Post on 31-Mar-2018
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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.