Strategic Development of a Manufacturing Execution

System (MES) for Cold Chain Management

Using Information Product Mapping
by MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
Todd Andrew Waldron JUN 152011
B.S. Chemical Engineering, Drexel University, 2002

M. Biotechnology, University of Pennsylvania, 2007 LIBRARIES

Submitted to the MIT Sloan School of Management and the Department of Chemical Engineering
in Partial Fulfillment of the Requirements for the Degrees of

Master of Business Administration

AND ARCHfVES
Master of Science in Chemical Engineering

In conjunction with the Leaders for Global Operations Program at the

Massachusetts Institute of Technology

June 2011

C 2011 Todd Andrew Waldron. All rights reserved.

The author hereby grants MIT permission to reproduce and to distribute publicly copies of this thesis
document in whole or in part in any medium now known or hereafter created.

Signature of Author
May 6, 2011
Department of Chemical Engineering, MIT Sloan School of Management

Certified by -"II Cti Stuart

i
Madnick, Thesis Supervisor
John Norris Maguire Professor of Information Technology, lWT Sloan School of Management

Certified by
1'itsopher,'ove, Thesis Supervisor
Latham Family Career Developmegt Professor, Departipnt of Chemical Engineering

Accepted by
Debbie Berechman, Execitive Director of MBA Program
MIT Sloan School of Management

Accepted by
William Deen, Chairman, Committee for Graduate Students
Department of Chemical Engineering
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 Strategic Development of a Manufacturing Execution
System (MES) for Cold Chain Management
Using Information Product Mapping
by

Todd Andrew Waldron

Submitted to the MIT Sloan School of Management and the Department of Chemical Engineering
on May 6, 2011 in Partial Fulfillment of the Requirements for the Degrees of

Master of Business Administration

AND
Master of Science in Chemical Engineering

ABSTRACT
The Vaccines & Diagnostics (V&D) division of Novartis recently developed a global automation
strategy that highlights the need to implement a manufacturing execution system (MES). Benefits of an
MES (electronic production records) include enhancing the compliance position of the organization,
reducing production delays, and improving process flexibility; however, implementing an MES at global
manufacturing sites presents unique logistical challenges that need to be overcome.
The goal of this thesis is to investigate cold chain management as an expanded functionality for
an MES. The thesis attempts to identify best practices for the strategic implementation of an MES in the
management of cold chain vaccine products. While the concepts presented in this thesis are in the context
of managing the cold chain for vaccine products, the best practices can be applied to a variety of cold
chain management scenarios.
In order to generate best practice recommendations for the strategic implementation of a cold
chain management MES, a thorough understanding of the manufacturing process will need to be acquired.
The first tool used to gain this understanding was value-stream mapping (VSM). VSM provided some
insight into the current paper-based cold chain management system; however, the tool was not applicable
for understanding the flow of information generated within the cold chain management system.
Another tool was used to enable the organization to focus on the data generated by a process, the
information product map (IP-Map). Current-state IP-Maps of the cold chain at the Rosia, Italy, site were
generated and numerous areas for improving the data quality were identified. Future-state IP-Maps of the
cold chain at the Rosia, Italy, site were generated to demonstrate how the implementation of a cold chain
MES could improve the shortcomings of the current system.
The future-state IP-Maps were based on underlying assumptions that directly lead to
recommendations for the cold chain MES implementation. First, a unit of measurement smaller than lot
size must be selected for tracking material data in the MES. Second, data capture technology for material
entering or leaving cold storage must be integrated with the MES.

Thesis Supervisor: Stuart Madnick

John Norris Maguire Professor of Information Technology, MIT Sloan School of Management

Thesis Supervisor: J. Christopher Love

Latham Family Career Development Professor, Department of Chemical Engineering
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ACKNOWLEDGMENTS
I am indebted to my advisors, Chris Love and Stuart Madnick, for their advice and guidance throughout
my internship and in the writing of this thesis.

Iwould like to express my sincerest gratitude to all the individuals I worked with at Novartis Vaccines
and Diagnostics, whose willingness to help was remarkable. My supervisors, Ian Allan and Nicola
Catania, and my colleague, Alessio Bertolucci, showed tremendous hospitality during my stay in Italy and
provided outstanding support during the project.

I am grateful for my classmates in the Leaders for Global Operations Class of 2011. I feel privileged to
have learned from your experiences and honored to have worked with you over the last two years.

I am fortunate to have worked with and learned from Don Rosenfield and all of the staff members of the
Leaders for Global Operations program. I could not imagine a more enriching educational experience.

I would like to thank my loving partner, Erin O'Neal, for not only selflessly helping to edit this thesis, but
for all of her support throughout this journey.

I am blessed to have wonderful parents, Jeff and Denise Waldron, who have provided a lifetime of
support and encouragement. Your strength and sacrifices over the years have allowed me to pursue my
goals, and for that, I can never thank you enough.
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 TABLE OF CONTENTS
ABSTRACT .................................................................................................................................................... 3
ACKNOW LEDGMENTS................................................................................................................................... 5
TABLE OF CONTENTS................................................................................................................................... 7
FIGURES ......................................................................................................................................
TABLE OF 9
CHAPTER 1: INTRODUCTION AND THESIS OVERVIEW ................................................................ 10
1.1 Problem Description ........................................................................................................................................ 10
1.2 Manufacturing Execution System ............................................................................................................... 10
1 .3 P ro je ct Driv ers.................................................................................................................................................... 12
1.3.1 Enhance Compliance Position.......................................................................................................................... 12
1.3.2 Reduce Production Delays.................................................................................................................................. 13
1.3.3 Improve ProcessFlexibility................................................................................................................................ 13
1.4 Organization of Thesis..................................................................................................................................... 14
1 .5 Co n fid e n tiality ..................................................................................................................................................... 14

CHAPTER 2: STUDY OVERVIEW ...................................................................................................... 15

2 .1 R esea rch Meth o d ............................................................................................................................................... 15
2 .2 Stu d y Site ............................................................................................................................................................... 16
2 .3 Key Co n cep ts ....................................................................................................................................................... 16
2 .3.1 S ta bility ....................................................................................................................................................................... 16
2.3.2 Shelf-Life and Expiry............................................................................................................................................. 17
2.3.3 Time Out-of-Refrigeration................................................................................................................................. 18
2.3.4 Cold Chain Management.....................................................................................................................................18
2 .4 P ro je t Sco p e ....................................................................................................................................................... 19

CHAPTER 3: VALUE-STREAM MAPPING..................................................................................... 21

3 .1 VSM Descrip tio.n ................................................................................................................................................. 21
3.2 Findings from VSM ............................................................................................................................................ 21
3.3 VSM Shortcomings for Understanding the Cold Chain................................................................. 27

CHAPTER 4: CURRENT-STATE INFORMATION PRODUCT MAPS (IP-MAPS).............................29

4.1 IP-Map Advantages for Understanding the Cold Chain................................................................. 29
4.2 IP-Map Description ........................................................................................................................................... 29
4.3 IP-Map Developm ent Approach .................................................................................................................. 31
4.4 Current-State IP-Maps ..................................................................................................................................... 32
4.4.1 Transfer of Bulk Materialfrom the Global Warehouse to the Filling and Inspection
Local Cold Room .................................................................................................................................................. 32
4.4.2 Filling and Inspection Processes...................................................................................................................... 33
4.4.3 Transfer of Filled/InspectedProductfrom the Fillingand Inspection Local Cold Room
to the Packagingand Labeling Local Cold Room........................................................................... 36
 4.4.4 Packagingand Labeling Processes................................................................................................................ 37
4.4.5 Transfer of Finished Productfrom the Packagingand Labeling Local Cold Room
to the Global Warehouse..................................................................................................................................41
4.4.6 FinishedProduct Time Out-of-RefrigerationData Review............................................................ 42
4.5 Cold Chain Management Concerns Identified by the IP-Maps................................................... 43

CHAPTER 5: FUTURE-STATE INFORMATION PRODUCT MAPS (IP-MAPS) .............................. 46

5.1 Fu tu re-State IP -Map s ....................................................................................................................................... 46
5.1.1 Transfer of Bulk Materialfrom the Global Warehouse to the Filling and Inspection
Local Cold R oom .................................................................................................................................................. 46
5.1.2 Filling and Inspection Processes......................................................................................................................47
5.1.3 Transfer of Filled/InspectedProductfrom the Filling and Inspection Local Cold Room
to the Packagingand Labeling Local Cold Room........................................................................... 49
5.1.4 Packagingand Labeling Processes................................................................................................................ 51
5.1.5 Transfer of FinishedProductfrom the Packagingand Labeling Local Cold Room
to the Global Warehouse.................................................................................................................................. 54
5.1.6 FinishedProduct Time Out-of-RefrigerationData Review............................................................ 55
5.2 Cold Chain Management Improvements Found in the Future- State IP-Maps.................... 56

CHAPTER 6: RECOMMENDATIONS...............................................................................................58
6.1 Select Smaller Units of Measurement for the Cold Chain MES................................................... 58
6.2 Implications of Selecting Smaller Units of Measurement for the Cold Chain MES.............58
6.3 Ensure Cold Chain Data is Captured Automatically ...................................................................... 61
6.4 Implications of Ensuring Automatic Capture of Cold Chain Data.............................................. 62

BIBLIOGRAPHY.....................................................................................................................................63
 TABLE OF FIGURES
Figure 1: M anufacturing Operations M odel (Allan 2009)..........................................................................11

Figure 2: Vaccine Product Flow Through Processing ............................................................................ 23

Figure 3: Process Interruption Disrupts Material Flow..........................................................................24

Figure 4: Division of M aterial During Processing ................................................................................. 25

Figure 5: Processing of Material at Numerous Facilities ........................................................................ 26

Figure 6: Straight-Through Processing of M aterial .............................................................................. 27

Figure 7: Information Product Map Symbol Guide .............................................................................. 30

Figure 8: IP-Map for the Transfer of Bulk Material from the Global Warehouse to the Filling and

Inspection Local C old Room .............................................................................................. 32

Figure 9: IP-Map for the Filling and Inspection Processes ................................................................... 34

Figure 10: IP-Map for the Transfer of Filled/Inspected Product from the Filling and Inspection Local Cold

Room to the Packaging and Labeling Local Cold Room ................................................... 36

Figure 11: IP-Map for the Packaging and Labeling Processes .............................................................. 38

Figure 12: IP-Map for the Transfer of Finished Product from the Packaging and Labeling Local Cold

Room to the G lobal W arehouse.......................................................................................... 41

Figure 13: IP-Map for the Finished Product Time Out-of-Refrigeration Data Review .......................... 43

Figure 14: Future-State IP-Map for the Transfer of Bulk Material from the Global Warehouse to the

Filling and Inspection Local Cold Room ............................................................................ 46

Figure 15: Future-State IP-Map for the Filling and Inspection Processes ............................................ 48

Figure 16: Future-State IP-Maps for the Transfer of Filled/Inspected Product from the Filling and

Inspection Local Cold Room to the Packaging and Labeling Local Cold Room...............50

Figure 17: Future-State IP-Map for the Packaging and Labeling Processes...........................................52

Figure 18: Future-State IP-Map for the Transfer of Finished Product from the Packaging and Labeling

Local Cold Room to the Global Warehouse........................................................................55

Figure 19: Future-State IP-Map for the Finished Product Time Out-of-Refrigeration Data Review ......... 56
CHAPTER 1: INTRODUCTION AND THESIS OVERVIEW

1.1 Problem Description

This thesis is based on work that was performed by the author over a six and a half month period
at the Rosia, Italy, site of Novartis Vaccines & Diagnostics (V&D). The goal of this thesis is to
investigate cold chain management as an expanded functionality for a manufacturing execution system
(MES). The thesis attempts to identify the best practices for strategic implementation of an MES in the
cold chain management of vaccine products. While the concepts shared in this thesis are in the context of
managing the cold chain for vaccine products, the best practices can be applied to a variety of cold chain
management scenarios.

Novartis V&D division is currently characterized by a series of manual activities for capturing
and reviewing process information. Manual data capture and review leads to a low-level of transparency,
investigational capability, and process integration. In light of these deficiencies, the V&D division
recently developed a new global automation strategy that highlights the importance of a manufacturing
execution system (MES). The MES has been identified as the main tool in the business transformation
road map that defines, documents, and controls all relevant production and quality parameters. A
strategically implemented MES has the capability to generate a competitive advantage for the division
through high levels of data transparency and flexible process integration.

Vaccine products must be maintained within a cold chain throughout their lifecycle in the
manufacturing facility. Maintaining vaccine products at proper refrigerated storage conditions between
processing steps is a critical component to ensuring the effectiveness of the product. Calculating the time
out-of-refrigeration for vaccine product is a manually intensive process performed across a number of
functional groups within the V&D division. Manual data capture leads to an increased cycle time and
inefficient use of resources. The MES is a tool that can automatically collect and analyze time out-of-
refrigeration data for vaccine product throughout the division, empowering key stakeholders to make
data-driven processing decisions.

1.2 Manufacturing Execution System

The manufacturing operations model of the pharmaceutical industry can be described as
overlaying levels of management. Lower levels manage local events that have a discrete impact while
higher levels direct global changes that have widespread implications. Information technology systems
can be used to manage a layer of the model or to enhance communications between the layers of the
model.

Level 0, the plant level, represents the actual production process. Level 1, the instrumentation
level, represents the equipment that sense and manipulate the production process. Instruments in Level I
take measurements of the Level 0 production. Level 2, the control level, represents the automation that
controls the production process. Process control systems (PCS) that direct infrastructure based on
readings from Level I instruments are also called supervisory control and data acquisition (SCADA)
systems. Information collected from the Level I instruments are often stored in data historians at Level 2.
Level 3, the operations level, represents the production recipes and work flows that produce the desired
products. An MES can manage the manufacturing steps that are controlled by Level 2 automation. PCS
control all relevant process parameters whose validated ranges are defined by the MES. Level 4, the
business planning level, manages the overall production plan and material flow. Enterprise resource
planning (ERP) software collects data from accounting, sales, and planning to determine the work orders
required to meet demand forecasts. The MES schedules production processes in an optimal way based on
instructions from the Level 4 production plans (Allan 2009).

Level 4 Business
Planning

Level 3 Operations

Level 2 Control /
Data Historian

Level 1 Instrumentation

Level 0 Production

Figure 1: Manufacturing Operations Model (Allan 2009)

The MES is an electronic interface that links the personnel, instruments, equipment, and
automation of the shop floor with the inventory, planning, logistics, and finance of management. The
MES builds this bridge by being the electronic interface that directs production and quality control
systems (Blumenthal 2004). The most important feature of an MES is its management of electronic batch
records. Production batch records serve as the instructions for supervisors and process technicians.
Production batch records contain all of the critical information about processing steps. Information about
who executed the steps and when the steps were executed are recorded in the production batch record.
Production batch records can also include ranges for critical process parameters. Examples of critical
process parameters include the weight of material additions, the temperature of process tanks, and the pH
of process fluids. Critical process parameter data from instruments can be recorded in the process batch
records and compared against pre-defined ranges. Electronic batch records automatically associate
captured process data with the appropriate batch record.

The MES is an established information technology tool for improving data transparency,
investigational capability, and process integration. The MES has the capability to manage products
maintained within a cold chain if it is implemented appropriately. Best practices for strategic implantation
of a cold chain management MES can be developed with the aid of process mapping techniques.

1.3 Project Drivers

Strategic implementation of an MES to bridge the Operations and Control levels of the
manufacturing operations hierarchy has regulatory and financial benefits. There are three main business
drivers for this project: an enhanced compliance position for the division, reductions in production delays,
and improved process flexibility for enhanced use of organization resources.

1.3.1 Enhance Compliance Position

The first main benefit of an MES implementation is its ability to enhance the compliance position
of the organization. Maintaining positive relationships with worldwide regulatory agencies is important
when trying to resolve manufacturing issues that fall under their jurisdiction and when trying to promote
new technologies and products for your company portfolio. Processing data that is recorded from
instruments into documents by a technician has the opportunity to be compromised. In order to prevent
the unintentional inclusion of incorrect data in a batch record, a check of the data entry by another
technician or supervisor is often incorporated into data capture procedures. Manual data capture takes
technicians and supervisors away from other critical processing functions that ensure the batch is being
manufactured according to the approved procedures. The MES can automatically verify information
captured by instruments and associate that data with the correct electronic batch record. The MES can
also be programmed to collect process data at specific time points during the process so the division is not
dependent on manual data entry, which could be impacted by the availability of labor.
 In addition to associating data with a specific batch record, the functionality of the MES can be
used to compare the data to an expected result. If the process data is outside of a predefined range, the
MES can flag the result internally or in conjunction with another system and send a notification to begin
an investigation into the result. The data that is managed by the MES can be archived in a data historian.
The functionality of the MES can interact with the data historian to aid investigations and process
improvement projects. When paper-based batch records are in place, data mining for investigations is a
time-consuming process. Questions that require data about previous lots of material require the
investigator to go back to the source documents and have the data audited. An MES that interfaces with a
data historian allows data that has already been reviewed to be easily accessed and organized by the
investigator. Additionally, this data can be used to map process trends, increasing visibility and allowing
supervisors and technicians to take preventative actions.

1.3.2 Reduce ProductionDelays

The next main benefit of an MES implementation is its ability to reduce production delays. Having
verified data automatically associated with electronic batch records not only enhances the compliance
position of the organization, but it can also decrease product release cycle time. Since all batch data is
available as soon as manufacturing is complete, personnel in the quality and release departments have
immediate access to batch information. Quality personnel are no longer responsible for a line-by-line
review of the paper batch records to ensure all of the data is accurate and has been verified. The MES
electronic batch record allows quality personnel to focus on critical process parameters, completing their
batch record review to release the associated material to the market in a fraction of the time compared to
the paper-based system. Expedited review of the batch record can help material get to the market quicker,
allowing the division to capitalize on a new market or preventing a possible stock-out situation for a
health care critical product.

1.3.3 Improve ProcessFlexibility

The last main benefit of an MES implementation is its ability to improve the process flexibility of
the organization. Processing material is comprised of similar steps such as measuring raw material,
adding vaccine fluids to a tank for formulation, or packaging a vial. Each of these steps is comprised of
almost identical instructions. The basic instructions can be programmed into an MES and linked together
to form basic operation blocks. The MES stores these basic operations blocks and allows the user to
create electronic batch records from these building blocks. The batch record designers save a great deal of
time and effort because they do not have to develop a batch record from basic instructions each time a
new product is added to the manufacturing site. Additionally, the operations blocks of the batch record
can be universally modified if improvements to a manufacturing process are implemented.

Having a standard interface for electronic batch records across the division improves production
intelligence across the organization. Resources can be shared across processes or across sites without
additional training on how to work with the batch record management system. Before implementation of
an MES, operations personnel that are assigned responsibilities in another department needed to learn
how the paper batch records were organized locally and how data was collected and entered into the batch
record before they could begin training on the local processing steps. Now that the interface is the same
for all batch records, the operators only need to be trained on the process steps before they can deliver
value-added work to the area. The MES allows for greater flexibility in assigning the work force which
makes the division more adept at handling unexpected product demand spikes.

1.4 Organization of Thesis

Chapter 1 explains the problem and project motivation, and defines manufacturing execution system.

Chapter 2 describes the company, division background, and project scope and defines cold chain
management.

Chapter 3 defines value-stream mapping, explains the benefits derived from initial use of this tool, and
discusses the limitations of the tool when analyzing cold chain management information flow.

Chapter 4 discusses why information product mapping is a valuable tool for analyzing cold chain
management information flow, defines information product mapping, and reviews maps for the current-
state cold chain management processes.

Chapter 5 discusses the benefits of a manufacturing execution system for cold chain management and
reviews maps of the future-state cold chain managed by a manufacturing execution system.

Chapter 6 provides best practice recommendations for the cold chain management implementation.

1.5 Confidentiality
Production data and diagrams presented in this thesis have been distorted or are hypothetical for
the purpose of ensuring the confidentiality of information proprietary to Novartis.
CHAPTER 2: STUDY OVERVIEW

2.1 Research Method

In order to generate best practice recommendations for the strategic implementation of a cold chain
management MES, a thorough understanding of the manufacturing process from formulation to labeling
will need to be acquired. The first tool used to gain this understanding was material and information flow
mapping, which is more commonly known in industry as value-stream mapping (VSM). VSM presented
difficulties in trying to understand the flow of information associated with vaccine products maintained in
the cold chain of a manufacturing site. Information used to determine key characteristics of the products
maintained in the cold chain are treated as a by-product when analyzing the manufacturing process using
VSM. Another tool that focuses on information as a quality characteristic of the products maintained in
the cold chain would be required to thoroughly understand the cold chain within the manufacturing
process.

The next tool used to gain a thorough understanding of the cold chain within the manufacturing
process was the information product map (IP-Map). The IP-Map is a modeling method used to focus an
analysis on the data generated by a manufacture process. Instead of considering data as a by-product of
production, this tool can be used to focus information as a product that has value to the customer.
Information product mapping was deemed an appropriate tool for this project based on its successful use
in health care delivery. In the paper entitled Developing dataproduction maps: meeting patientdischarge
data submission requirements by Davidson, Lee, and Wang, the authors used data production maps, an
early form of the IP-Map, to understand the entire information manufacturing system at an 875-bed
hospital in the western United States. The data quality maps that were developed by the authors helped
the hospital improve the quality of patient data required for submission to the State Department of Health
Services, successfully eliminating non-compliance letters that the hospital was receiving frequently prior
to the project. This tool was used to gain an understanding of a complex information manufacturing
system and solve a cross-functional problem that appeared to be intractable. This problem is similar to the
implementations of a cold chain management MES that would need to manage complex information
streams across multiple organizations (Davidson, Lee and Wang 2004).

Initial value-stream maps and information product maps were generated by reviewing operating
procedures and production batch records. The process maps were refined over several months of process
observations and interviews with technicians, process supervisors, and process engineers.
2.2 Study Site
Novartis International AG is a multinational pharmaceutical company headquartered in Basel,
Switzerland. Novartis was formed in 1996 by the merger of Ciba-Geigy and Sandoz Laboratories. The
company is divided into four international divisions: pharmaceuticals, vaccines and diagnostics, Sandoz
(generic pharmaceuticals), and consumer health. The V&D division was added to the company in 2006
after the acquisition of Chiron Corporation.

The history of mergers and acquisitions that characterized the formation of Novartis has also
shaped the current culture of the company. The divisions of the company act independently and
information is not readily exchanged across divisional boundaries. Each division develops its own
strategies and creates its own vision for future success. Communicating best practices across divisions is
an important source of time and cost savings for Novartis. The V&D division is segmented in the same
manner as the parent company based on the acquisition of the Chiron Corporation. Creating one vision for
the division and finding common platforms to promote operational efficiencies are a key part of the
division strategy.

In 2010, Novartis had more than $50.6 billion in net sales. The V&D division accounted for $2.9
billion in sales, or 6 percent of total net sales. V&D is the smallest of the four divisions by revenue,
however, the division had a 25% increase in constant currency net sales from their total in 2009. The
division also has a strong pipeline that includes 15 vaccine candidates currently in clinical trials (Novartis
2010). The V&D division seeks to demonstrate that it is a critical piece of the Novartis portfolio. The
division has committed to have systems in place to support its strategic growth. This project will strive to
develop best practices for a cold chain management MES that will increase flexibility among the
operations sites and prepare the division to readily accept new products and handle increased demand.

2.3 Key Concepts

2.3.1 Stability

Legislative assemblies in countries around the world have mandated regulatory agencies to
control the approval of vaccines before they can be marketed to the public. Major regulatory agencies
include the Center for Biologics Evaluation and Research (CBER), a branch of the United States Food
and Drug Administration (FDA), the European Medicines Agency (EMA) and the Pharmaceuticals and
Medical Devices Agency (PMDA) in Japan. Each regulatory body has specific guidelines for determining
the safety, purity, and efficacy of vaccines before they can be licensed for sale to the public. Worldwide

16
regulatory authorities also require each lot of vaccine to be tested for critical properties including safety,
efficacy, identity, potency, and stability before giving their approval for release to market.

Stability is a measure of the ability of a vaccine to retain its physical, chemical, and biological
properties. Testing of a vaccine product for stability usually refers to the thermostability of that product,
or the stability of the vaccine at various temperatures. Thermostability is determined by measuring the
change in potency of a vaccine stored at a given temperature for a given period of time. Potency is the
capacity of the vaccine to generate desired effects in a test, usually cell-culture or animal based, which is
correlated with the immune response generated in a patient. Potency tests are important for determining
the overall effectiveness of a drug. Stability studies conducted at different temperatures for different
lengths of time create a thermostability profile for the vaccine that is used to generate guidelines for
proper storage conditions. Long-term stability test programs are designed to evaluate storage at constant
temperature, while accelerated studies evaluate the effect of short-term excursions.

The International Conference on Harmonization of Technical Requirements for Registration of

Pharmaceuticals for Human Use (ICH) brings together the regulatory authorities of Europe, Japan, and
the United States to discuss scientific and technical aspects of product registration (ICH 2010). In
November of 2003, the ICH released guidance for the pharmaceutical industry entitled Q1A(R2) Stability
Testing ofNew DrugSubstances and Products (ICH 2003). The guidance provides vaccine manufacturers
with recommendations on the type and amount of stability data that should be generated as part of the
application package of a new drug substance.

Key recommendations from the ICH include: performing stability studies on at least three batches
of drug substance that simulate the final process that will be used for production batches; ensuring the
drug product is packaged in the same closure system that will be used for storage and distribution during
the studies; and testing batches at a minimum frequency of every three months for the first year, every six
months for the second year, and annually thereafter. Recommended storage condition temperature ranges
are also provided for long-term and accelerated stability test programs (ICH 2003).

2.3.2 Shelf-Life and Expiry

The main goals of stability studies are to determine the shelf-life for the vaccine product and the
time out-of-refrigeration for the vaccine and its intermediates during manufacturing. The shelf-life of a
vaccine is the period of time in which the vaccine will be efficacious if stored at proper conditions.
Vaccine shelf-life is determined by calculating the vaccine release model, which incorporates the
thermostability profile at all temperatures the vaccine is exposed to and the minimum potency that is
required to generate the desired immunological response in the patent. The shelf-life is then used to assign
an expiry date to a specific vaccine lot, dependent on the date of manufacture of the product. The expiry
date is the final day a lot of correctly stored vaccine is expected to maintain the minimum potency
required to generate the necessary immune response in the patient.

2.3.3 Time Out-of-Refrigeration

Time out-of-refrigeration (TOR) is the total amount of time that a vaccine product or intermediate
product is outside of its specified temperature range, usually 2-8*C. Deviations from the specified
temperature range can occur during processing, packaging, and shipping. Stability studies similar to those
recommended by the ICH are performed on vaccine products and intermediates to determine the
acceptable TOR during manufacture and shipping. The results of these stability studies provide
information on how long the vaccine can be held at its recommended storage temperature and, if
deviations outside of this recommended storage temperature occur, how long these TOR excursions can
be to still maintain acceptable chemical and biological properties. Data from these TOR studies is also
incorporated into the vaccine release model to determine product shelf-life. Therefore, monitoring and
documenting TOR for each vaccine lot is an important part of managing the manufacturing cold chain for
a product.

2.3.4 Cold Chain Management

Cold chain management refers to all of the policies and personnel that are used to ensure the
integrity of vaccine material during manufacturing and distribution. The word "cold" refers to
environmentally sensitive material and understanding the impact of removing that material from a
temperature controlled environment. The word "chain" refers to the chain of custody for the material.
Each time vaccine material is removed from its temperature controlled environment for processing,
transportation, or storage, that information must be documented. Delivery and receipt of temperature
sensitive vaccine material must be linked by the cold chain management documentation. According to
the World Health Organization, in order to maintain the original quality, every activity in the distribution
of pharmaceutical products should be carried out according to the principals of Good Manufacturing
Practice (GMP), Good Storage Practice (GSP) and Good Distribution Practice (GDP) (World Health
Organization 2005).

Critical parameters that are measured as part of ensuring the reliability of a cold chain are
developed during stability studies, shelf-life determination, and time out-of-refrigeration calculations. The
thermostability profile of products maintained in the cold chain is determined during stability studies. The
critical process parameter of the cold chain management system is time out-of-refrigeration. Once
thermostability profiles are completed, time out-of-refrigeration limits for each of the vaccine products
monitored by the cold chain management system can be determined. Responsibility for cold chain
management ultimately resides with the manufacturer and regulatory agencies are requiring heighten
levels of monitoring and control.

Global regulatory agencies have increased oversight to ensure the integrity of pharmaceutical
products in the distribution chain. Regulatory guidance to industry, presentations by industry thought-
leaders, and regulatory enforcement citations have highlights a number of trends impacting cold chain
management. The first of these trends reinforces that the responsibility of managing the cold chain lies
with the product manufacturer. The next trend is that cold chain management must be completed over the
entire supply chain to ensure patient safety. The final trend highlights the increased importance of
temperature control and monitoring to mitigate risks during product transport (Bishara 2006). This
transport can be on a global level between the manufacturer and the customer or on a local level between
a product line and a warehouse. These trends will be acknowledged as part of the best practice
recommendations for implementation of a cold chain management MES.

Failure to comply with the increasing scrutiny on cold chain management can lead to citations
from regulatory agencies. If these citations are not addressed, as deemed appropriate by the citing
regulatory agency, the agency has the capacity to prevent material from being sent to the market and/or to
levy substantial monetary fines. This action not only has immediate financial implications, but it can
impact the reputation of the company and can draw additional scrutiny from other regulatory agencies, the
media, and the public. Examples of citations handed down from the FDA include one in May of 1999 for
a standard operating procedure lacking acceptance criteria for the storage and movement of material
between two sites and another in October of 2001 for bulk material intended for refrigerated storage being
left at ambient conditions for several days before shipping (Bishara 2006). Strategic implantation of an
MES to manage the cold chain can ensure appropriate time out-of-refrigeration procedures have been
generated and associated data is gathered and analyzed.

2.4 Project Scope

With the understanding that the V&D division wants to standardize information technology
systems to help foster growth, having the MES manage the entire production cold chain would provide
the most benefit to the division. However, establishing sensible boundaries for the work completed during
internship was a necessary part of focusing the project and preparing it for success. Management of the
entire V&D cold chain would include numerous production sites, all materials used in manufacturing, and
governance across all production steps.

The current Novartis vaccine manufacturing network is comprised of production sites in Europe
and the United States. The internship was based out of the Rosia, Italy, and therefore the cold chain
management work was focused on vaccine materials throughout this site. Process experts at each of the
manufacturing sites were consulted throughout the internship to ensure the best practice recommendations
for an MES implementation were applicable throughout the V&D network.

Production steps that occur at the Rosia, Italy, site include weigh and dispense of raw materials,
bulk manufacture, formulation and filling, inspection, labeling, and packaging. Numerous vaccine
products are manufactured and prepared for distribution at this site. In addition, bulk materials from sites
throughout the V&D network arrive at the Rosia site for formulation, filling, and shipping. Time out-of-
refrigeration data for bulk material from these sites and from bulk material that is produced in Rosia is
managed by systems and procedures not associated with formulation, inspection, labeling, and packaging.
For this reason, the scope of the project was focused on the processing steps from formulation to
packaging.

Products that need to be maintained at controlled temperatures include raw materials from
suppliers, intermediates in the manufacturing process, and finished product. Procedures with well-defined
time out-of-refrigeration limits are available for the processing steps from formulation to packaging.
Because the focus of the project has been narrowed to these processing steps at the Rosia site, the vaccine
materials from which time out-of-refrigeration data will be collected is constrained. Collected time out-of-
refrigeration data will be evaluated from the time vaccine material is removed from the global cold
storage warehouse to the time the finished product is returned to the global warehouse for delivery to the
market. Data points will be captured every time vaccine material is removed from cold storage during
these processing steps.
CHAPTER 3: VALUE-STREAM MAPPING

3.1 VSM Description

Value-stream mapping is a tool developed for the Toyota Production System. The tool is used by
Toyota Production System practitioners to depict current events on the manufacturing floor and to design
a lean future-state of events on the manufacturing floor. A value-stream is all of the actions, both value-
added and non-value-added, required to deliver a product through the manufacturing site to the customer
from raw material to the final product. Value-stream mapping is an exercise completed with paper and
pencil that helps the user see and understand the flow of material and information as product travels
through the manufacturing facility. In their book Learningto See, value-stream mapping to create value
and eliminate muda, Rother and Shook describe the objective of value-stream mapping:

"The purpose of value-stream mapping is to highlight sources of waste and eliminate

them by implementation of a future-state value-stream that can become a reality within a
short period of time. The goal is to build a chain of production where the individual
processes are linked to their customers either by continuous flow or pull, and each
process gets as close as possible to producing only what its customers need when they
need it" (Rother and Shook 2003).

Mapping allows the user to visualize the flow of material and information across all parts of the
manufacturing process. Each step in the manufacturing process is documented as part of the value-stream
map. This technique provides a cross-functional look at the manufacturing flow across organizational
boundaries. Analyzing processing across organizations prevents the user from being biased by the local
goals of the isolated independent units. Once the current-state mapping is complete, a future-state map is
devised, improving global flow instead of focusing on localized improvements that may be detrimental to
the overall product goals. The ideal state of the manufacturing floor is then developed through
implementation plans that eliminate wastes such as overproduction, rework and inventory build (Rother
and Shook 2003).

3.2 Findingsfrom VSM

The initial attempt at understanding and improving cold chain management at the Rosia site using
value-stream mapping was unsuccessful. A great deal of time was spent on the manufacturing floor
charting observations of material flow including the flow of bulk material in the warehouse, secondary
product throughout manufacturing steps, and finished vaccine material to the shipping docks.
Unfortunately, the observations did not lead to a map that clearly described concerns with cold chain
management. The mapping was not going to yield a process improvement plan for cold chain monitoring
that could be managed by an MES.

Initiation of value-stream mapping did yield some observations about the current paper-based
cold chain management system. One benefit of the paper-based system is the flexibility of the system.
Deviations that occur during processing can easily be managed by the paper-based system. An ideal
automation solution must be sophisticated enough to handle a number of deviations from standard
procedures that occur in production. The next five figures will diagram vaccine material flow and some
routine deviations from this flow that are easily managed by the paper-based system that must also be
managed by the MES.

Figure 2 through Figure 6 have notation that indicates product movement, product processing and
time out-of-refrigeration clock starts and stops. Arrows formed from solid lines that are not shaded on the
inside (=- ) that lead from one storage location to another represent the transfer of vaccine material
from a given location to another location. Arrows formed from dashed lines that are shaded on the inside
(m=*~) that run across processing steps represent the processing of vaccine material. Two symbols in
these figures represent time out-of-refrigeration data that is recorded in paper documents. The letter "S"
enclosed in a circle signifies a recorded TOR start time and the letter "E" enclosed in a circle signifies a
recorded TOR end time. The presence of these two symbols signifies that time out-of-refrigeration data is
recorded as soon as the material is removed from, or enters, the cold storage location. Each start time
must be paired with an end time, with the end time appearing at the end of the series of product
movement and product processing arrows.

The current-state of typical vaccine product flow is diagramed in Figure 2. Bulk vaccine must
proceed through four major processing areas before being sent to the market: 1) formulation and filling,
2) inspection, 3) labeling, and 4) packaging. Each of the processing steps can occur in different buildings
on-site. The first step in the product flow is removing bulk vaccine from the global cold storage
warehouse and delivering it to a temporary cold storage warehouse just outside the formulation and filling
lines. A small inventory of bulk vaccine is maintained in this temporary warehouse. The bulk vaccine is
combined with stabilizers and possibly an adjuvant to enhance the immune response generated in patients.
The formulated vaccine is then filled into vials or syringes, capped, and returned to the temporary cold
storage warehouse. In order to demonstrate all possible movements of the material, a worst-case scenario
for product flow, the filled vaccine is then returned to the global cold storage warehouse until is it needed
for inspection. For the remainder of this product flow description, vaccine material will always be
returned to the global warehouse after processing, representing a worst-case scenario.

Global Cold Storage Warehouse

-0 en -@0 e^C -n @ en
v\@
C) (D_ v@'7 0 . v 0 _ @z, @ _(
Local Local Local Local
Warehouse Warehouse Warehouse Warehouse

Formulation &
J1L1*
Inspection Packaging
L
Labeling
Filling

Figure 2: Vaccine Product Flow Through Processing

Filled vaccine is transferred to the temporary cold storage warehouse outside of the inspection
area until the material is ready to be examined. The vaccine vials are then inspected manually or by
automated equipment and are returned to the temporary storage warehouse. The inspected vaccine
material is returned to the global cold storage warehouse and then sent to the temporary warehouse in the
building where packaging of the inspected vials occurs. Material is staged from the local warehouse and
the inspected vials or syringes are inserted into blister packaging and matched with inserts that include
important information such as indications, usage, dosage, and warnings. Packaged vaccine lots are
returned to the local cold storage warehouse and then sent to the global warehouse. The final stage in the
typical vaccine product flow diagram involves transferring the packaged vials from the global warehouse
to the temporary warehouse outside of the labeling area. Packaged vials are labeled for shipment to the
customer and returned to the local warehouse before being sent to the global warehouse.

The first case the automation solution must be able to manage is when processing is interrupted,
which is illustrated in Figure 3. Processing can be interrupted by machine failure, raw material depletion,
unavailability of labor or a number of other issues. During the interruption, vaccine material is removed
from the ambient temperature of the processing area and returned to the local cold storage warehouse.
The time out-of-refrigeration calculation for the process must be stopped and then started again when the
material remaining to be processed is removed from cold storage. Resuming processing could occur at
any future point in time and stopping processing could occur during any processing step; formulation and
filling is used as an example of stopping processing in Figure 3. Using a traditional paper-based system,
the time the material has been entirely returned to the temporary cold storage warehouse is noted in the
margins of the batch record. The time the first pallet of material is removed from the local warehouse is
also recorded in the margin of the batch record. This additional data is used to calculate the time out-of-
refrigeration for the lot of vaccine during this phase of the manufacturing process. In some sections of the
batch record where mechanical failures are known to occur, additional space is provided for returning and
recalling material from the temporary warehouse during production interruptions. The MES solution must
be flexible enough to handle additional time stamps when vaccine material is returned to and recalled
from the cold storage warehouse.

Global Cold Storage Warehouse

v @ @

Local
Warehouse

AUSE

Formulation &
Filling

Figure 3: Process Interruption Disrupts Material Flow

The next case the automation solution must be able to manage is when a lot of vaccine material is
divided into two or more sections during processing, which is illustrated in Figure 4. Lots can be divided
at the formulation and filling phase when material is designated to be shipped to a specific country. This
can occur when market-specific regulatory agencies do not approve of the use of a particular adjuvant or
stabilizer in the vaccine recipe. In this case, the bulk lot is divided into portions and can be formulated
and filled at different times. Lots can also be divided at the packaging phase as specific regulatory
agencies may require additional information in the medical insert or a special type of packaging. Each of
these requests can divide a lot during processing. In Figure 4, the lot is divided at the inspection phase
because one section of the lot will be evaluated manually, while another section of the lot will be
evaluated by automated equipment.
 Global Cold Storage Warehouse
Lot 123 C ]
Lot 123 Lot 123A _ULot 123B

Lot 123A I
Local
Warehouse
Lot 123Bj (

Inspection Inspection

Figure 4: Division of Material During Processing

Before inspection begins, the ERP generates two separate orders from the lot of filled material.
This instruction generates two paper batch records, one for each section of the divided lot. Time out-of-
refrigeration data from the filled lot is transferred to each of the two new inspection batch records. The
automation solution must be able to manage split lots during all phases of production. A link must be
maintained connecting the time out-of-refrigeration data from the previous step with the time out-of-
refrigeration data of the new process step pathways.

The next case the automation solution must be able to manage is when only part of the processing
occurs at the Rosia site, which is illustrated in Figure 5. The Rosia site has facilities to complete all four
of the major processing steps on-site, however, the V&D division is an expansive network with current
processing facilities in Europe and the United States. Bulk vaccine is often formulated, filled, and
inspected at another location and then shipped in cold storage vehicles to Rosia. Personnel at the Rosia
site then package and label the material for local markets. Flexibility in the supply chain is a key part of
Novartis' strategy to allow them to support the global marketplace, especially with time-sensitive
vaccines such as the vaccine that protects against influenza.
 Cold Storage Warehouse

TOR H
istory 0 - -

Filled &
Local
Warehouse
Local
Warehouse 1
Inspected
I Material I
Labeling

Figure 5: Processing of Material at Numerous Facilities

Material that arrives from another site has a time out-of-refrigeration history. This history must be
able to be transferred electronically or entered manually into the cold chain MES solution. With the
current paper-based system, the amount of time out-of-refrigeration from the previous processing steps
that occurred at another facility is simply added to the local batch record.

The final case the automation solution must be able to manage is when processing is straight-
through and intermediate storage in a local warehouse is not required, which is illustrated in Figure 6.
Material is not always returned to a local warehouse and then to the global warehouse before beginning
the next phase of processing. Vaccine material sometimes starts a process such as formulation and filling
and then is manually inspected before being sent directly to a packaging line. After packaging the
material may remain in the local cold storage warehouse outside of packaging until it is delivered directly
to labeling for processing.

The MES solution will have an underlying architecture that accounts for all of the possible
production steps and transportation locations. The system must be able to automatically generate blank
values when part of the established architecture is bypassed. The system must also be able to bring
together start values from one processing step and end values from another processing step.
 Global Cold Storage Warehouse

Local
Warehouse
Local
Warehouse
Local
Warehouse
Local
Warehouse I
Formulation &
Filling
Inspection Packaging Labeling
I
Figure 6: Straight-Through Processing of Material

3.3 VSM Shortcomings for Understanding the Cold Chain

Value-stream mapping presented three difficulties in trying to understand and explain the cold
chain management system at Rosia. First, value-stream mapping is most effective when it is focused on
one product or a family of products (Rother and Shook 2003). In mapping the cold chain at Rosia, it was
necessary to account for all vaccine product material flow. Next, value-stream mapping is best when the
manufacturing process flows are mature. The tracking of temperature-sensitive material is not centralized.
Data for tracking time out-of-refrigeration is collected as a loose network of procedures and systems.
Finally, important information tracked in a value-stream map tells the reader what initiates the movement
of product. Time out-of-refrigeration measurements and calculations do not initiate the movement of
product.

According to Rother and Shook, "one point to understand clearly before starting [a value-stream
map] is the need to focus on one product family" (Rother and Shook 2003). Customers care about a
specific product from the manufacturing facility so focusing on the flow of one product or family of
products with similar processing and equipment use is critical to the end user. Mapping all products on
the same map muddles the picture, preventing the user from clearly finding and eliminating wastes. A
more appropriate tool for mapping the cold chain would allow the user to track the process by which all
products are flowing through the cold chain network.

Value-stream mapping is best executed when defined procedures guide material flow through the
manufacturing site. While it is possible to go and see the movement of vaccine product in and out of cold
storage units, the tracking of time out-of-refrigeration is guided by an informal network of emails and
phone calls. Mapping these communications in the context of a value-stream map is difficult because they
do not impact flow of material.

One goal of the future-state value-stream map is to highlight communications and information flow
that signal the movement of material valued by the customer. Instructions from an enterprise resource
planning system are one type of automated message that signals how much vaccine material should be
processed during a given production step. The processing list generated by schedulers is a paper-based
message that tells individual processing areas which raw materials they need to gather and prepare for the
next few days of processing. These messages are a necessary part of the value-stream map because the
communication tells each processing area what they should do in the next step of the process. Time out-
of-refrigeration is a critical process parameter for vaccine material captured during processing, but it does
not drive the movement of material. Time out-of-refrigeration data may shorten a processing window, but
it does not tell production areas what raw materials are required for processing, what should be
manufactured, or when manufacturing should be initiated. Time out-of-refrigeration information is a by-
product of the manufacturing process and a more effective tool for mapping the cold chain would capture
the generation and movement of this critical information.
CHAPTER 4: CURRENT-STATE INFORMATION PRODUCT
MAPS (IP-MAPS)
4.1 IP-Map Advantages for Understanding the Cold Chain
Data generated by a manufacturing process is often viewed as a by-product of production.
Organizations instinctively focus their time and resources on improving the material being generated and
not on improving the quality of critical data that supports processing. This data has a process flow similar
to that of the material with which is it associated. The end result of the data flow is information that
customers find valuable. Customers consider end result data about product quality or safety just as
important as the appearance of the finished good. In the case of vaccines, information derived from
production data points provides insight into the quality, safety, and efficacy of the lot of material. These
attributes are not only highly valued by the customer, but they are required by law for release and
distribution of the product.

Focusing on data as a by-product can lead organizations to spend valuable resources on the
system that controls the data instead of focusing on the product the data will deliver. Reliable information
is critical to good decision making. The faster reliable, consistent data is available to the internal and
external customer, the more value the customer will find in the relationship. High quality information is a
competitive advantage that can keep customers loyal to a product and increase the value of the brand. One
tool that can be used to focus an organization on the data generated by a process is the information
product map (IP-Map).

4.2 IP-Map Description

An IP-Map is a method for modeling the production of an information product. Instead of
considering data a by-product of production, this tool can be used to focus information as a product that
has value to the customer. The tool uses inputs called data elements to generate outputs called information
products. A data element is the smallest unit of named data that has meaning in the context of an
operational environment. Examples of data elements include dates, times, names, deposits, or phone
numbers. An information product is a collection of data element instances that meet the specified
requirements of a data customer. Examples of information products include birth certificates, work
permits, and financial statements. The IP-Map is a systematic representation of the process involved in
creating an information product from the data elements (Lee, et al. 2006).
 The guide to IP-Map symbols and representations presented in Figure 7 is consistent with
standard conventions. These notations are found throughout the IP-Maps of this thesis.

Symbol Definition/Purpose

RD, __ Raw Data: A predefined set of data units that are used as the raw
material in a process that will produce an information product.
_____01 InformationProduct: A finalized collection of data produced by
human, mechanical, or electronic effort for use by a data consumer.
CD, 1 Component Data:A set of temporary, semi-processed information
needed to manufacture the information product. Data generated within
the IP-Map and used in creating the final information product.
Source (Raw Data)Block: Represents the source of raw input data that
Data must be available in order to produce the information product expected
Source by the consumer.
DS1

Consumer (Output) Block: Represents the consumer of the information

product. The consumer defines in advance the data elements that
Cu constitute the finished information product.

Data Data Quality Block: Represents the check for data quality in those
Quality items that are essential in producing defect-free information product.
QCI The block has two possible outputs: a correct stream and an
incorrect
stream.

ProcessingBlock: Represents the manipulation, combination, or

Processing calculation of raw or component data items and/or component data
Pi items used to calculate the information product.

Decision Block: Represents the direction of data to a different set of

Decision blocks for processing, if necessary.

Data Storage Block: Represents the capture of data items in storage

files and databases so they can be available for further processing.

Organizational Business Boundary Block: Represents instances where raw input or

Boundary component data items are handed over by one organizational unit to
BBi another organizational unit.

Information Information System Boundary Block: Reflects changes to raw or

System component data items as they move from one type of information
Boundary system to another.
ISBi

Figure 7: Information Product Map Symbol Guide

4.3 IP-Map Development Approach
Two important facets of proper treatment of information as a product are to understand the
information needs of the customer and to manage information as the product of a well-defined production
process. The procedure for generating the current-state maps adhered to these points and closely followed
the procedures suggestion by Lee, et al. in Journey to Data Quality.

1. Choose the IP to be mapped Choose the data elements that constitute the basic building blocks of
the IP. The total TOR for the finished vaccine product was selected as the IP to be mapped. This
is the most important piece of information for the customer as it determines the efficacy of the
product. The data elements are the times that product is removed from and entered into cold
storage as the material is transferred and processed. These data points are used to calculate the
information product. The number of data elements does not change in the current-state and
future-state IP-Map because they are predefined and critical to the information product.
2. Identify the data collector, the data custodian, and the data consumer. Reviewing operating
procedures and observing production steps allowed for the identification of who is creating,
collecting, and entering data. In addition, information was collected about those who will use the
data to generate the IP.
3. Depict the IP by capturingthe flows of the data elements, their transformations,and the
connections between and amongflows. Reviewing operating procedures and observing data
transfers between cold storage units and production allowed for the identification of data
conversion and connections.
4. Identify the functionalroles. Identify the pertinent systems. Interviewing operators and
supervisors through the manufacturing site helped determine which departments were responsible
for which processing steps when procedures were unclear. (Lee, et al. 2006)

Once this information was collected, the current-state IP-Maps were generated. The first step in this
process was outlining the physical work flow. When the physical work flow was outlined, the data flow
was diagramed using the physical work flow as a skeleton for this process. Next, system infrastructures
were added to the data flow mapping. Finally, the organizational infrastructure and roles were
incorporated in the data flow map to create the final IP-Maps.
4.4 Current-State IP-Maps

4.4.1 Transfer of Bulk Materialfrom the Global Warehouse to the Filling and
Inspection Local Cold Room
The first process that was analyzed using IP-Mapping was the raw data generated and
manipulated as bulk vaccine material is transferred from the global cold storage warehouse to the local
cold storage room outside of the filling area. Figure 8 shows the IP-Map generated by this process. In
order to initiate movement of bulk vaccine, Checklist A is created by an operator from the
shipping/receiving department (DOC 1). The time the first container of bulk material is removed from the
global warehouse is written in DOC 1 by a shipping/receiving operator (RD 1). The data is generated just
outside the global cold storage warehouse (DS 1) and DOC I is attached to the first container of bulk
vaccine removed from the global warehouse. The designated number of bulk vaccine containers are
removed from the global cold storage warehouse and are transferred across an organizational boundary to
the local cold storage warehouse outside of the filling area (BB 1).

Bulk Bulk Materiall Bulk

Checklist A Tie u DOCiTransferred from Tm InChecklist B
Created WaWroouse - 1e to D1 D1,RD2- TOR Calculation Di Ces
DOCI WaeSe Fill/InapLocalStorage CdrmP1DOC2
05S 1 DS2

RD1, RD2

from
Fill/sp LocalStorage
Transferred RDl RD2 DOCito
CDOCII
to Warehouse
BB2 DocumentStorage
4 ST01

Figure 8: IP-Map for the Transfer of Bulk Material from the Global Warehouse
to the Filling and Inspection Local Cold Room

The checklist attached to the first pallet of bulk vaccine is removed by an operator from the
filling/inspection area before the container enters the local warehouse. The time the last container of bulk
material enters the local warehouse is written in DOC 1 by a filling/inspection operator (RD2). The data is
generated just outside the local cold storage room (DS2). The raw data generated in this process, RDI and
RD2, is used to calculate the time out-of-refrigeration for the transfer of bulk material from the global
warehouse to the local cold storage outside the filling area (CD1). The calculation is captured by the P1
processing block and is completed by an operator from filling/inspection. Once the TOR calculation of P1
is complete, DOC 1 is transferred back across an organizational boundary from the storage warehouse
outside of the filling area to the global warehouse (BB2). DOCI is then stored by a shipping/receiving
operator in a filing cabinet in the global warehouse (STO 1).

The TOR data CD1 is transferred to Checklist B (DOC2). This document is created by an
operator from the filling/inspection department and is attached to the last container of bulk material that
entered the local cold storage room outside the filling department. The document is used to capture
information from the next two manufacturing processes, filling and inspection.

4.4.2 Fillingand Inspection Processes

The second process that was analyzed using IP-Mapping was the raw data generated and
manipulated as bulk vaccine material is removed from containers, formulated with stabilizers and
adjuvant, filled into vials or syringes, and inspected for quality issues. Figure 9 shows the IP-Map
generated by these processes. DOC2 is removed from the last container of bulk material to enter the
filling cold storage room and this document is used to record information for the next two processes. The
first decision occurs once DOC2 is recovered; the processes of formulation/filling and inspection can
either occur continuously or intermittently. Filled material can proceed directly to an automated
inspection line or it can be returned to the local cold storage site and manually inspected at a later time.
Intermittent filling and inspection occurs when the production schedule for automated inspection lines is
full or when the automated equipment is having mechanical difficulties.

Filling and inspection occurring continuously will be discussed first. The bulk vaccine material is
removed to DS2, the area just outside the local cold storage room. The time the first container of bulk
material is removed from the local cold storage room is recorded in DOC2 by a filling operator (RD3).
The designated number of bulk vaccine containers are removed from the local cold storage room and are
filled and inspected. During the course of these processes, a disruption can occur and all of the bulk
vaccine containers, or filled pallets of secondary material depending on the time of the disruption, can be
returned to the local cold storage warehouse. These steps do not always occur and are indicated by a
dashed line in the IP-Map. The time the last container of bulk material, or pallet of filled material, is
returned to the local cold storage room is recorded in DOC2 by a filling/inspection operator (RD4). When
processing is ready to continue, the time the first container of bulk vaccine or pallet of filled product is
removed from local cold storage is recorded in DOC2 by a filling/inspection operator (RD5). When
inspection is complete, the time the last pallet of filled/inspected product enters the cold room is recorded
in DOC2 by an inspection operator (RD6). All of these raw data points are generated at DS2 just as
material is either entering or leaving the local cold storage outside of the filling area.
 -.----. 0 RD7
--- CD1, -CD1, RD7,
RDB, RD9

Secondary Secondary
Product CDI, RD7, Product
Time In RD o Time Out
Coldroom Coldroom
DS2 DS2

Figure 9: IP-Map for the Filling and Inspection Processes

The raw data generated in this process, RD3 through RD6, and the TOR data from the transfer of
bulk material, CD1, is used to calculate the time out-of-refrigeration for the continuous filling and
inspection processes (CD2). The calculation is captured by the P2 processing block and is completed by
an operator from filling/inspection. At this point the TOR data is reviewed against limits for these two
processing steps. If the TOR limit was exceeded, an email is generated letting the supervisors of the next
processing step, packaging, know they have less time to complete their phase of processing than expected
(DOC3). The email transfers across an organizational boundary as it is sent from a filling/inspection
supervisor to a packaging supervisor (BB3). DOC2 is then incorporated in the filling and inspection
batch record (DOC5). If the TOR data is within the limits for filling and inspection, no email is sent to
packaging and DOC2 is directly incorporated with the DOC5.

Filling and inspection occurring intermittently will be discussed next. The bulk vaccine material
is removed to DS2, the areajust outside the local cold storage room, for filling. The time the first
container of bulk material is removed from the local cold storage room is recorded in DOC2 by a filling
operator (RD7). The designated number of bulk vaccine containers are removed from the local cold
storage room and are filled. During the course of filling, a disruption can occur and all of the bulk vaccine
containers can be returned to the local cold storage warehouse. These steps do not always occur and are
indicated by a dashed line in the IP-Map. The time the last container of bulk material is returned to the
local cold storage room is recorded in DOC2 by a filling operator (RD8). When processing is ready to
continue, the time the first container of bulk vaccine is removed from the local cold storage is recorded in
DOC2 by a filling operator (RD9). When filling is complete, the time the last pallet of filled product
enters the cold room is recorded in DOC2 by a filling operator (RD10). All of these raw data points are
generated at DS2 just as material is either entering or leaving the local cold storage outside of the filling
area.

The filled vaccine material is next removed to DS2, the area just outside the local cold storage
room. The time the first pallet of filled material is removed from the local cold storage room is recorded
in DOC2 by an inspection operator (RDI 1). The designated number of pallets with filled vaccine product
are removed from the local cold storage room and are inspected. During the course of inspection, a
disruption can occur and all of the filled pallets of secondary material can be returned to the local cold
storage warehouse. These steps do not always occur and are indicated by a dashed line in the IP-Map. The
time the last pallet of filled material is returned to the local cold storage room is recorded in DOC2 by an
inspection operator (RD 12). When inspection is ready to continue, the time the first pallet of filled
product is removed from local cold storage is recorded in DOC2 by an inspection operator (RD13). When
inspection is complete, the time the last pallet of inspected product enters the cold room is recorded in
DOC2 by an inspection operator (RD14). All of these raw data points are generated at DS2 just as
material is either entering or leaving the local cold storage outside of the filling area.

The raw data generated in this process, RD7 through RD 14, and the TOR data from the transfer
of bulk material, CDI, is used to calculate the time out-of-refrigeration for the intermittent filling and
inspection processes (CD3). The calculation is captured by the P3 processing block and is completed by
an operator from filling/inspection. At this point the TOR data is reviewed against limits for these two
processing steps. If the TOR limit was exceeded, an email is generated letting the supervisors of the next
processing step, packaging, know they have less time to complete their phase of processing than expected
(DOC4). The email transfers across an organizational boundary as it is sent from a filling/inspection
supervisor to a packaging supervisor (BB3). DOC2 is then incorporated in the filling and inspection
batch record (DOC5). If the TOR data is within the limits for filling and inspection, no email is sent to
packaging and DOC2 is directly incorporated with the DOC5.

DOC5 with the incorporated DOC2, regardless of whether the filling and inspection steps
occurred continuously or intermittently, is sent across an organizational boundary by an inspection
supervisor to a record retention supervisor in another building (BB4). The batch record is then stored in
the record retention archive for at least one year after the expiry of the product (STO2) (FDA 2010).

4.4.3 Transfer of Filled/InspectedProductfrom the Filling and Inspection Local

Cold Room to the Packagingand Labeling Local Cold Room
The third process that was analyzed using IP-Mapping was the raw data generated and
manipulated as filled and inspected material is transferred from the local cold storage room outside of the
filling area to the local cold storage room outside of the packaging area via the global cold storage
warehouse. Filled/inspected product inventory is maintained in the global warehouse until the end
consumer country has been identified and the material is ready to be packaged and labeled. Figure 10
shows the IP-Map generated by this process. In order to initiate movement of filled/inspected material,
Checklist A is created by an operator from the filling/inspection department (DOC6). The time the first
pallet of inspected material is removed from the local cold room is written in DOC6 by a
filling/inspection operator (RD15). The data is generated just outside the global cold storage warehouse
(DS2) and DOC6 is attached to the first pallet of inspected material removed from the local cold room.
The designated number of pallets of filled/inspected material are removed from the local cold room
outside of the filling area and are transferred across an organizational boundary to the global warehouse
(BB2).

Fill/lnsp Fill/Inap Material/ Fill/Insp Fill/Inap

Checklist A Product DOC6 Transferred from Product Product
Created Time Out -RD1 Local Storage to RD15-w Time In -RD15, RD16-* Time Out
DOC6 Coidroom Warehouse Warehouse Warehouse
DS2 1312 DS1 05S1

RD15, RD16, RD17

Fill/Insp Material/ Fill/Insp

DOC6 Transferred from Product Checklist C
Warehouse to RD15 16, Time In RD15, RD16 TOR Callation 0 Created
Pkg/Label Local Storage R07 Coldroom RD7 D8DOC7
BB5 D53

RD15, RD16,
RD17, RD18

DOC6 Transferred from

Pkg/Label Local Storage RD15, RD16,
to Warehouse RD17, RD18 Doc to
1316 DocumentStorage
STOI

Figure 10: IP-Map for the Transfer of Filled/Inspected Product from the Filling and Inspection
Local Cold Room to the Packaging and Labeling Local Cold Room

The checklist attached to the first pallet of filled/inspected material is removed by an operator
from the global warehouse before the pallet enters the warehouse. The time the last pallet of
filled/inspected material enters the global warehouse is written in DOC6 by a global warehouse operator
(RD 16). The data is generated just outside the global warehouse (DS 1). DOC6 is attached to the last
pallet of filled/inspected material to enter the global warehouse and remains there until the material is
ready for further processing. Once the material is ready to be transferred to the local warehouse outside of
the packaging area, DOC6 is retrieved from the last pallet of material by a global warehouse operator.

The time the first pallet of filled and inspected material is removed from the global warehouse is
written in DOC6 by a shipping/receiving operator (RD 17). The data is generated just outside the global
cold storage warehouse (DS 1) and DOC6 is attached to the first pallet of filled/inspected material
removed from the global warehouse. The designated number of filled/inspected pallets of material are
removed from the global cold storage warehouse and are transferred across an organizational boundary to
the local cold storage warehouse outside of the packaging area (BB5).

The checklist attached to the first pallet of filled/inspected material is removed by an operator
from the packaging/labeling area before the pallet enters the local warehouse. The time the last pallet of
filled/inspected material enters the local warehouse is written in DOC6 by a packaging/labeling operator
(RD 18). The data is generated just outside the local cold storage room (DS3). The raw data generated in
this process, RD 15 through RD18, is used to calculate the time out-of-refrigeration for the transfer of
material from the local cold storage site outside the filling area to the local cold storage site outside the
packaging area via the global warehouse (CD4). The calculation is captured by the P4 processing block
and is completed by an operator from packaging/labeling. Once the TOR calculation of P4 is complete,
DOC6 is transferred back across an organizational boundary from the storage warehouse outside of the
packaging area to the global warehouse (BB6). DOC6 is then stored by a shipping/receiving operator in a
filing cabinet in the global warehouse (STO 1).

The TOR data CD4 is transferred to Checklist C (DOC7). This document is created by an
operator from the packaging/labeling department and is attached to the last pallet of filled/inspected
material that entered the local cold storage outside the packaging department. The document is used to
capture information from the next two manufacturing processes, packaging and labeling.

4.4.4 Packagingand Labeling Processes

The fourth process that was analyzed using IP-Mapping was the raw data generated and
manipulated as filled/inspected material is removed from pallets, set into blister packaging, matched with
safety and use instructions, and labeled. Figure 11 shows the IP-Map generated by these processes. DOC7
is removed from the last pallet of filled/inspected material to enter the packaging cold storage room and
this document is used to record information for the next two processes. If the processing steps of filling
and inspection exceeded their time out-of-refrigeration limit, the amount of time that exceeded the alarm
limit is added to DOC7 by way of the email DOC3 or DOC4. After this TOR data is potentially added to
DOC7, a decision occurs; the processes of packaging and labeling can either occur continuously or
intermittently. Packaged material can proceed directly to an automated labeling line or it can be returned
to the global warehouse and labeled at a later time once the destination country of the customer is known.
Continuous processing is usually selected if a TOR alarm limit was exceeded in a previous process.
Continuous processing requires the associated material to be out-of-refrigeration for less time and allows
for the entire batch to remain under its total TOR alarm limit.

CD2 or CD3, RD23,RD24

A
kg Material/DOC
Time Out Time In ut DOC9Transferred from TmI
0009 Coldroom Wareo use Warehouse Waes WarehousetoCoom
053 OS1
i Local Storage DS3
BB5

CD2or CD3, CD2 or CD3, RD23, CD2 or CD3 RD23 CD2or CD3 CD2 or 3 23 CD2 or CD3, RD23,
RD3 Figr
D4R2,R2 e 11: IP-Ma D4 D5 for2 th 23, R24,
RD25, RD26 RD2
nRD24
RD26, RD27
. R24, RD25,
RD2, RD27

Figure 11: IF-Map for the Packaging and Labeling Processes

Packaging and labeling occurring continuously will be discussed first. The filled/inspected
material is removed to DS3, the area just outside the local cold storage room. The time the first pallet of
filled/inspected material is removed from the local cold storage room is recorded in DOC7 by a packaging
operator (RD 19). The designated number of pallets with filled/inspected vaccine are removed from the
local cold storage room and are packaged and labeled. During the course of these processes, a disruption
can occur and all of the filled/inspected pallets of material or packaged pallets of material, depending on

38
the time of the disruption, can be returned to the local cold storage warehouse. These steps do not always
occur and are indicated by a dashed line in the IP-Map. The time the last pallet of filled/inspected
material, or pallet of packaged material, is returned to the local cold storage room is recorded in DOC7 by
a packaging/labeling operator (RD20). When processing is ready to continue, the time the first pallet of
filled/inspected material or pallet of packaged material is removed from local cold storage is recorded in
DOC7 by a packaging/labeling operator (RD2 1). When labeling is complete, the time the last pallet of
packaged/labeled product enters the cold room is recorded in DOC7 by a labeling operator (RD22). All
of these raw data points are generated at DS3 just as material is either entering or leaving the local cold
storage outside of the packaging area.

The raw data generated in this process, RD19 through RD22, the TOR data from the filling and
inspection processes, CD2 or CD3, and TOR data from the transfer of filled/inspected product, CD4, is
used to calculate the time out-of-refrigeration for the continuous packaging and labeling processes (CD5).
The calculation is captured by the P5 processing block and is completed by an operator from
packaging/labeling. At this point the TOR data is reviewed against limits for these two processing steps.
If the TOR limit was exceeded, an email is generated letting the quality group know the batch has
exceeded its TOR limit (DOC8). The email transfers across an organizational boundary as it is sent from a
packaging/labeling supervisor to personnel in the quality department (BB7). DOC7 is then incorporated
in the packaging and labeling batch record (DOC 11). If the TOR data is within the limits for packaging
and labeling, no email is sent to the quality group and DOC7 is directly incorporated with the DOC 11.

Packaging and labeling occurring intermittently will be discussed next. Filled/inspected material
is removed to DS3, the area just outside the local cold storage room, for packaging. The time the first
pallet of filled/inspected material is removed from the local cold storage room is recorded in DOC7 by a
packaging operator (RD23). Once packaging is complete, the time the last pallet of packaged material is
returned to the local cold room is recorded in DOC7 by a packaging operator (RD24). In between the
packaging and labeling steps, the material can be returned to the global warehouse for long term storage
prior to labeling and shipping.

In order to initiate the transfer of packaged product back to the global warehouse for long term
storage, Checklist A is created by an operator in the packaging area (DOC9). DOC7 and DOC9 now
travel together but all data generated from the transfer of material to and from the global warehouse is
documented in DOC9. These steps do not always occur and are indicated by a dashed line in the IP-Map.
The time the first pallet of packaged material is removed from the local cold room is written in DOC9 by
a packaging operator (RD25). The data is generated just outside the local cold storage (DS3). DOC9 and
DOC7 are attached to the first pallet of packaged material removed from the local cold room. The
designated number of pallets of packaged material are removed from the local cold room outside of the
packaging area and are transferred across an organizational boundary to the global warehouse (BB6).

DOC7 and DOC9 are removed from the first pallet of packaged material by an operator from the
global warehouse before the pallet enters the warehouse. The time the last pallet of packaged material
enters the global warehouse is written in DOC9 by a global warehouse operator (RD26). The data is
generated just outside the global warehouse (DS 1). DOC7 and DOC9 are attached to the last pallet of
packaged material to enter the global warehouse and they remain there until the material is ready for
further processing. Once the material is ready to be transferred to the local warehouse outside of the
packaging area, DOC7 and DOC9 are retrieved from the last pallet of material by a global warehouse
operator.

The time the first pallet of packaged material is removed from the global warehouse is written in
DOC9 by a warehouse operator (RD27). The data is generated just outside the global cold storage
warehouse (DS 1). DOC7 and DOC9 are attached to the first pallet of packaged material removed from
the global warehouse. The designated number of pallets of packaged material are removed from the
global cold storage warehouse and are transferred across an organizational boundary to the local cold
storage warehouse outside of the packaging area (BB5).

The checklist attached to the first pallet of packaged material is removed by an operator from the
packaging/labeling area before the pallet enters the local warehouse. The time the last pallet of packaged
material enters the local warehouse is written in DOC9 by a packaging/labeling operator (RD28). The
data is generated just outside the local cold storage room (DS3). When labeling is ready to be initiated,
the time the first pallet of packaged material is removed from the local cold storage is recorded in DOC7
by a packaging/labeling supervisor (RD29). When labeling is complete, the time the last pallet of
packaged/labeled product enters the cold room is recorded in DOC7 by a labeling operator (RD30). These
raw data points are generated at DS3 just as material is either entering or leaving the local cold storage
outside of the packaging area.

The raw data generated in this process, RD23 through RD30, is used to calculate the time out-of-
refrigeration for intermittent packaging and labeling processes (CD6). The calculation is captured by the
P6 processing block and is completed by an operator from packaging/labeling. At this point the TOR data
is reviewed against limits for these two processing steps. If the TOR limit was exceeded, an email is
generated letting the quality group know the batch has exceeded its TOR limit (DOC 10). The email
transfers across an organizational boundary as it is sent from a packaging/labeling supervisor to personnel
in the quality department (BB7). DOC7 is then incorporated in the packaging and labeling batch record
(DOC 11). If the TOR data is within the limits for packaging and labeling, no email is sent to the quality
group and DOC7 is directly incorporated with the DOC 11. After the TOR calculation at P6, DOC9 is
sent across an organizational boundary from the packaging/labeling department to the warehouse (BB6).
DOC9 is then stored by a shipping/receiving operator in a filing cabinet in the global warehouse (STO 1).

DOC 11 with the incorporated DOC7, regardless of whether the filling and inspection steps
occurred continuously or intermittently, is sent across an organizational boundary by a labeling supervisor
to a record retention supervisor in another building (BB7). The batch record is then stored in the record
retention archive for at least one year after the expiry of the product (STO2) (FDA 2010).

4.4.5 Transferof FinishedProductfrom the Packagingand Labeling Local Cold

Room to the Global Warehouse
The fifth process that was analyzed using IP-Mapping was the raw data generated and
manipulated as finished product is transferred from the local cold storage room outside of the packaging
area to the global cold storage warehouse for shipping. Figure 12 shows the IP-Map generated by this
process. In order to initiate movement of the finished product, Checklist A is created by an operator from
the packaging/labeling department (DOC 12). The time the first pallet of finished material is removed
from the local cold room is written in DOC 12 by a packaging/labeling operator (RD3 1). The data is
generated just outside the local cold storage room outside the packaging area (DS3) and DOC 12 is
attached to the first pallet of finished product removed from the local cold room. The designated number
of pallets of finished material are removed from the local cold room outside of the packaging area and are
transferred across an organizational boundary to the global warehouse (BB5).

Finished Finished
Checklist A d ProductD31
Fini-D3
d -R3duD2 TORCalculation 7roCuc
Created TimeOut RD31e- TrnfreDrmPg 31i TimeIn RD31,RD32o-
DOC12 Cokiroom Lae oWrhueWarehouse -C7 D 12t
053 BSDS1 STOI

CD7

EmailC 13 Transferred
DOC from
Created D7 Warehouse
to Quality
DOC13 BBS

Figure 12: IP-Map for the Transfer of Finished Product from the Packaging and Labeling
Local Cold Room to the Global Warehouse

The checklist attached to the first pallet of finished material is removed by an operator from the
global warehouse before the pallet enters the warehouse. The time the last pallet of finished material
enters the global warehouse is written in DOC12 by a global warehouse operator (RD32). The data is
generated just outside the global warehouse (DS 1). The finished product is now managed by a set of
procedures outside of the scope of this project as it waits to be shipped to a customer. The raw data
generated in this process, RD31 and RD32, is used to calculate the time out-of-refrigeration for the
transfer of finished material from the local cold storage outside the packaging area to the global
warehouse (CD7). The calculation is captured by the P7 processing block and is completed by an operator
from the global warehouse. Once the TOR calculation of P7 is complete, DOC 12 is stored by a
shipping/receiving operator in a filing cabinet in the global warehouse (STO 1). An operator from the
warehouse also generates an email with the TOR total calculated in P7 (DOC 13). The email is sent across
an organizational boundary from the warehouse to a quality supervisor (BB8).

4.4.6 FinishedProductTime Out-of-RefrigerationData Review

The final process that was analyzed using IP-Mapping was the quality review of TOR data for the
finished vaccine product. Figure 13 shows the IP-Map generated by this process. A quality supervisor
collects the TOR data from the final transfer of finished product to the global warehouse (DOC 12), from
the filling/inspection batch record (DOC5), and from the packaging/labeling batch record (DOC 11). The
TOR calculation from DOC 12, from the filling/inspection batch record, and from the packaging/labeling
batch record is checked by a quality supervisor against the associated raw data and calculations (QC 1,
QC2, QC3). DOC8, DOC 10, and DOC13 are emails from processing supervisors to the quality
department to inform them that the finished product has exceeded its TOR limit. These emails are used as
a warning system. Quality supervisors review the raw data of DOC 12, DOC5, and DOC 11 to verify the
TOR calculations from the major processing steps. If there are any irregularities with the raw data entries
or with the calculations associated with the quality checks of DOC 12, DOC5, or DOC 11, an investigation
is opened by the quality department to resolve these issues (DOC 13, DOC14, DOC 15).

Once the TOR calculations from DOC 12, DOC5, and DOC 1 are verified, this data is then used
to calculate a total time out-of-refrigeration for the finished vaccine lot (CD8). The calculation is captured
by the P8 processing block and is completed by a quality supervisor. The "*" associated with the
component data inputs to P8 indicates that the values might be different from the starting value of CD7,
CD2 or CD3, and CD5 or CD6 if a quality investigation is required and confirms an incorrect data entry
or manipulation. The total TOR for the finished product is one component of the release status for the lot
of material. If the TOR for the finished lot exceeds the total TOR limit, an investigation is initiated by the
quality department (DOC 13). The finished material is placed into quarantine and cannot be released to the
marketplace until the quality investigation is completed, and the material deemed safe for release. If the
total TOR for the finished product cannot be justified through additional stability studies, the material
must be discarded.

Incorrect
TORData
Check Investigation
ito
Checklist
A 7 C TORResult
DOC12 DoC13
Inveshg
ion into
TORResult C0
DOC13

Correct
Yes,CTB
Ino rrct CD*r
TORData
Bttneor D r Check Does RRelease
F i2re 1 I -C2 Investigation
into Finished
Product exceedimitAcceCD
Oy-f e aton Da t e e
Aftere t s TORResulti Cs or CDtRalcutapton ve Fshe ltdartet te
Dthe
finPihdProduct T t O fCBo po 03

iret i CD5 oreCD in

,.e. ta rouc i

TORDateF
futurel ( ) Check
step cC3l r neetigtonmrto
BatchRecordT cDorCDr TORResult
DOCit DOC15

lcorract_ _

e
uato ,C8.ne
T R cl
-b sd
c ed p R
Figure ins13:iLP-Map
ed podu
fort the
wh c Finished
s heuaiy-h Product Time Out-of-Refrigeration Data Review
f
TO rth

After the investigation is completed and approved by the quality department, the total TOR for
the finished product crosses an information system boundary. The total TOR for the finished product is
transferred from paper to an electronic database (LSB 1). The customer for the final information product is
the product release department. The release department awaits the final electronic version of the total
TOR for the finished product which is the quality-checked paper-based TOR calculation, CD8, entered
into the electronic database (IPI). Once the information product is complete, it is accepted by the release
group (CB 1). The final information product is stored in an electronic database for ease of access in the
future (STO3). If the total TOR for the finished product is within the total TOR limit, the data directly
crosses the information system boundary into the electronic database. The finished product is now one
step closer to being released to consumers.

4.5 Cold Chain Management Concerns Identified by the IP-Maps

The current-state IP-Maps reveal a number of important facts about the total TOR calculation for
finished vaccine material. These IP-Maps highlight the transfer of information across organizational
boundaries, the generation of emails to transfer data and notify' supervisors of exceeded TOR limits, and
the need to quality check data and calculations. Each of these facts jeopardizes the integrity of the data
used to generate the final information product, total TOR for the finished vaccine material.
 When data travels across organizational boundaries, the chance of losing or damaging the data is
high. Individuals responsible for the integrity of the data must ensure that the documents containing the
data are delivered and received appropriately. Documents that contain critical data can easily be lost or
misplaced in the hectic pace of the manufacturing floor. Movement of the data also increases the risk of
the data being altered or destroyed accidentally. Data sheets are susceptible to tears, rips, stains, and other
forms of permanent damage. Supervisors take great care to ensure that procedures are in place for the
safe transfer of documents that contain data.

Data generated in the current cold chain travels across organizational boundaries a minimum of
nine times throughout processing. Data physically moves along with the documents in which it is
recorded. The documents travel from the global warehouse to the local cold storage room outside of
filling, from the local cold storage room outside filling to the local cold storage room outside packaging,
and from the local cold storage room outside packaging to the global warehouse. Documents are also
compiled with batch records and transferred from production areas to designated document retention
areas. During the physical transfer of material, associated documents could be misplaced as they travel
across the site and between buildings.

Documents that travel with product are usually attached to a pallet of product during relocation.
When pallets of material are removed from one cold storage site and sent to another cold storage site, the
time the first pallet of material is removed from cold storage is written in the associated document and the
document is attached to the first pallet. When the first pallet of material arrives at the desired cold storage
location, the document containing data is removed from that pallet and held by an operator in the area.
The operator passes the document onto another operator if his shift ends or if he needs to leave the area
for another reason. Once the last pallet of material enters the cold storage area, an operator in that area
writes down the time the last pallet entered the cold room in the document. If additional TOR data needs
to be added to the document, the document is attached to the last pallet that entered cold storage.

The document remains attached to the last pallet of material until that material is ready for further
processing. Once the material is going to be processed further, the document needs to be retrieved from
inside the cold storage unit. Over time, pallets of material are moved around inside the cold storage unit.
Finding the pallet with the document containing the appropriate data can be a time consuming process
that often requires a great deal of rearranging product in the warehouse to get to the required documents.

When TOR alarms occur in processing, the supervisor in the area where the deviation occurred is
required to notify the supervisor of the next processing step about the alarm. The amount of time that
exceeds the TOR limit from the processing step is passed onto the next processing step. This information
is communicated via email from the processing supervisor where the alarm occurred to the processing
supervisor of the next manufacturing step. For example, assume the TOR for all processes up to
inspection is three hours greater than the alarm limit. According to procedure, the inspection supervisor
generates an email for the packaging supervisor letting the packaging supervisor know that the product
has exceeded is TOR limit and that the packaging and labeling steps have three less hours to be
completed. The packaging supervisor is now responsible for ensuring this information is included in the
documents that capture TOR data for packaging and labeling.

Usually the filled/inspected material would be packaged and labeled shortly after the inspection
step is complete. However, there are some instances when a mechanical failure occurs causing delays in
the production schedule. Additionally, an unforeseen shortage in another product line could cause the
shared packaging and labeling lines to have a full schedule. The filled/inspected material that has
exceeded its TOR alarm limit by 3 hours will not be scheduled for packaging and labeling for many
months. The supervisor who received the TOR alarm email must remember the alarm or risk exceeding
the TOR limit for the finished material. Alternatively, the supervisor could go back to the batch record
and review the TOR for the lot to see if there was an alarm, but this is a time consuming process that
requires walking across the site, getting access to the retention area, finding the appropriate document,
and reviewing the data.

The fact that data is manually entered into documents means that a quality check of the data must
occur before the product is released to consumers. Additionally, calculations are completed manually and
these must also be checked by a quality supervisor. Because all data is entered and manipulated manually,
and this data is not converted across an information system boundary to an automated system, there is no
real time monitoring of the data. All monitoring of time out-of-refrigeration data during processing is
completed using cumbersome data retrievals from paper sources. Personnel from quality or release that
may be interested in the time out-of-refrigeration of a particular lot would need to find the associated
documents in production or contact supervisors responsible for the data. Decisions that require immediate
data checks have to be delayed until the required information is gathered.
CHAPTER 5: FUTURE-STATE INFORMATION PRODUCT
MAPS (IP-MAPS)
5.1 Future-State IP-Maps
Implementation of an MES has the potential to eliminate concerns about data integrity associated
with the current paper-based cold chain management system. The following future-state IP-Maps diagram
the flow of information used to create an information product if an MES were managing the cold chain.
The flow of product is not changed in any way during this exercise. The only difference in these IP-Maps
is how the MES manages the flow of information, creating value for the customer.

5.1.1 Transfer of Bulk Materialfrom the Global Warehouse to the Filling and
Inspection Local Cold Room
The first process that received a future-state IP-Map was the raw data generated and manipulated
as bulk vaccine material is transferred from the global cold storage warehouse to the local cold storage
room outside of the filling area. Figure 14 shows the future-state IP-Map for this process. In order to
initiate movement of bulk vaccine, a worksheet associated with product transfer is generated in the MES
by a planner (DOC1). The time the container of bulk material is removed from the global warehouse is
automatically recorded in DOC I by an automated tagging system (RD 1). The data is generated as the
container passes through the door of the global cold storage warehouse (DS 1). The time the container of
bulk material enters the local warehouse outside the filling area is automatically recorded in DOC I by an
automated tagging system (RD2). The data is generated as the container passes through the door of the
local cold storage area (DS2). The MES calculates the time out-of-refrigeration for the container of bulk
material (CD 1). The calculation is captured by the P1 processing block. The TOR data for the bulk
container is stored in a database and this information can be viewed by anyone who has access to the
MES interface (STO 1).

Bulk Bulk
Created s Time Dut Time In TOR Calculation CDI- DOCI to
Warehouse Coldroom -RD RD2 P1
DOC1 DS1 DS2 Database

Figure 14: Future-State IP-Map for the Transfer of Bulk Material from the Global Warehouse
to the Filling and Inspection Local Cold Room
5.1.2 Filling and Inspection Processes

The second process that received a future-state IP-Map was the raw data generated and manipulated as
bulk vaccine material is removed from containers, formulated with stabilizers and adjuvant, filled into
vials or syringes, and inspected for quality issues. Figure 15 shows the future-state IP-Map generated by
these processes. In order to initiate processing of bulk vaccine, a worksheet associated with the filling and
inspection processes is generated in the MES by a filling/inspection supervisor (DOC2). This worksheet
electronically links the TOR data-from the bulk containers to the TOR data of the associated filling and
inspection pallets of material. The first decision occurs once DOC2 is generated; the processes of
formulation/filling and inspection can either occur continuously or intermittently.

Filling and inspection occurring continuously will be discussed first. The time the bulk vaccine
container is removed from the local cold room is automatically recorded in DOC2 by an automated
tagging system (RD3). The data is generated as the container passes through the door of the local cold
room (DS2). During the course of these processes, a disruption can occur and all of the bulk vaccine
containers, or filled pallets of secondary material depending on the time of the disruption, can be returned
to the local cold storage warehouse. These steps do not always occur and are indicated by a dashed line in
the IP-Map. The time the container of bulk material, or pallet of filled material, is returned to the local
cold storage room is automatically recorded in DOC2 (RD4). When processing is ready to continue, the
time the container of bulk vaccine or pallet of filled product is removed from local cold storage is
automatically recorded in DOC2 (RD5). When inspection is complete, the time the pallet of
filled/inspected product enters the cold room is automatically recorded in DOC2 (RD6). The raw data
points RD4, RD5, and RD6 are recorded in DOC2 by an automated tagging system at DS2 just as
material passes through the door of the local cold storage outside of the filling area.
 Figure 15: Future-State IP-Map for the Filling and Inspection Processes

The MES uses the raw data generated in this process, RD3 through RD6, to calculate the time
out-of-refrigeration for the continuous filling and inspection processes (CD2). The calculation is captured
by the P2 processing block. The TOR data for the filling and inspection processes is reviewed against
limits for these two processing steps. If the TOR limit was exceeded, a warning is generated in the MES
(DOC3). Before the packaging supervisor can generate a worksheet for processing the filled/inspected
pallet, he must acknowledge in the MES that the processing time for packaging and labeling will be
shorter based on the previous deviation. Quality supervisors with access to the MES will be able to track
the lot closely and put measures in place to prevent the lot from exceeding its total TOR limit. If the TOR
data is within the limits for filling and inspection, no warning is generated in the MES. The TOR data for
the filled/inspected pallet is stored in a database and this information can be viewed by anyone who has
access to the MES interface (STO 1).

Filling and inspection occurring intermittently will be discussed next. The time the bulk vaccine
container is removed from the local cold room is automatically recorded in DOC2 by an automated
tagging system (RD7). The data is generated as the container passes through the door of the local cold
room (DS2). During the course of filling, a disruption can occur and all of the bulk vaccine containers can
be returned to the local cold storage warehouse. These steps do not always occur and are indicated by a
dashed line in the IP-Map. The time the container of bulk material is returned to the local cold storage
room is automatically recorded in DOC2 (RD8). When processing is ready to continue, the time the
container of bulk vaccine is removed from local cold storage is automatically recorded in DOC2 (RD9).
When filling is complete, the time the pallet of filled product enters the cold room is automatically
recorded in DOC2 (RD 10). Raw data points RD7 through RD10 are recorded in DOC2 by an automated
tagging system at DS2 just as material passes through the door of the local cold storage outside of the
filling area.

The time the filled vaccine pallet is removed for inspection from the local cold room is
automatically recorded in DOC2 by an automated tagging system (RD 11). During the course of filling, a
disruption can occur and all of the filled vaccine pallets of material can be returned to the local cold
storage warehouse. These steps do not always occur and are indicated by a dashed line in the IP-Map. The
time the pallet of filled material is returned to the local cold storage room is automatically recorded in
DOC2 (RD 12). When inspection is ready to continue, the time the pallet of filled material is removed
from local cold storage is automatically recorded in DOC2 (RD 13). When filling is complete, the time the
pallet of filled product enters the cold room is automatically recorded in DOC2 (RD 14). Raw data points
RDI 1 through RD14 are recorded in DOC2 by an automated tagging system at DS2 just as material
passes through the door of the local cold storage outside of the filling area.

The MES uses the raw data generated in this process, RD7 through RD 14, to calculate the time
out-of-refrigeration for the intermittent filling and inspection processes (CD3). The calculation is captured
by the P3 processing block. The TOR data for the filling and inspection processes is reviewed against
limits for these two processing steps. If the TOR limit was exceeded, a warning is generated in the MES
(DOC4). Before the packaging supervisor can generate a worksheet for processing the filled/inspected
pallet, he must acknowledge in the MES that the processing time for packaging and labeling will be
shorter based on the previous deviation. Quality supervisors with access to the MES will be able to track
the lot closely and put measures in place to prevent the lot from exceeding its total TOR limit. If the TOR
data is within the limits for filling and inspection, no warning is generated in the MES. The TOR data for
the filled/inspected pallet is stored in a database and this information can be viewed by anyone who has
access to the MES interface (STO 1).

5.1.3 Transfer of Filled/InspectedProductfrom the Fillingand Inspection Local

Cold Room to the Packagingand Labeling Local Cold Room
The third process that received a future-state IP-Map was the raw data generated and manipulated
as filled and inspected material is transferred from the local cold storage room outside of the filling area
to the local cold storage room outside of the packaging area via the global cold storage warehouse.
Filled/inspected product inventory is maintained in the global warehouse until the end consumer country
has been identified and the material is ready to be packaged and labeled. Figure 16 shows the future-state
IP-Maps generated by this process.

FiII/Insp FiII/Insp
MES Worksheet Product Product TOR Calculation
Created 0 Time Out -RD15-* Time In -RD15, RD16+ P4 -CD4-+ DOC5 to
DOC5 Coldroom Warehouse Database
DS2DS ST

Fi11l/lnsp Fill/Insp
MES Worksheet Product Product TOR Calculation
Created Time Out -RD17+ Time In -RD17, RD18+ P5 CD5 DOC6 to
DOC6 Warehouse Coldroom Database
DS1 DS3 STO1

Figure 16: Future-State IP-Maps for the Transfer of Filled/Inspected Product from the
Filling and Inspection Local Cold Room to the Packaging and Labeling Local Cold Room

In order to initiate movement of filled/inspected material, a worksheet associated with product

transfer is generated in the MES by a planner (DOC5). The time the pallet of filled/inspected material is
removed from the local cold room is automatically recorded in DOC5 by an automated tagging system
(RD 15). The data is generated as the pallet passes through the door of the local cold room outside of the
filling area (DS2). The time the pallet of filled/inspected material enters the global warehouse is
automatically recorded in DOC5 by an automated tagging system (RD 16). The data is generated as the
pallet of material passes through the door of the global warehouse (DS 1). The MES calculates the time
out-of-refrigeration for the pallet of filled/inspected material (CD4). The calculation is captured by the P4
processing block. The TOR data for the filled/inspected pallet is stored in a database and this information
can be viewed by anyone who has access to the MES interface (STO 1).

The transfer of filled/inspected material from the global warehouse for packaging and labeling is
also tracked by the MES. A worksheet associated with product transfer is generated in the MES by a
planner to initiate this movement (DOC6). The time the pallet of filled/inspected material is removed
from the global warehouse is automatically recorded in DOC6 by an automated tagging system (RD17).
The data is generated as the pallet passes through the door of the global warehouse (DS 1). The time the
pallet of filled/inspected material enters the local cold room outside of the packaging area is automatically
recorded in DOC6 by an automated tagging system (RD 18). The data is generated as the pallet of material
passes through the door of the local cold room (DS3). The MES calculates the time out-of-refrigeration
for the pallet of filled/inspected material (CD5). The calculation is captured by the P5 processing block.
The TOR data for the filled/inspected pallet is stored in a database and this information can be viewed by
anyone who has access to the MES interface (STO 1).

5.1.4 Packagingand Labeling Processes

The fourth process that received a future-state IP-Map was the raw data generated and
manipulated as filled/inspected material is removed from pallets, set into blister packaging, matched with
safety and use instructions, and labeled. Figure 17 shows the future-state IP-Map generated by these
processes. In order to initiate processing of filled/inspected vaccine, a worksheet associated with the
packaging and labeling processes is generated in the MES by a packaging/labeling supervisor (DOC7).
This worksheet electronically links the TOR data from the bulk containers and filled/inspected pallets of
material to the TOR data of the associated packaging and labeling pallets of material. The first decision
occurs once DOC7 is generated: the processes of packaging and labeling can either occur continuously or
intermittently. Packaged material can proceed directly to an automated labeling line or it can be returned
to the global warehouse and labeled at a later time once the destination country of the customer is known.
Continuous processing is usually selected if a TOR alarm limit was exceeded in a previous process.
Continuous processing requires the associated material to be out-of-refrigeration for less time and allows
for the entire batch to remain under its total TOR alarm limit.

Packaging and labeling occurring continuously will be discussed first. The time the
filled/inspected material is removed from the local cold room is automatically recorded in DOC7 by an
automated tagging system (RD 19). The data is generated as the pallet of material passes through the door
of the local cold room (DS3). During the course of these processes, a disruption can occur and the
filled/inspected pallet of material, or packaged pallet of material depending on the time of the disruption,
can be returned to the local cold storage warehouse. These steps do not always occur and are indicated by
a dashed line in the IP-Map. The time the pallet of filled/inspected material, or pallet of packaged
material, is returned to the local cold storage room is automatically recorded in DOC7 (RD20). When
processing is ready to continue, the time the pallet of filled/inspected material, or pallet of packaged
material, is removed from local cold storage is automatically recorded in DOC7 (RD2 1). When labeling is
complete, the time the pallet of packaged/labeled product enters the cold room is automatically recorded
in DOC7 (RD22). The raw data points RD20, RD21, and RD22 are recorded in DOC7 by an automated
tagging system at DS3 just as material passes through the door of the local cold storage outside of the
packaging area.
 Time Cut Time In
Pkg/Label RD1S, RD20, TOR Calculation De O
Coldroom CRD19eo n RD1 RD22 TO CD6 exceed i mitfor Yes, CD6 MES Warning D6
Fill/lnsp Pkg/Labe?
D3 DS3

RD19 RD19, RD20, RD21

No CD6
Secondary Secondary
Product Product
* Time In RD19, RD20 -- Time Out
Coldroom Coldroom
DS3 CS3

Lontinuous
DOC7 to
Continuousor Database
MES Worksheet
Created Intermittent
DOC7 Processing
DC

Intermittent No, CDD

Fill/loop Pkg Pkg Pkg RD23

TieCtTm n RTime imut RD23, Label DS TR Does TDR

DS3
~Coldroom
RD23-oo- R2-
RD2
DS3
TieI Coldroom
R2, RD29
TmOu
DS3
RD24--t
Coldroom
RD2S
Time In
TieIP9
RD29,
TO-acuain
aclto
D9 exceed i mit for
DS3
Cooroo RD30
RD24~ Pkg/Label?
TOR CacuSto
exedlm<o

No Data No Data CD9

MES Warning

CrkseedTime Time In TOR Calculation Crte Time Out Time In TOR Calculation
DC9 CD m Warehouse P7C10 Warehouse Coldroom P8
DS3 -S1 DS1 CC38

CC7 CDS

RD25 ----RD25, RD26-- ----------RD27 ----- RD27, RD28

DOC9 to DOC10 to
Database Database
STC01STC1

Figure 17: Future-State IP-Map for the Packaging and Labeling Processes

The MES uses the raw data generated in this process, RD 19 through RD22, to calculate the time
out-of-refrigeration for the continuous packaging and labeling processes (CD6). The calculation is
captured by the P6 processing block. The TOR data for the packaging and labeling processes is reviewed
against limits for these two processing steps. If the TOR limit was exceeded, a warning is generated in the
MES (DOC8). Before the quality supervisor can generate an MES form to release the material to the
marketplace, he must acknowledge the TOR alarm limit in the MES. Quality supervisors with access to
the MES will be able to track the remaining movement of the product closely and put measures in place to
prevent the lot from exceeding its total TOR limit. If the TOR data is within the limits for packaging and
labeling, no warning is generated in the MES. The TOR data for the finished product pallet of material is
stored in a database and this information can be viewed by anyone who has access to the MES interface
(STO 1).

Filling and inspection occurring intermittently will be discussed next. The time the
filled/inspected pallet of material is removed from the local cold room is automatically recorded in DOC7
by an automated tagging system (RD23). The data is generated as the pallet of material passes through the

52
door of the local cold room (DS3). Once packaging is completed, the time the pallet of packaged material
enters the local cold room is automatically recorded in DOC7 (RD24). RD24 is recorded by an automated
tagging system at DS3 just as material passes through the door of the local cold storage outside of the
packaging area. In between the packaging and labeling steps, the material can be returned to the global
warehouse for long term storage prior to labeling and shipping.

In order to initiate the transfer of packaged product back to the global warehouse for long term
storage, a worksheet associated with the movement of product to the global warehouse is generated in the
MES by a packaging/labeling supervisor (DOC9). These steps do not always occur and are indicated by a
dashed line in the IP-Map. The data associated with movement of material during packaging, RD23 and
RD24, remains with DOC7, the MES worksheet associated with packaging and labeling. The time the
pallet of packaged material is removed from the local cold room is automatically recorded in DOC9
(RD25). The data is generated by an automated tagging system just as the pallet passes through the door
of the local cold storage outside of the packaging area (DS3). The time the pallet of packaged material
enters the global warehouse is automatically recorded in DOC9 (RD26). The data is generated by an
automated tagging system just as the pallet passes through the door of the global warehouse (DS 1). The
MES uses the raw data generated in this process, RD25 and RD26, to calculate the time out-of-
refrigeration for the transfer of packaged material to the warehouse (CD7). The calculation is captured by
the P7 processing block. The TOR data for the pallet of packaged material is stored in a database and this
information can be viewed by anyone who has access to the MES interface (STO 1).

In order to initiate the return of packaged product from the global warehouse for labeling, a
worksheet associated with the movement of product from the global warehouse is generated in the MES
by a shipping/receiving supervisor (DOC 10). The time the pallet of packaged material is removed from
the global warehouse is automatically recorded in DOC 10 (RD27). The data is generated by an automated
tagging system just as the pallet passes through the door of the global cold storage warehouse (DS 1). The
time the pallet of packaged material enters the local cold storage is automatically recorded in DOC 10
(RD28). The data is generated by an automated tagging system just as the pallet passes through the door
of the local cold storage room outside the packaging area (DS3). The MES uses the raw data generated in
this process, RD27 and RD28, to calculate the time out-of-refrigeration for the transfer of packaged
material from the warehouse (CD8). The calculation is captured by the P8 processing block. The TOR
data for the pallet of packaged material is stored in a database and this information can be viewed by
anyone who has access to the MES interface (STO 1).
 When labeling is ready to be initiated, the time the pallet of packaged material is removed from
the local cold storage room is automatically recorded in DOC7 (RD29). When labeling is complete, the
time the pallet of finished product enters the cold room is automatically recorded in DOC7 (RD30). Raw
data points RD29 and RD30 are recorded in DOC7 by an automated tagging system at DS3 just as
material passes through the door of the local cold storage outside of the filling area.

The MES uses the raw data generated in this process, RD29 and RD30, and raw data stored
during the packaging of the filled/inspected pallet, RD 23 and RD24, to calculate the time out-of-
refrigeration for the intermittent packaging and labeling processes (CD9). The calculation is captured by
the P9 processing block. The TOR data for the packaging and labeling processes is reviewed against
limits for these two processing steps. If the TOR limit was exceeded, a warning is generated in the MES
(DOC 11). Before the quality supervisor can generate an MES form to release the material to the
marketplace, he must acknowledge the TOR alarm limit in the MES. Quality supervisors with access to
the MES will be able to track the remaining movement of the product closely and put measures in place to
prevent the lot from exceeding its total TOR limit. If the TOR data is within the limits for packaging and
labeling, no warning is generated in the MES. The TOR data for the pallet of finished product is stored in
a database and this information can be viewed by anyone who has access to the MES interface (STO 1).

5.1.5 Transfer of FinishedProductfrom the Packagingand Labeling Local Cold

Room to the Global Warehouse
The fifth process that received a future-state IP-Map was the raw data generated and manipulated
as finished product is transferred from the local cold storage room outside of the packaging area to the
global cold storage warehouse. Figure 18 shows the future-state IP-Map generated by this process. In
order to initiate movement of finished product, a worksheet associated with product transfer to the global
warehouse is generated in the MES by a planner (DOC 12). The time the pallet of finished product is
removed from the local cold room is automatically recorded in DOC 12 by an automated tagging system
(RD3 1). The data is generated as the pallet passes through the door of the local cold room outside of the
packaging area (DS3). The time the pallet of finished product enters the global warehouse is
automatically recorded in DOC 12 by an automated tagging system (RD3 2). The data is generated as the
container passes through the door of the global warehouse (DS 1). The MES calculates the time out-of-
refrigeration for the pallet of finished product (CD 10). The calculation is captured by the P 10 processing
block. The TOR data for the pallet of finished product is stored in a database and this information can be
viewed by anyone who has access to the MES interface (STO 1).
 FinihedFinished
MES Worksheet Product Product TOR Calculation
Created --- Time Out --RD31-o Time In --RD31, RD32+ P110 -CD10+ DOC 12 to
DOC12 Coldroom Warehouse Database
D3DS1 STOI

Figure 18: Future-State IP-Map for the Transfer of Finished Product from the
Packaging and Labeling Local Cold Room to the Global Warehouse

5.1.6 FinishedProduct Time Out-of-RefrigerationData Review

The final process that received a future-state IP-Map was the quality review of TOR data for the
finished vaccine product. Figure 19 shows the future-state IP-Map generated by this process. The TOR
data for the vaccine product is continually updated as it moves through processing. The accumulated time
out-of-refrigeration for the material is updated after every product transfer and processing step. Anyone
who has access to the MES can view the accumulated TOR for the material at any point during
processing. Once all processing steps are complete and the finished product is moved to the global
warehouse for shipping, the total TOR for the finished product is calculated.

The TOR data from the transfer of the bulk material (CD 1), filling and inspection (CD2 or CD3),
transfer of the filled/inspected product (CD4 and CD5), packaging and labeling (CD6 or CD9), transfer of
the packaged material if necessary (CD7 and CD8), and transfer of the finished product (CD10) is used to
calculate a total time out-of-refrigeration for the finished vaccine lot (CD 11). The calculation is captured
by the P11 processing block. The total TOR for the finished product is one component of the release
status for the lot of material. If the TOR for the finished lot exceeds the total TOR limit, an investigation
is initiated by the quality department (DOC13). The finished material is placed into quarantine and cannot
be released to the marketplace until the quality investigation is completed, and the material deemed safe
for release. If the total TOR for the finished product cannot be justified through additional stability
studies, the material must be discarded.
 MES Worksheet
Created CD1
DOC1

MES Worksheet
Created CD2 orCD3-
DOC2

into
Investigation
MES rksheet 0 TOR Result ~ CD11
DCretdD DOC13

Yes, CD1I
MES Worksheet
Created CD5.
DOC6

Finished Product DoesTOR Information Release

TOR Calculation - D1 exceedlimitfor System P1 Accepts
FiihdProduc Finished 1 Boundary TOR Data P1 Rlae est
P11 Product? ISB1 CB1 storedin Database
MES Worksheet CD6orCD
Created D6 or CD9
DOC7

MES Worksheet
Created ----- CD7-- -
DOC9

MES Worksheet
Created ---- ---- CD8---
DOC1O

MES Worksheet
Created D1C
DOC12

Figure 19: Future-State IP-Map for the Finished Product Time Out-of-Refrigeration Data Review

After the investigation is completed and approved by the quality department, the total TOR for
the finished product crosses an information system boundary. The total TOR for the finished product is
transferred from the MES to an electronic database (ISB 1). The customer for the final information
product is the product release department. The release department awaits the final TOR calculation,
CD 11, entered into the electronic database (IP 1). The final information product is stored in an electronic
database for ease of access in the future (STO2). If the total TOR for the finished product is within the
total TOR limit, the data directly crosses the information system boundary into the electronic database.
The finished product is now one step closer to being released to consumers.

5.2 Cold Chain Management Improvements Found in the Future-

State IP-Maps
The future-state IP-Maps reveal a number of improvements created by the implementation of the
MES. First, data used to calculate TOR for the vaccine material are no longer transferred across
organizational boundaries. Second, supervisors no longer need to be notified by upstream process
supervisors when TOR alarms occur. Finally, data is recorded and calculated automatically by the
automated system. All of these improvements ensure the integrity of the data for vaccine product release.
 The future-state IP-Maps highlight that the number of information transfers across organizational
boundaries is drastically reduced. All data points are automatically entered and stored in a database that
interfaces with the MES, completely eliminating the paper-based recording system. Documents
containing critical data are no longer physically attached to pallets of material as the material is
transferred from one cold storage area to another. This reduces the potential for documents being
misplaced or damaged on the hectic manufacturing floor. Supervisors no longer need to spend time
ensuring documents containing TOR data safely arrive at their intended destination. In addition,
documents are no longer attached to a pallet in the cold storage area when additional data points still need
to be added to the document. Implementation of the cold chain MES eliminates the need to repeatedly
enter cold storage to search for required documents.

When a TOR alarm occurs in processing, the supervisor in the area where the deviation occurred
is no longer required to notify the supervisor of the next processing step about the alarm. This information
is communicated via a warning in the MES. A worksheet used to gather data for the next processing step
cannot be generated until the MES alarm is acknowledged by a supervisor from the downstream
processing step. This ensures that the downstream supervisor is aware of the alarm and the information
does not get lost in the shuffle of email. In addition, the alarm remains in place until the material is ready
to be processed further. For example, if material has exceeded its TOR alarm limit for a given processing
step and then remains in a cold vault for six months before the next processing begins, the downstream
supervisor does not need to retain that information in a localized system.

The fact that data is no longer manually entered into documents means that a manual quality
check of the data does not need to occur before the product is released to the marketplace. The total TOR
for the lot is updated continuously throughout processing. The total TOR for the finished vaccine product
is calculated as soon as the material is delivered to the global warehouse. Supervisors from production,
quality, or release can monitor the TOR progress and TOR alarm warnings associated with a batch from
their computer, if they have access to the MES. This means personnel from quality or release no longer
have to find TOR documents in production or retention to access data. The same personnel are no longer
dependent on the availability of supervisors from other departments if they want instant access to TOR
data. Decisions that require immediate data checks will no longer have to wait for the required
information to be gathered. Having TOR data in a central repository also makes troubleshooting easier as
process engineers will be able to evaluate TOR time trends to evaluate changes in the process.
CHAPTER 6: RECOMMENDATIONS

The future-state IP-Maps in Chapter 5 are developed based on two major underlying assumptions:
1) the time out-of-refrigeration at ambient temperature is measured for individual containers or pallets of
material and 2) capturing time out-of-refrigeration data is an automatic process that occurs as soon as
material enters or leaves cold storage. These assumptions provide the basis for two important cold chain
MES implementation recommendations. First, a unit of measurement smaller than lot size must be
selected for tracking material data in the MES. Second, data capture technology for material entering or
leaving cold storage must be integrated with the MES.

6.1 Select Smaller Units of Measurement for the Cold Chain MES
Selecting a unit of measurement for product handled by the cold chain MES is a significant
strategic decision. The smaller the size of the unit, the more complex the management system will have to
be in order to interact with the data collection instruments. Tracking cold chain data associated with
pallets of material is less involved than tracking data associated with trays of material that make up pallets
or vials of material that make up trays. The unit of measurement decision for the cold chain MES is
constrained by the capabilities of the instruments on the processing floor and the business planning
software. If the business planning software is unable to communicate in terms of pallets of material, the
unit of measurement will be fixed at lots of material. If the instruments on the floor cannot distinguish
when a new tray of material has been loaded, the unit of measurement will be fixed at pallets of material.

In an ideal situation, the MES would be able to track individual vials of material from its vaccine
bulk origin to its finished product container end. A more realistic recommendation is to manage material
in the cold chain MES at the container/pallet level. This level eliminates the cost and complication of
managing smaller units, while still providing significant benefits to the V&D division.

6.2 Implications of Selecting Smaller Units of Measurement for

the Cold Chain MES
Vaccine material lots are separated into smaller subunits, such as trays of vials or pallets of trays,
for easier handling and transportation throughout manufacturing. The time out-of-refrigeration calculated
for the entire lot of vaccine during a given processing step is assigned to each of the subunits. For
example, during packaging a pallet of material is removed from cold storage and setup for processing.
When that first pallet of material is removed from the cold storage warehouse, the first piece of data for
calculating time out-of-refrigeration is generated. Temporary packaging is removed from the pallet so that

58
the vials can be staged, packaged, and prepared for shipping before being placed onto a new pallet. The
first pallet out of the processing unit for a given processing step is then returned to the cold storage
warehouse.

During staging, packaging, or preparation for shipping, another pallet of vaccine from the lot is
removed from cold storage and staged for processing. The process is repeated until a predetermined
number of pallets of material from the lot have completed packaging. Once the last pallet from this lot has
been returned to the cold storage warehouse, the last piece of data for calculating time out-of-refrigeration
for packaging is generated. These two pieces of data are then used to calculate the time out-of-
refrigeration for the entire lot during this manufacturing process. Individual pallets of material are only
exposed to ambient temperature for a fraction of the time that the entire lot is exposed to ambient
temperature; however, each pallet of the lot is assigned the time out-of-refrigeration of the entire lot.

If each pallet of the lot were assigned its actual time out-of-refrigeration, flexibility would
increase throughout the process. Because each pallet is assigned the full time out-of-refrigeration for the
lot as a conservative measure, there is an increased risk of exceeding the time out-of-refrigeration limit
for that processing step. This false positive result causes a time and resource consuming investigation to
be initiated. Highly trained personnel interview technicians and supervisors, review batch records, and
consult with process specialists during the investigation. The investigation is reviewed by quality and
release groups to ensure the product impact decisions are defendable to inquiring regulatory agencies.
Personnel responsible for completing these investigations are also responsible for proactively addressing
processing issues and executing process improvement projects. When a time out-of-refrigeration
deviation occurs during processing, the investigation often unnecessarily diverts resources that could be
utilized for process improvement projects. Because closed investigations are required for release of the
lot, investigations take precedence over process improvement projects that could have significant cost
savings for the organization.

Production supervisors spend time communicating the TOR deviation to other departments and
planning must revise schedules to accommodate tighter time out-of-refrigeration allowances for
downstream processes. In the extreme situation in which a time out-of-refrigeration limit is exceeded for
an entire lot, the material must be held in quarantine until the impact to the product from the deviation is
resolved. Material implicated in an investigation must be quarantined in segregated sections of the
warehouse to prevent accidental shipping. According to internal procedures, intermediate material held
under quarantine cannot be processed further until the investigation is completed and the material
removed from quarantine. The finished material remains in inventory occupying valuable cold storage
space during the investigation. Time out-of-refrigeration alarm limit deviations can cause havoc in the
downstream schedule as material designated for processing needs to be replaced with other lots of
material that have not yet reached the appropriate phase of manufacturing. Upstream lots are then pulled
in the schedule requiring costly overtime and schedule adjustments.

In order to remove a lot of finished material from quarantine, it must be determined that the
product has retained its chemical and biological properties. In the case where the TOR is exceeded for
the entire lot and there is no stability data to support the time and temperature conditions that the lot was
exposed to, a new stability study must be performed to ensure the safety and viability of the product. A
real-time stability study to support an investigation is a lengthy, costly endeavor that might require
reprioritization of other important stability programs. The worst-case scenario is that, in the end, the
material is discarded because the total time out-of-refrigeration for the lot cannot be justified by
additional stability studies. The most recently published Adult Vaccine Price List has the Novartis vaccine
Fluvirin@ private sector cost as $12.10 per dose (CDC 2011). Assuming a batch size of 50,000 doses, the
company loses $605,000 in revenue for each discarded lot, not including the opportunity cost for lost
production time. In addition, this material is not available for patients, which could have a negative
impact on public health.

In addition to the resources consumed by the investigation, the warehouse loses a great deal of
capacity flexibility. If pallets of material were assigned time out-of-refrigeration based on their actual
time of exposure to ambient temperature instead of conservatively being assigned the TOR of the entire
lot, material could be removed from refrigerated storage to create space for more critical material.
Assume a lot of Meningitis vaccine accumulates a time out-of-refrigeration of 56 hours over the four
major processing steps. The TOR limit for Meningitis vaccine is 60 hours. The actual time out-of-
refrigeration for each pallet of Meningitis vaccine is between 12 and 18 hours. The Meningitis lot is
stored in a cold temperature warehouse that is near capacity. Now assume a lot of Influenza vaccine has
been manufactured and needs to be stored on-site for a short time before being shipped to the customer. If
the Meningitis pallets of material had been assigned their actual TOR, they could be removed from cold
storage for at least 42 hours before being returned to cold storage based on the TOR limit. However, since
the TOR calculation for the lot only allows the material to be removed from cold storage for 4 hours,
alternate accommodations need to be found for the lot of Influenza vaccine.

The lot of Influenza vaccine can be shipped to another V&D warehouse for cold storage at great
expense. Alternatively, the lot of Influenza vaccine can be stored off-site, with the tradeoff being that the
quality of this valuable material becomes dependent on the temperature controls of another company.
Another option is that additional cold storage space can be constructed on-site for the seasonal Influenza
material. Cold storage space is extremely expensive to build and maintain. Accurate TOR information for
each subunit of material within a lot would allow capacity planners to more accurately forecast their cold
storage space needs.

6.3 Ensure Cold Chain Data is Captured Automatically

Capturing the time that vaccine material is removed from and returned to cold storage is the
critical set of data points for calculating time out-of-refrigeration. A strategic improvement to the current
paper-based data collection system would be an automated data collection system. In the same manner
that the MES integrates with process instruments to capture critical process data such as weights,
temperatures, and pressures, the MES can integrate with instruments that record time.

My recommendation would be for each container or pallet of material to be associated with a

unique radio frequency identification (RFID) tag that is recognized by the business planning software and
the MES. RFID tag readers would be placed at the entrance of every cold storage location. Each time
vaccine material with an RFID tag passed through a cold storage location, the RFID tags would generate a
data point. The incoming data supplied by the RFID tag readers would be associated with vaccine product
through MES worksheets. The summation of data from these worksheets would allow the MES to
maintain an updated time out-of-refrigeration for all vaccine material.

The MES is already responsible for selecting which containers or pallets of material will be used
for the next processing step. These associations will allow TOR data from previous processes to be
included in the current material TOR calculation. If pallets of material are blended in manufacturing to
form the next material, logic can be written in the MES to assign the new material the worst-case time
out-of-refrigeration from the starting pallets of material. If a lot of material is split into multiple upstream
lots, the MES will understand these associations and will be able to calculate the TOR for the new
material based on the data from the input material.

An alternative solution to my recommendation would be to have bar codes on each container or

pallet of material instead of RFID tags. RFID tags are beneficial because the data is automatically
recorded by the RFID tag reader. Bar codes must be scanned to generate data. While the bar code
generated data would automatically be linked with the appropriate material in the MES, this solution
would require additional manpower and resources. Technicians responsible for collecting the TOR data
would have to be trained on how to scan the bar codes each time material is removed from or added to a
cold storage unit. In addition, the technician would have to scan the bar code in a timely manner to ensure
the integrity of the data. Automated data collection for the cold chain MES has a number of other
efficiency benefits for the V&D division.

6.4 Implications of Ensuring Automatic Capture of Cold Chain

Data
With automated collection of time out-of-refrigeration data, analysis of the data could be
performed and metrics established. The time out-of-refrigeration alarm limits for each of the four major
processing steps are determined arbitrarily based on historical processing times. Additionally, each of the
time out-of-refrigeration alarm limits has some buffer time incorporated in the limit for unanticipated
process interruptions. The anticipated time that material will be exposed to ambient temperature is less
than the alarm limit for the associated processing step. If the time out-of-refrigeration alarm limit is
exceed upstream, this often does not impact the finished product that is shipped to the customer because
downstream processing steps can often be executed in a shorter period of time. However, a process
deviation investigation is still initiated.

While it is possible to expose product to ambient temperature for shorter periods of time during
downstream steps, this activity also requires additional management and resources. Lots that need a short
time out-of-refrigeration during a given process step require additional operators to ensure the tighter time
out-of-refrigeration limit is met. The additional operators are often required to be compensated at
overtime pay. The planner also manages the extra stress of readjusting the processing schedule against
current product needs. This becomes exceedingly difficult during times of high production in the
processing calendar. Moving operations to a slot in the production schedule where it has a better chance
of meeting the shorter time out-of-refrigeration specification can lead to sacrifices in meeting market
demand for other products.

The time out-of-refrigeration alarms for each processing step do serve as a guide for how long
each processing step should last. Automated data collection would allow for accurate time out-of-
refrigeration alarm limits to be generated for each processing step. This information could also be used as
an effective metric for process evaluation and to proactively address problems. Collecting and analyzing
this data could implicate a particular department in the process sequence that is routinely impacting the
process schedule by exceeding their allotted TOR. Sharing this data with all departments could make
members of the production team that are not meeting expectations appreciate the direct impact they are
having on their colleagues. Sharing this data could also create competition that might incentivize
departments to perform more efficiently.
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