PMT222 Tups Vortrag Continuous Improvement and Process Monitoring Tools 01

Continuous Improvement and

Process Monitoring Tools

Dr. Hans Tups

Continuous Improvement and Process Monitoring ToolsDr. H. Tups2007-03-11, page 2;

Continuous Improvement and Process Monitoring Tools

Presentation Preview:

� FDA Guidance for Industry PAT

� Online Analytics

� Online Spectroscopy and SpectroBAY ®

�Drying

�Granulation

�Tableting

� Advanced Process Control and Online Analytics

� Performance Monitoring PerMonDO ®

� Six Sigma Projects


D. Christopher Watts, Ph.D.D. Christopher Watts, Ph.D.Office of Pharmaceutical Science, CDER, FDAOffice of Pharmaceutical Science, CDER, FDA

Science Seminar Series for the Office of CommissionerScience Seminar Series for the Office of Commissioner

April 9, 2004April 9, 2004

Process Analytical TechnologyProcess Analytical Technology(PAT):(PAT):

What’s in a name?What’s in a name?

http://www.fda.gov/cder/guidance/6419fnl.pdf


PATPAT = Process Understanding = Process Understanding

• A process is well understood when:

– all critical sources of variability are identified andexplained

– variability is managed by the process

– product quality attributes can be accurately andreliably predicted

• Accurate and Reliable predictions reflectprocess understanding

• Process Understanding inversely proportionalto risk

Ref.: C. Watts, FDA CDER http://www.fda.gov/ cder/OPS/PATCommissionerSem2004.ppt


PATPAT Approach: Quality by DesignApproach: Quality by Design

Focus on Process Understanding (= PAT)

• What parameters are critical to ProductQuality?– Experimental Design

• How do we monitor and analyze theseparameters?

– Appropriate Instrumentation and Visualization

• How do we control these parametersthroughout the process?

Ref.: C. Watts, FDA CDER http://www.fda.gov/ cder/OPS/PATCommissionerSem2004.ppt



BTS view: Opportunities for using PAT

[2] Test order

[3] Order

ProcessProcess

DCSDCS

EBRSEBRS

ArchiveArchive PDBPDB

InterfaceInterface

LIMSLIMS

AnalyticsAnalytics

[4] Device-

data

[5] MeasuredDatapoints

[6] Datapoints,References

[7]Datapoints,Test orders

[10] Datapoints, Test orders

[8] Analysis, References

Index

[9] Datapoints

,Analysis

[1] In Process

Testing

Proben-etikett

Proben-etikett

Legend:LIMS Lab Informat. Manag. SystemEBRS Electronic Batch RecordingPDB Production Database DCS Distributed Control SystemAPC Advanced Process ControlOnline

Analytics

APC


Traditional Analytics – Offline

Sampling Sample transport Lab analyser

� High costs for lab analysers and personnel

� Large delay of analytical information

� Not suitable for process automation


Innovative Analytics – Online

Example:ProcessChromatography withintegrated samplepreparation

� High costs forequipment andmaintenance

☺ Continuous analyticalprocess information

☺ Suitable for processautomation


Innovative Analytics – Inline

Examples:NIR-, UV-, VIS-,Raman-Spectroscopy

� Moderate costs forequipment andmaintenance

☺ Nearly real time data(~ 1 min),multiplexing

☺ Suitable for processautomation

NIR probe NIR-SpectrometerSpectroBAY ®

Light fiber

Field Analyzerhouse


Online Analytics – Online Spectroscopy

Several technologies have the capability for online applications.

200 400 800 1000 2500 20000 Wavelength [nm]

UV VIS NIR MIRUV VIS NIR MIR

Transitions: Electronic Ove rtone-Vibrational Fundamental Vibrat ional

Absorptionstrength: strong weak strong

Groups: Aromates, Chromophores CH/OH/NH-Bondings A norganics, Organics

Spectroscopic Inline / Online - Methods:

– Diode Laser- Spectroscopy– Raman- Spectroscopy– UV/VIS- Spectroscopy– Near infrared- Spectroscopy (NIR)– Mid infrared- Spectroscopy (MIR)

Spectroscopic Inline / Online - Methods:

– Diode Laser- Spectroscopy– Raman- Spectroscopy– UV/VIS- Spectroscopy– Near infrared- Spectroscopy (NIR)– Mid infrared- Spectroscopy (MIR)


Inline Monitoring of Moisture with NIR during Drying

Goal• Monitoring of moisture during drying

processes with NIR

Scope• Developing and validating quantitative

NIR-Applications for moisture content• Installing NIR-system at a dryer in a

pilot plant• Quantitative Inline Monitoring of drying

processes with NIR-Spectroscopy

Benefits• Provide real time information• Basis for process control• Ensuring endpoint concentration

Fast dryingSlow drying


Inline NIR-Spectroscopy – Polymorphic Transition

Mod 1 and SolventMod 2 and SolventMod 2

Goal• Monitoring of polymorphic transitions

during drying processes with NIR


NIR-Applications for polymorphicspecies and solvent content

• Installing NIR-system at a dryer in apharma plant

• Quantitative Inline Monitoring of dryingprocesses with NIR-Spectroscopy

Benefits• Provide real time information• Achieve increased capacities


Inline NIR-Spectroscopy – Fluidized Bed GranulationGoal • Monitoring of moisture during Flui-

dized Bed Granulation with NIRScope • Developing and validating quanti-

tative NIR-Application for moisture• Installing NIR-system at a Fluidized

Bed Granulator in a pharma plant• Quantitative Inline Monitoring of

drying processes with NIR-Spectroscopy

Benefits • Provide real time information• Achieve increased capacities

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Atline NIR-Spectroscopy – API-Content in tablets (IPC)

Goal • Atline monitoring of API-content and

optional of moisture in tablets with NIR-Spectroscopy as a IPC method during tableting


NIR-application for “API”-content in tablets

• Integrating NIR-Spectroscopy using a SpectroBAY system in the tablet quality control system RQ 100 of IMA Kilian

• Feasibility study with “mock” tablets


Atline NIR-Spectroscopy – API-Content in tablets (IPC)

Further Results • During method development we found

a density dependence within our tablets• For the density also a multivariate

model could be built • Predictions of the density could be

made with high accuracyBenefits• Non invasive• Non destructive• Improved statistics• Provide real time information• “Continuous content uniformity test”


PAT-Application: Microreaction Technology

Microreaction technology opensup a new outlook for novel andinnovative reaction processes.Ehrfeld Mikrotechnik BTS GmbHoffers a portfolio of modularmicroreaction technology

components:

� several types ofcontinuous micro reactors

� ultra-fast mixer,

� highly effective heat exchanger


PAT-Application: Microreaction Technology

in collaboration with partnersEhrfeld Mikrotechnik BTS GmbHoffers also analytical micro sensordevices for PAT-applicationsduring micro reaction processes:

� micro NIR flow cell

� ATR probe

� micro pH-probe

� conductivity sensor*

* under development


SpectroBAY ® - a modern online spectroscopy system

From our perspective the benefitsof Online-Spectroscopy are:

• real time information

• multiplexer for several measuring points

• simultaneous monitoring of several components at each measuring point

• direct analysis of chemical compositions

• basis for process control

NIR-spectra of a batch polymerisation

KPI # 1KPI # 2

KP

I # 2 mg / g

KP

I # 1

m

g / g



Suitable for many applications:

� analysing a whole production area (raw materials,

reaction, separation, final products)

� concentration monitoring in organic solutions

� online reaction monitoring of polymerizations

� moisture measuring in liquids, powders, granulates,

active ingredients and tablets

� online reaction monitoring of API synthesis

� online monitoring in several unit operations (drying,

mixing, agglomeration, ...) during a drug production

decreasing water content



SpectroBAY is a modern online spectroscopy

system with the following features:

� a proved spectroscopic system

� robust process spectrometer

(e.g. MATRIX-F, Bruker Optics)

� Multiplexer for 6, 13 or 20 fiber-coupled

measuring cells or probes

� Industrial standard PC and PLC

� Analyser Result Transfer Software (ARTS)

� Several DCS-interfaces available (current loop,

bus protocols, profiNet, file transfer to server)



BTS view: Opportunities for using PAT

[2] Test order

[3] Order

ProcessProcess

DCSDCS

EBRSEBRS

ArchiveArchive PDBPDB

InterfaceInterface

LIMSLIMS

AnalyticsAnalytics

[4] Device-

data

[5] MeasuredDatapoints

[6] Datapoints,References

[7]Datapoints,Test orders

[10] Datapoints, Test orders

[8] Analysis, References

Index

[9] Datapoints

,Analysis

[1] In Process

Testing

Proben-etikett

Proben-etikett

Legend:LIMS Lab Informat. Manag. SystemEBRS Electronic Batch RecordingPDB Production Database DCS Distributed Control SystemAPC Advanced Process ControlOnline

Analytics

APC


26

Manufacturingprocess

Control function

On-line monitoringof critical process

parameters

Process control

Process feedProcessoutput

Closed loop control(process

parameters only)

TemperatureTime

Pressureetc.

Future control philosophyFuture control philosophy

Ref.: D. Rudd, GlaxoSmithKline


Advanced Process Control

� Conceptual design of control structure and advanced process control concepts

� Controller performance optimization

� Dynamic optimization and control of unit operations (reactors, separation units, ...)

� Control of coupled units and complete production plants

� Optimization and automation of plant start-up, load change, and grade change procedures

X

XTIC002

FIC003

FIC007

FIC004


Controller

Advanced Process Control and Online Analytics

Online data of chemical composition are essential for an integrated automation of chemical and pharmaceutical production processes.

Examples:

� Quality control for reactors and separation steps (e.g. distillation, crystallization, drying).

� Exact determination of reaction end points.

� Specific characterization of end products.

Controller


combinationshybrid modelshybrid models

Performance Monitoring – Methods and Tools

monitoring toolsmonitoring tools KPIsprocess data laboratory data

based on first principles (heat / mass transfer etc.)

rigorous modelsrigorous models heuristic modelsheuristic models

PCA, neural nets (NN), data mining tools, SPC


Performance Monitoring

EquipmentEfficiency

EquipmentAvailability

ControllerPerformance

EnergyUsage

ProductQuality

PlantCapacity� Calculation and visualization of process

KPI (energy, yield, ....)

� Calculation and visualization of asset KPI (heat exchangers, controllers, ....)

� Data reconciliation (e.g. for material accounting)

� Soft sensoring (fouling, plugging, selectivity, conversion, ....)

� Sensor checking, trend detection

� Prediction of equipment lifetime

� Optimization of process conditions, predictive maintenance


Capacity Yield Energy Environment Quality Reliability

Potential Assessment(a quantitative “reality check”)

Improvements

PLUS

Monitoring

D e f i n e

M e a s u r e

A n a l y s e

I m p r o v e

C o n t r o l

BU

/ B

TS

Par

tner

s hip

A step-by-step way to realize efficient production:

assess, improve and monitor

Six Sigma Projects


Six Sigma Projects - Project Execution

Phase IDefine

Measure

• Identify customer’s needs• Identify relevant KPIs and control objectives• Perform “reality check”• Estimate economic benefit

� Milestone 1: Project proposal• Analyse system in detail• Identify performance impacting parameters• Design and customize methods and tools

� Milestone 2: Working plan• Implement monitoring and control functions• Train plant personnel• Integrate into workflow• Monitor and sustain improvement

Phase IIAnalyse

Phase IIIImproveControl


PAT-Application: Plugging Detection

Monitoring ScreenMonitoring Screenflow rates

valve position

remaining „life time“

pluggingindicator

• Early detection of mixer plugging to avoid shut down

• Continuously calculate „plugging index“ based on flow rates / valve positions

• Predict remaining „life time“• Set alarm when necessary

• Avoid shut down by timely cleaning

• Increase plant availability

Goal

Benefit

Scope


PAT-Application: Reaction Monitoring

QIQI

QIQI

EDnBA

CBA

+→+→+

measurement errormeasured

concentrations

Reconciledconcentrations

• Achieve precise reactor control

• Minimize measurement errors by data reconciliation based on rigorous process model

• Visualize reconciled values online• Control reactor based on

reconciled concentrations

• Increased selectivity due to optimal conditions

• Identify faulty measurements

Goal

Benefit

Scope


PAT-Application : Batch Monitoring - Yield

Goal

• Reduce batch to batch yield variations

Benefit

Scope• Evaluate data from electronic

batch recording system• Apply multivariate statistics to

identify yield related KPI• Define and implement „Golden

Batch“ rules for KPI

• Establish cause-effect relationship• Improve operating conditions• Achieve consistent yield



Conclusion:With online analytics and process automation we enhance

theperformance of our chemical and pharmaceutical productionprocesses and contribute to the PAT-Initiative of FDA

� Increasing plant capacities and production yields

� Reproducible product quality within specification limits

� Reducing operational costs

� Reducing offline analytics in the laboratories

� Contribute to operational and environmental safeties



„If you can‘t measure it,

you cannot improve it !“

[email protected]: +49 175 [email protected]

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PMT222 Tups Vortrag Continuous Improvement and Process Monitoring Tools 01