4th international conference on process analytical technologies in organic process r&d brussels...

PAT and Process Control: Hybrid Real-Time

Technologies for Enhanced Chemical

Development

Dominique Hebrault

Sr. Technology & Application

Consultant

Brussels, March 17-18, 2009

1

Presentation Outline

Introduction

- PAT

- Process Control

Case Studies

- Real Time In Situ Reaction Monitoring with ReactIR™

- Kinetics, Scale-up, and Process Safety with RC1e, and ReactIR™

- Crystallization with FBRM®, PVM® and ReactIR™

- Experiment Design, Data Acquisition, Analysis with Enhanced

Software Tools

2

Introduction

Organic Synthesis Lab at

the turn of the century…

…which century?

3

Introduction

FDA’s View of Process Analytical Technologies

Process Analytical Technology (PAT)

- A system for designing, analyzing, and controlling manufacturing

- Through timely measurements of critical quality and performance

attributes of raw and in-process materials and processes

- With the goal of ensuring final product quality

PAT Fundamental Tenets

- Quality cannot be tested into the product; it should be built-in or should

be by design

PAT Goals

- Enhance understanding and control of processes

PAT tools can be categorized as:

- Process analyzers

- Process control tools

- Multivariate tools for design, data acquisition and analysis

- Continuous improvement and knowledge management tools

PAT tools are used:

- Process development

Process monitoring to develop mechanistic understanding

Statistical DOE and model building to enhance process

understanding

Use of risk analysis in establishment of design space

- Manufacturing

4

Introduction

Scale-up

MonARC

Understanding

ReactIR™ iC10

API Development Production APIScale up

Introduction

PVM® in the labFBRM® in the lab FBRM® in the plant

Optimization

ReactIR™ 45

RTCal™ for real-time

reaction calorimetry at lab scale

Production

Poor temperature control

– Side reactions, slow kinetics

– Supersaturation control issues → broad distribution, impurity, polymorph

Manual addition

– High reagent concentration → by-products

– Supersaturation spikes → oiling out

Poor mixing

– Slow reaction

– Concentration gradient→ side-reaction

– Solid breakage, attrition

Introduction

Reduce risk of experimental error

Reproducibility, traceability, data

logging, modeling

7


Introduction

- PAT

- Process Control

Case Studies





Software Tools

Development of a Safe and Scalable

Oxidation Process for the Preparation of

6-Hydroxybuspirone

Introduction

Active metabolite of Buspirone,

manufactured and marketed as Buspar,

employed for the treatment of anxiety

disorders and depression

Multi Kg amount needed for clinical dev.

Process lack of ruggedness and

unreliable product quality

Source: Daniel J. Watson,* Eric D. Dowdy, Jeffrey S. DePue, Atul S. Kotnis, Simon Leung, and Brian C. O’Reilly, Bristol-Myers Squibb

Pharmaceutical Research Institute, NJ, USA, Organic Process Research and Development, 2004, 8, 616-623; Mettler Toledo Real Time Analytics

Users’ Forum 2004, London, UK

Case Study: FTIR, PAT Tool in Pharma Development

Challenges

Monitor deprotonation of 1 for:

-More precise determination of endpoint

to minimize bis-deprotonation

-Allow for variations in the base titer,

water content, and phosphite quality


KHMDS

1677cm-1

1627cm-1 Observations

-Deprotonation complete within 5’

-Enolate anion 3 stable at -25⁰C for 12h

-Addition of P(OEt)3 before addition of

the base → no impact on IR signal

-Kinetics of enolate degradation





KHMDS

Observations

-Deprotonation complete within 5’

-Enolate anion 3 stable at -25⁰C for 12h

-Addition of P(OEt)3 before addition of

the base → no impact on IR signal

-Kinetics of enolate degradation




Challenges

Monitor deprotonation of 1 for:

-More precise determination of endpoint

to minimize bis-deprotonation

-Allow for variations in the base titer,

water content, and phosphite quality


KHMDS Improved process

-Charged the base to 1 until complete

consumption → Stable signal (1677cm-1)

-1 / THF charged back to the vessel

until the signal increased → 1-3%

excess of the starting material

(quantified FTIR)

-Result: Impurity 8 is minimized





Conclusion

-ReactIR™ allowed titration of the

correct amount of base, prevented

accidental overcharge due to

ambiguous concentration

-Implementation to the pilot plant (13Kg)

-69% yield and >99 area %, need for

recrystallization eliminated

-Robust, superior process &

crystallization thanks to the successful

use of PAT

Buspirone

Buspirone enolate




Development and Scale-up of Three

Consecutive Continuous Reactions for

Production of 6-Hydroxybuspirone

Introduction

Control base / buspirone stoichiometry is

critical to product quality

Optimization based on offline analysis is

time consuming and wasteful

Actual feed rate adjusted based on the

feedback from inline FTIR: Flow cell and

ReactIR™ DiComp probe

Case Study: FTIR as PAT Tool for Continuous Process

Source: Thomas L. LaPorte,* Mourad Hamedi, Jeffrey S. DePue, Lifen Shen, Daniel Watson, and Daniel Hsieh, Bristol-Myers Squibb

Pharmaceutical Research Institute, NJ, USA, Organic Process Research and Development, 2008, 12, 956-966; Mettler Toledo Real Time

Analytics Users’ Forum 2005 - New York

Case Study: FTIR as PAT tool for Continuous Process

Implemented startup strategy

-Start with slight undercharge of base

(feed rate) to reduce diol 8

-Flow rate increased at 1% increments

until no decrease of Buspirone 1 signal

is observed

-Base feed rate was reduced 1-3%

-Works well because enolization fast,

equilibrium reached within minutes

KHMDS




Case Study: FTIR as PAT Tool for Continuous Process

Outcome

-Ensure product quality via proper ratio

and base feed rate

-Minimize waste of starting material

-Faster reach of steady state via real-

time detection of phase transitions

-FTIR also used for enolization

monitoring during steady state

Scale-up

-Lab reactor: Over 40 hours at steady

state

-Pilot-plant reactor: Successful

implementation (3-batch, 47kg/batch)




16


Introduction

- PAT

- Process Control

Case Studies





Software Tools

An Integrated Approach Combining

Reaction Engineering and Design of

Experiments for Optimizing Reactions

Introduction

Early phase RC1e experiments to obtain

a basic understanding of:

-Enthalpy

-Kinetics

-Mass Balance

-Type of phases

Case Study: Calo for Reaction Kinetics Screening

Source: D.M. Roberge, Department of Process Research, Lonza, Switzerland, Organic Process Research and Development, 2004, 8, 1049-1053;

Mettler Toledo 15th International Process Development Conference 2008, Annapolis, USA; Chem. Eng. Tech., 2005, 28, No. 3, 318-323

Type A: Very fast, t1/2< 1 s, controlled by

mixing

Type B: Rapid, 1 s < t1/2< 10 min, mostly

kinetically controlled

Type C: Slow, t1/2 > 10 min, safety issue

in a batch mode

50% of reactions in the

fine/pharmaceutical industry could

benefit from a continuous process

(microreactors)

RC1e allows precise measurement of

reaction enthalpy

Instantaneous reaction heat is related to

reaction rate

Results: Very fast reaction

-No heat accumulation

-Dosing controlled


Source: D.M. Roberge, Organic Process Research and Development, 2004, 8, 1049-1053; Mettler Toledo 15th International Process Development

Conference 2008, Annapolis, USA; Chem. Eng. Tech., 2005, 28, No. 3, 318-323

C=C double bond oxidized / cleaved by

aqueous NaOCl catalyzed by Ru

Type A: Very fast, t1/2< 1 s

controlled by mixing

Results: Rapid reaction

-Heat signal function of dosing rate

-Reagent accumulates and reacts

after the end of the dosage

-Lower temperatures favor high

accumulation

-Higher temperatures favor formation

of side products




Quench of ozonolysis into methanol /

dimethyl sulphide

Type B: Rapid, 1 s < t1/2< 10 min, mostly

kinetically controlled

Results: Slow reaction

-Accumulation of energy > 70%

-Most of the heat potential evolves

after the end of addition

-Typically initiated by temperature

increase or catalyst addition

-Autocatalytic reaction and / or

induction period




Knoevenagel-type reaction catalyzed by NaOH:

intramolecular aromatic ring condensation

Type C: Slow, t1/2 > 10 min, safety

issue in a batch mode

Conclusion

Real time RC1e calorimetry also for early

on kinetics and safety assessment

Case Study: Integrated PAT for Industrial Scale-Up

Thorough Examination of a Wittig-Horner

Reaction Using Reaction Calorimetry

(RC-1), LabMax®, and ReactIR™

Introduction

Process not ready for industrial

development: Lack of robustness due to

poor understanding of water effect, base

form, kinetics, and thermo-dynamics

-RC1™ used for kinetic and heat

information

-ReactIR™ and LabMax® used for

quantitative kinetic simulation under

well controlled conditions

Source: Michael Grabarnick and Sharona Zamir*, Makhteshim Chemical Works Ltd., Israel, Organic Process Research and Development, 2003, 7,

237-243, Mettler Toledo 2001 RXE User Forum

Side-reaction: Benzyl phosphonate hydrolysis


Results

Heat flow from RC1™ used as a real-time

monitoring technique

Initial RC1™ and DOE study results

showed reaction is fast and yield

sensitive to base addition




-Eahydrolysis > Eastilbene_formation →

temperature↓

-Stilbene formation more sensitive to

H2O than hydrolysis → [H2O] ↓. Impact

on reaction rate constant

-Stilbene formation 2nd order versus

[BA] → [BA] ↑

Validation Run

-Stilbene formation 1st order versus

[KOH]

-Validation experiment under improved

conditions in RC1™




Process simulation

-BA/stilbene concentration

-Plant reactor temperature (Cp, heat

data from RC1)

Validation of the simulation process with

ReactIR™ and LabMax®

-Real-time concentration data, under

well controlled scaled-down conditions

-Comparison to simulated profiles: good

fit, confirmed 94% yield

-Model tested: 8 m3 production reactor

-Reactants dissolution at 50⁰C

-Tj: -10⁰C

-Once 30 < Tr < 40⁰C, aq. KOH added




Conclusion

Use of real-time analytics (FTIR, heat)

and modeling to study the mechanism of

a Wittig-Horner reaction via a thorough

kinetic and thermodynamic research

Improved large scale conditions were

obtained

Preparation of mathematical model to

plan industrial equipment: Need for a

more effective heat exchanger for yield

improvement



26


Introduction

- PAT

- Process Control

Case Studies





Software Tools

27

PVM® Technology

Particle Video Microscope

Microscope quality images, in-process and in

real-time

Characterize particle systems from 2μm to 1mm

FBRM® Technology

Focused Beam Reflectance Measurement

Track real-time changes in particles and droplets as they naturally exist in the process

Characterize particle systems from 0.5μm to 3mm

FBRM® PVM®

Case Study: Integrated PAT for Crystallization

Process Design and Scale-Up

Elements for Solvent Mediated

Polymorphic Controlled Tecastemizole

Crystallization

Introduction

Tecastemizole: Active metabolite of

histamine H1-receptor antagonist

Astemizole, 2 polymorphic forms A

(stable) and B

800L scale process history shows high

risk of not obtaining desirable polymorph:

Seed controlled to solvent mediated

interconversion

Raman spectroscopy and DSC

unsuitable for interconversion monitoring

Source: Kostas Saranteas,* Roger Bakale, Yaping Hong, Hoa Luong, Reza Foroughi, and Stephen Wald Chemistry and Pharma Sciences,

Sepracor Inc., MA, USA, Organic Process Research and Development, 2005, 9, 911-922, Mettler Toledo 2001 Lasentec® Users' Forum


Results

Interconversion rate influenced by

temperature, mixing, B agglomerate size,

initial seed composition



Water added

IR Peak Area, 1513 cm-1

Tr

Particle # / secSeeding

Challenges

Methodical study under well

controlled conditions

-Need for computer control of

batch temperature, agitation

rate, and dose control of the

antisolvent addition (LabMax® )

-Real time supersaturation

determination (ReactIR™)

-In situ particle count and size

measurements (FBRM®)


-Significant effect on interconversion

rate of hold and cooling temperature

profile following addition of water

-Nonlinear cooling profile takes advantage of the temperature rate

effect on form interconversion (4 h above 70⁰C)

-Interconversion rate-limiting step is

growth of form A




Summary and conclusion

Scale-down version of the crystallization

step performed at lab scale under well

controlled conditions with LabMax®,

FBRM®, and ReactIR™

After better crystallization understanding,

and optimization, scale-up successfully

validated at both pilot (1200L) and full-

scale manufacturing (6000L)

New profile

Old profile

Tr

Time



32


Introduction

- PAT

- Process Control

Case Studies





Software Tools

Software for Design, Data Acquisition and Analysis

Automated Lab Reactor

– Initiate and control PAT experiments

– Live drag/drop data exchange with reactor

Process Analyzers

– Control lab reactor based on trend data

– Live drag/drop data exchange with reactor

Multivariate analysis

– ConcIRT™ live algorithm:

Converts in situ FTIR/Raman

data into concentration profiles

– iC Quant™ determines

component concentrations in

an unknown mixture

Data to information software tools

– iC SafetyTM converts reaction

calorimetry data into process

safety information

Summary

- Did the reaction work?

- Understand selectivity and reactivity

- Identify intermediates or by-products

- How long did it take?

- Endpoint, initiation-point, stall-point

- Can this process be scaled-up?

- Identify key control parameters

- Understand reaction kinetics- Will it be safe?

- Measure reaction heat/enthalpy

- Determine heat capacity, heat

transfer coefficient

- Worst case scenario estimation

- Thermal accumulation and

conversion

Process chemistry challenges: ReactIR™, calorimetry and automated reactors

Summary

- Do the particles have the right

dimensions, distribution,

morphology?

- Do product scale-up consistently

meet specifications? Does it

require rework?

- How is filtration rate? How about

drying time? Is it consistent?

- Measure solubility and screen MSZ

- Understand, monitor, and control

supersaturation

- Track nucleation and growth kinetics of

crystallization

- Identify and control critical parameters

- Scale-down experiments in the lab

Crystallization development: ReactIR™, FBRM®, PVM®, automated reactors

4th international conference on process analytical technologies in organic process r&d brussels...

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