FDA

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Drug Making Breaks Away From Its Old Ways ‘Continuous-Manufacturing’ Process Can Improve Quality Control, Speed Output

By Jonathan D. Rockoff Feb. 8, 2015 8:07 p.m. ET For decades, drug makers have used cutting-edge science to discover medicines but have manufactured them using techniques dating to the days of the steam engine….

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Acknowledgements

Novartis Pharmaceuticals, esp. Markus Krumme

MedImmune

Pfizer

Singapore-MIT Alliance

Colleagues at MIT, esp. Allan Myerson, and around the world

Students, Post-docs, and Researchers….

new technologies for holistic pharmaceutical creation€¦ · holistic pharmaceutical process...

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