Paving the way to process understanding

Your process analytical technology guide

pharmaCOMPETENCE

Maintenance

Asset management

Downtime management

Maximizing flexibility

Quality by design

Total quality management

Real-time product release

PAT

Right-first-time

Process knowledge

Production predictability

Ease of use

Maximizing operational efficiency

Availability

Process reproducability

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Siemens Pharma Base Camp

Supply chain excellence

Optimal asset valuation

Manufacturing excellence

Production logistics

Warehouse integration

Demand-driven supply net

Collaborative manufacturing

Overall quality excellence

Siemens Pharma Roadmap

Your routes to success

As a pharmaceutical entrepreneur today, you are moving in a difficult market landscape. Packing a need for sustainable solutions

to optimize your business, you find yourself faced with the unavoidable decision of embarking on new paths in order to conquer

new territory. With our Siemens Pharma Base Camp, we support you during this journey. By providing you with a solid base camp

for exploring new territory. There you will meet experienced scouts who have been gaining knowledge and expertise on your

Setting off for success Welcome to the Siemens Pharma Base Camp

industry for many years. And there you will be provided with the right tools, like innovative and industry-

specific automation and process engineering technology for all your crucial process steps. The possi-

bilities are there for the taking, the path to success is mapped out, and our scouts are standing by to assist

you. The time to act is now. Embark with us on a journey toward a successful future.

Achieving your goals with PAT by:

• Quickly gaining knowledge about the key variables of specific processes

• Determining the mechanism to minimize off-spec products and maximize

product yield

• Creating a high process reproducibility (consistent quality) and early identi-

fication of unsuccessful batches, based on increased process understanding

• Controlling even delicate processes 24 hours a day

• Meeting future regulatory requirements for real-time product release and

a risk-based validation approach.

Siemens leverages its expertise and experience to increase your ability to

optimally control your processes and help you produce excellent pharma-

ceutical produce efficiently – from API synthesis to packaging. With end-to-

end optimized control of your manufacturing processes, you will experience

greater flexibility and consistency. This provides a solid base for enduring

high product quality and productivity.

Choosing a proven path:

The multidisciplinary Siemens PAT approach

Lead-time reduction and manufacturing performance improvement in pharma-

ceutical manufacturing need effective real-time monitoring and control to

guarantee a low-cost, safe and high quality production. With our modern

multidisclipinary process monitoring solutions (PAT) we offer you a proven path to

effective manufacturing, ensuring quality, and reduced validation efforts. New

analytical technologies, control structures, and advanced process control tools

result in an integrated, “transparent” unit operation.

MES

Knowledgemanagement

systems

Advancedprocesscontrols

ModelingProcess

development

Multivariatedata analysis

Processanalytics

regulatory

Multidisciplinary

approach to process

and quality under-

standing and control

New production methods and the demand for shorter time-to-market

create a need for a faster and more complete understanding of pro-

cesses. An increased emphasis on production efficiency (shortening of

throughput delays, upscaling, shifting from batch to continuous pro-

duction methods, increasing capacity and yield) also require increased

real-time process information.

Stricter control of operational conditions throughout the process are

achieved through new advanced sensor technologies and new tech-

niques that handle a wider range of process parameters. PAT closes the

information gap for defining better control strategies and ultimately

optimizes the whole process. Moreover, plant automation is reaching

a level where all processes are operated centrally. Centralized systems

need online evaluations of fundamental process parameters such as

temperature, pressure, weight, and power absorption. Typically, chemi-

cal analysis cannot be evaluated online, a fact that limits its possibility

of controlling and optimizing processes due to the relatively long times

required for laboratory analysis. In-process data and data analysis tools

improve process understanding and control. This ensures quality and

reduces the risk of bring noncompliant products to market. Pharma-

ceutical manufacturing today requires built-in process optimization

and quality assurance to ensure right-first-time (RFT) quality.

Introducing PAT has a considerable positive impact on reducing pro-

duction costs. PAT speeds decisions on the unit operation level and

improves quality/efficiency of process steps. This leads to shorter batch

runs and increased quality consistency. Consistency in quality is a critical

component to enable real-time product release.

Stepping up the pace:

Your benefits with PAT

Raw materials Formulation Finishing Packaging

Weighing & Dispensing

Sieving

Blending/Mixing Granulation

Compressing/Capsulation

Coating

Blistering/Filling

Case Packing

Labeling

Pelletizing

PAT opportunities for key secondary

manufacturing steps

PAT PAT

Conditioning

Grinding

Drying

PAT

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Setting the right direction:

The PAT implementation roadmap

Siemens follows the recommendations of the FDA guidance in its proven PAT approach,

supporting its clients with extensive knowledge and change management services as

well as validation services in each phase. The Siemens PAT implementation roadmap

starts with a risk assessment followed by an assessment of product quality as well as

process and analyzer characteristics. The next step is to perform a multivariate analysis

to define critical to quality attributes (CQA). These attributes need to be measured and

controlled online. Finally, Siemens will develop and implement a control strategy that

will contain process variables in the ”Golden Batch“ process path.

Process control definition Process control for process correction

Golden batch process path

Risk assessmentProduct quality

assessmentProcess

assessmentAnalyzer

assessment

Continuous optimizationand improvement

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Process assessment

Process path definition

Process control improvement

Process optimization

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The PAT implementation roadmap applies PAT to new processes for faster up-scaling/

development and to existing processes for increased quality consistency. To implement

PAT, a multidisciplinary team and an implementation roadmap are created. The imple-

mentation starts with a thorough assessment of both process and analytic technology

conducted by the PAT implementation team. Through process monitoring it is possible

to build a knowledge repository on process behavior, using process analytics as the

”monitoring-eyes“ inside the process. Process analyzer tools permit online evaluation

of chemical and physical parameters. This evaluation is necessary for process control.

The analyzer tools can also be used for instantaneous inline measurements to get a

complete picture or fingerprint of the process, containing information on chemical

and physical aspects as well as performance (bioavailability, stability) features.

These measurements provide a comprehensive view of the entire process and provide

a better insight into what is happening during a specific process step.

Seeing the big picture:

Siemens process assessment

Key process steps are defined when the

process is assessed for areas to increase

controllability, improve performance, and

mitigate risk. These steps determine the

product quality and product performance.

In addition to the process, the assessment

should also include product quality (product

performance: bioavailability, bioequivalence,

stability). To deploy the correct process

analytical tool, the key process steps that are

critical to quality need to be evaluated for

dynamics, precision, and goal (for process

control, batch end-point decision).

Multivariate data analysis is then used to

clarify and describe the interdependence

between process, product and quality para-

meters, and to define the critical to quality

(CQA) attributes.

The correct selection of an optimal process

analytic solution to incorporate into a control

system for a specific process or process stage

is extremely important. The Siemens assess-

ment tool defines critical process steps that

require increased controllability, and aids in

proposing the optimal PAT method that

meets the specific process dynamics and

characteristics. The combination of the right

analyzer tools for process monitoring and

process control systems allows a number of

different processing strategies to be investi-

gated during process development or during

optimization of existing processes. This

results in well-defined production processes.

The results of the assessment and of the

multivariate data analysis form the basis for

a knowledge system to help increase process

understanding and consecutive process

improvements.

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Risk evaluation ofproduct quality

Risk evaluationof process

Quality info fromclinical tests

Identify qualityvariables/attributes

Defining optimalquality

Raw material qualityinformation

Process variables

Defining optimalanalytical technique

Defining optimalanalyzer

configuration

Equipment/processknowledge

Process controll-ability assessment

Process performanceassessment

Validationassessment

Risk assessment Product qualityassessment

Processassessment

Analyzerassessment

Process assessment

Knowledge andchange

management

Validation plan

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The next step is to define an ideal, well-characterized

process track. This is obtained by executing a reduced

Design of Experiments (DOE) based on the multivariate

analysis results. Good and bad batches are defined by

the product quality obtained from the various experi-

ments. From the good batches the ideal ”golden batch“

is identified. This batch delivers the ideal product quality

in the shortest time with the lowest utilization of

ressources. The other good batches define the tolerance

range around the golden batch track.

Once the golden batch track is established, the process

variable setpoints are defined and an ideal process con-

trol strategy is implemented. This is the case for ideal

process runs. Once the process starts to deviate or

abnormal process situations occur, corrections are

required. The iterative learning control makes correc-

tions using the library of control strategies, which were

obtained from the DOE and multivariate data analysis.

The last step uses the established mean time knowledge

to optimize the golden batch track and its associated

control strategy. This knowledge base also serves to

predict process behavior and product quality, based on

raw material characteristics.

Defining the ideal route:

Process control improvement

Process path definition

Multivariatedata analysis

DOE(multiple batchruns)

ExecuteDOE

Identifygood/bad batches

Goldenbatchdefinition

Tunnelcalculation(allowedvariation)

Process control improvement

Multivariatedata analysis

Relationshipbetween processvariables

Transformation ofPAT process track intoprocess variables

Ideal processcontrol strategyfor golden batch

Process control definition

Establish library ofcontrol strategies

Process control for process correction

Iterative learning experimentson bad batches

Continuousimprovement

Process optimization

Prediction of process behaviourand product quality

Optimize goldenbatch process track

Optimize controlstrategy

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Production efforts in all industries are geared toward the

elimination of errors alltogether, i.e. finding the right route

the first time. Comprehensive information on process

quality is determined through Critical to Quality (CTQ)

parameters (physical, chemical and biological). In secon-

dary manufacturing, formulation/blending is a key pro-

cess step. This process step is a major contributor to the

final product quality. During this step corrective measures

can be taken if the CTQ parameters are not met, contrary

to the tableting step, where usually no corrections can

be made to improve the composition.

Previously, API-concentration, moisture level or bioavail-

ability were obtained through offline laboratory methods.

Results were not obtained until several hours after samp-

ling and the results were entered into the process com-

puter offline. This markedly limited the ability to control

and optimize secondary manufacturing processes.

Quality is increased by keeping the process close to the

optimum production path and the likelihood of serious

problems is diminished. In-process measurements pro-

vide parameters that are continuously measured and eva-

luated under almost real time conditions. These quality

practices, build-in by design into the process, deliver

right-first-time quality.

Staying on a focussed course:

Right-first-time quality

Close loop control(physical/chemical

parameters only)

Advancedprocess control

Transform toquality data

Process feed Process output

MonitoringQualitativeand quantitativefingerprint

New analytictechnology

required

process information

physical/chemical

parameters

hold/

release

Process

Knowledge andchange

management

Validation plan

Gained processunderstanding

Knowledge onprocess capabilities

Knowledge onraw materialprocessability

Knowledge onprocess behaviourand controllability

Validationdocument

Process control strategy for real time product release

To ensure right-first-time quality, Siemens developed an assessment

tool that captures our knowledge and experience as a market leader in

process analytics for over 40 years. Siemens is experienced providing

process analytic solutions based on a wide array of analytical techniques.

Siemens experience ensures the correct use of the right analyzer and

the development of applications to support it.

Siemens deploys PAT for both physical and chemical status monitoring,

in addition to using total quality information monitoring (on product

performance, activity, or bioavailability) to improve process understand-

ing and to optimize processes.

Whether you need individual process analyzers, bus systems, or integrat-

ed automation solutions linked to the MES layer, you can count on the

scalable products and solutions from Siemens. Our products and ser-

vices are precise, compatible with existing systems, and a dedicated to

remain compatible for the future of your plant.

Our Life Science solution for integrated Advanced Process Control (APC)

uses APC tools integrated with SIMATIC PCS 7 process control system.

These tools are interfaced via an OPC client channel to the WinCC server.

The tools utilize the SIMATIC IT Historian database and data obtained by

the process analyzers. APC represents an important link between the

planning and scheduling functions of the execution and control levels.

By using APC, SIMATIC PCS 7 includes powerful process optimization

functionality and ensures not only a more efficient process control but

also greater transparency in production.

Well-equipped and in the know:

PAT systems and solutions

Overview of multidisciplinary PAT solution for process control,

process optimization and real-time product release

flexibilityIT / MES INFRASTRUCTURE

Batch

Pharma modules

Equipment modules

Optimization

(fundamental process)Modeling

Control solution

(grey) Modeling

Real-timeproduct release

Modeling/verification

PAT application

Control modules

Electronic batchrecord

0011001000111101010111001010

Process control level Advanced process control tools Product release Procedures

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Potential obstacles can be encountered on every

journey. With our PAT solutions, we ensure that

you steer clear of all of them, even those concern-

ing validation and personell considerations.

Validation is an intrinsic part of the Siemens PAT

implementation. Our validation strategy is based

on science and risk based methods that reduce

validation efforts.

The impact of introducing a PAT solution is high,

especially with regards to personnel considerations

including organizational structures and working

methods. The success of the PAT solution is in-

creased by implementing a change management

track synchronized with the PAT implementation

road map at the start of the PAT project. Barriers

for the introduction of this new technology and

its impact can be removed by aligning people,

organizational structures and procedures. This co-

ordination service is offered by Siemens to ensure

the success of your PAT investment.

Another critical success factor is assigning the right

project team. The team needs to be multidisci-

plinary and able to leverage the capabilities of the

involved disciplines. For example, a specialist in

analytics needs to also think from process and pro-

cess control perspectives to avoid the mindset that

a process analyzer is just replacing a lab analytic

method, which will not add value to increase pro-

duct quality and consistency. Siemens can provide

you with expertise to include in your own multi-

disciplinary PAT implementation team.

Venturing on safe terrain:

Validation and personell considerations

SiemensValidation/qualification

SiemensProcesstechnology

SiemensProcessanalytics

SiemensAssessments

SiemensProject management

SiemensMultivariateanalysis

SiemensProcesscontrol

Client

ClientProcess development

ClientQuality

ClientValidation/qualification

ClientProcessautomation

Siemens Client

Reporting

Steering committee

Project team

PAT implementation project team

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For further information on Siemens solutions

for pharmaceutical industry, just go to:

www.siemens.com/pharma

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Siemens AG

Automation and Drives

Competence Center Pharma

Siemensallee 84, 76187 Karlsruhe

Germany

pharma-info@siemens.com

w w w . s i e m e n s . c o m / p h a r m a

The information provided in this brochure contains

merely general descriptions or characteristics of perfor-

mance which in actual case of use do not always apply

as described or which may change as a result of further

development of the products. An obligation to provide

the respective characteristics shall only exist if expressly

agreed in the terms of contract.