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The ProductQuality ResearchInstitute (PQRI)is
collaborativeeffort
betweenthepharmaceuticalindustry,regulatoryagencies, andacademia.
Oneof the purposesof PQRI is topromotediscussion oncurrent topics
ofinterest in thepharmaceuticalfield. To thatend, PQRIcommissioned
aworking group todevelop a WhitePaper thatdiscusses theconcept
ofprocessrobustness andhow it applies todevelopment,scale up,
andmanufacture ofpharmaceuticalproducts.
Process Robustness – A PQRI WhitePaper
by PQRI Workgroup MembersMichael Glodek, Merck & Co.;
Stephen Liebowitz, Bristol-Myers Squibb; Randal McCarthy,Schering
Plough; Grace McNally, FDA; Cynthia Oksanen, Pfizer; Thomas
Schultz, Johnson &Johnson; Mani Sundararajan, AstraZeneca; Rod
Vorkapich, Bayer Healthcare; KimberlyVukovinsky; Pfizer, Chris
Watts, FDA; and George Millili, Johnson & Johnson - Mentor
IntroductionObjective
The ability of a manufacturing process totolerate the expected
variability of rawmaterials, operating conditions, pro-cess
equipment, environmental condi-tions, and human factors is referred
to as ro-bustness.
The objective of this paper is to unify under-standing of the
current concepts of processrobustness and how they apply to
pharmaceu-tical manufacturing. The paper also
providesrecommendations on development and main-tenance of a robust
process. The concepts pre-sented here are general in nature and
canapply to many manufacturing situations; how-ever, the focus of
the discussion is applicationof robustness principles to
non-sterile soliddosage form manufacturing. The tools, casestudies,
and discussion presented in this papercenter around new product
development andcommercialization as, ideally, process robust-ness
activities start at the earliest stages ofprocess design and
continue throughout thelife of the product. It is also recognized
thatconcepts of robustness can be applied retro-spectively to
established products in order toenhance process understanding.
BackgroundThere is a heightened emphasis on greaterprocess
understanding in the pharmaceuticalindustry. There is great
incentive from amanufacturer’s point of view to develop
robustprocesses. Well understood, robust processessuggest greater
process certainty in terms ofyields, cycle times, and level of
discards. Lowerfinal product inventories may be carried if
themanufacturing process is reliable.
There is a growing expectation from globalregulatory agencies
that firms demonstrate acomprehensive understanding of their
processesand controls. The finalized FDA report
entitled“Pharmaceutical cGMPs for the 21st Century -A Risk-Based
Approach” clearly expresses theexpectation that firms strive for
“the imple-mentation of robust manufacturing processesthat reliably
produce pharmaceuticals of highquality and that accommodate process
changeto support continuous process improvement.”As evidenced by
recent draft guidelines, theother members of the ICH tripartite
have alsoadopted the philosophy embraced by this “Risk-Based
Approach.” The eventual implementa-tion of recommendations
contained in ICH Q8and Q9 should establish the linkage
between“knowledge” and “associated risk.” An underly-
ing principle of ICH Q8 is thatan assessment of process
ro-bustness can be useful in riskassessment and risk reduc-tion.
Furthermore, such an as-sessment of process robustnesscan
potentially be used to sup-port future manufacturing andprocess
optimization, espe-cially in conjunction with theuse of structured
risk man-agement tools outlined in thedraft ICH Q9 guidance.
The
Figure1. ProvenAcceptable Range (PAR).
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establishment of robust processes serves the best interests
ofthe patients, global regulatory agencies, and firms. It
isanticipated that such processes will consistently produce safeand
efficacious products in a cost effective manner. While notin the
scope of this document, it is also anticipated thatregulatory
agencies will adjust their oversight requirementsfor processes that
are demonstrated to be robust, as suchprocesses are anticipated to
present low risk for productquality and performance.
There is more to a robust process than having a dosageform pass
final specifications. Robustness cannot be testedinto a product;
rather, it must be incorporated into the designand development of
the product. Performance of the productand process must be
monitored throughout scale up, intro-duction, and routine
manufacturing to ensure robustness ismaintained and to make
adjustments to the process andassociated controls if necessary.
Process understanding - howprocess inputs affect key product
attributes - is the key todeveloping and operating a robust
process.
This paper presents key concepts associated with
processrobustness, defines common terms, details a
methodicalapproach to robust process development, and discusses
toolsand metrics that can be used during development or forongoing
process monitoring. Where appropriate, case studiesare used to
demonstrate concepts. The tools, approaches, andtechniques
discussed are commonly understood concepts andare routinely used in
other industries. Many pharmaceuticaldevelopment and manufacturing
programs are employingsome or all of the techniques. The intent is
to organize theapproaches and show how, when used together, they
can leadto greater process understanding and control.
Principles of Process RobustnessDefining RobustnessThe ability
of a process to demonstrate acceptable quality andperformance while
tolerating variability in inputs is referredto as robustness.
Robustness is a function of both formulationand process design.
Formulation design variables include thequalitative and
quantitative composition of raw materials,both API and excipients.
Process design variables include theprocess selected, the
manufacturing sequence or steps, theequipment settings, such as
speeds and feed rates, andenvironmental conditions. In this
discussion, all processinputs will be referred to as
parameters.
Performance and variability are factors impacting robust-ness
and may be managed through process design and prod-uct composition.
Elements of product composition for consid-eration include the
choice of API form, since some API formsare more robust than
others, and the choice of the excipients,e.g., the grades and
concentrations.
Process performance and variability may be managedthrough the
choice of manufacturing technology. Settingappropriate parameter
ranges for a robust process requiresconsideration of the
manufacturing technology selected. Spe-cial considerations are
needed for situations/processes wherethe appropriate setting of one
parameter depends on thesetting of another. Well designed processes
reduce the poten-
tial for human mistakes, thereby contributing to
increasedrobustness.
A typical pharmaceutical manufacturing process is com-prised of
a series of unit operations. A unit operation is adiscrete activity
e.g., blending, granulation, milling, or com-pression. Parameters
for a unit operation include: machin-ery, methods, people, material
(API, excipients, materialused for processing), measurement
systems, and environ-mental conditions. The outputs of a unit
operation are de-fined as attributes, e.g., particle size
distribution or tablethardness.
During product and process development both the inputsand
outputs of the process are studied. The purpose of thesestudies is
to determine the critical parameters and attributesfor the process,
the tolerances for those parameters, and howbest to control them.
Various experimental and analyticaltechniques may be used for
process characterization. Thegoal of this development phase is to
have a good understand-ing of the process and the relationships of
the parameters tothe attributes. The body of knowledge available
for a specificproduct and process, including critical quality
attributes andprocess parameters, process capability, manufacturing
andprocess control technologies and the quality systems
infra-structure is referred to as the Manufacturing Science
under-lying a product and process.
Critical Quality Attributes (CQAs)There are some measured
attributes that are deemed criticalto ensure the quality
requirements of either an intermediateor final product. The
identified attributes are termed CriticalQuality Attributes
(CQAs).
CQAs are quantifiable properties of an intermediate orfinal
product that are considered critical for establishing theintended
purity, efficacy, and safety of the product. That is,the attribute
must be within a predetermined range to ensurefinal product
quality. There may be other non-quality specificattributes that may
be identified, e.g., business related at-tributes, however, and
they are outside the scope of CQAs.
Critical Process Parameter (CPPs)During development, process
characterization studies iden-tify the Critical Process Parameters
(CPPs). A Critical Pro-cess Parameter is a process input that, when
varied beyonda limited range, has a direct and significant
influence on aCritical Quality Attribute (CQA). Failure to stay
within thedefined range of the CPP leads to a high likelihood of
failingto conform to a CQA.
It is also important to distinguish between parametersthat
affect critical quality attributes and parameters thataffect
efficiency, yield, or worker safety or other businessobjectives.
Parameters influencing yield and worker safetyare not typically
considered CPPs unless they also impactproduct quality.
Most processes are required to report an overall yield frombulk
to semi-finished or finished product. A low yield of anormally
higher yielding process should receive additionalscrutiny since the
root cause for the low yield may be indica-
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tive of a manufacturing issue or may be resultant from a lackof
process control. In the event a process produces a lowerthan
expected yield, it becomes relevant to demonstratethorough process
understanding and control why the lowyield occurred.
Development of comprehensive manufacturing science forthe
product will produce the process understanding neces-sary to define
the relationship between a CPP and CQA.Often the relationship is
not directly linked within the sameunit operation or even the next
operation. It is also importantto have an understanding of the
impact of raw materials,manufacturing equipment control, and degree
of automationor prescriptive procedure necessary to assure adequate
con-trol. The goal of a well characterized product
developmenteffort is to transfer a robust process which can be
demon-strated, with a high level of assurance, to consistently
pro-duce product meeting pre-determined quality criteria
whenoperated within the defined boundaries. A well
characterizedprocess and a thorough understanding of the
relationshipsbetween parameters and attributes will also assist in
deter-mining the impact of input parameter excursions on
productattributes. CPPs are intrinsic to the process, and their
impacton quality attributes is mitigated by process controls
ormodifications to other parameters.
Normal Operating Range (NOR), ProvenAcceptable Range (PAR)During
the early stages of process development, parametertarget values and
tolerance limits are based on good scientificrationale and
experimental knowledge gained from the labo-ratory and pilot scale
studies. A parameter that shows astrong relationship to a critical
quality attribute becomes akey focal point for further study. In
developing the manufac-turing science, a body of experimental data
is obtained, andthe initially selected parameter tolerances are
confirmed oradjusted to reflect the data. This becomes the Proven
Accept-able Range (PAR) for the parameter, and within the PAR
anoperating range is set based on the typical or Normal Oper-ating
Range (NOR) for the given parameter. Tolerance rangesmay be
rationalized and adjusted as increased process under-standing is
gained.
Further study of parameters is a prelude to determiningthose
that are critical process parameters. If varying a pa-rameter
beyond a limited range has a detrimental effect on acritical
quality attribute, it is defined as a Critical ProcessParameter
(CPP). Final selection and characterization of thecritical process
parameters should be completed prior toexecuting the commercial
scale batches.
In subsequent product development the parameters andattributes
of the process are characterized to determine thecritical
parameters for the process, the limits for those pa-
rameters, and how best to control them. Controllable param-eters
may be parameters that are adjustable, e.g., dryingtime or
temperature. At other times it may be desirable to ‘fix’a parameter
by specifically setting one value and not testingaround the
variability. A cause and effect relationship may beestablished for
parameters and desired attributes. As anexample, the drying time
and temperature are parameters toa granulation process that affect
the moisture level, anattribute of the granulation.
In a robust process, critical process parameters have
beenidentified and characterized so the process can be
controlledwithin defined limits for those CPPs. The NOR of the
processis positioned within the PAR for each of the CPPs. The PARis
a function of the process and reflects the range over whicha
parameter can vary without impacting critical qualityattributes. A
process that operates consistently in a narrowNOR demonstrates low
process variability and good processcontrol. The ability to operate
in the NOR is a function of theprocess equipment, defined process
controls and processcapability. If the difference, delta, between
the NOR and PARis relatively large, the process is considered
robust withrespect to that parameter. Refer to Figure 1. Where the
deltabetween the NOR and PAR is relatively small, adequateprocess
control and justification should be provided to assurethe process
consistently operates within the PAR.
Characterizing and defining parameters may take a pathof first
defining the NOR and range midpoint where thecommercial product
would be expected to be consistentlymanufactured, followed by
defining the boundaries of thePAR. A process that operates in a NOR
that is close in limitsto the PAR may experience excursions beyond
the PAR. Inthis case, the process may lack robustness
In processes that contain CPPs, and where the betweenthe NOR and
PAR is relatively small, the concern of excur-sions beyond the PAR
drives the need for a greater under-standing of the tolerances of
the CPPs. This is warranted toassure adequate process control is
provided within the pro-cess.
Further characterization of parameters is achieved
asmanufacturing experience is gained and the state of robust-ness
of the process is assessed.
Variability: Sources and ControlTypical sources of variability
may include process equipmentcapabilities and calibration limits,
testing method variabil-ity, raw materials (e.g. API and excipient
variability betweenlots and vendors), human factors for
non-automated pro-
Figure 2. Case study example: process flow diagram for a
directcompression tablet.
Critical Quality Attributes
DissolutionAssay
Tablet uniformityBlend uniformity
Stability
Table A. Case study example: Table of Critical Quality
Attributes(CQAs) for a direct compression tablet. (Note that this
list is forthe case study example only and may not be all
inclusive).
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cesses, sampling variability, and environmental factors
withinthe plant facility. A myriad of systems are available
tomonitor and control many of the input factors listed.
Variability in operator technique may contribute to pro-cess
variability. In assessing robustness of a process it may
benecessary to evaluate operator-to-operator variability
andday-to-day variability of the same operators. Ideally,
pro-cesses are designed to minimize the effect of operator
vari-ability.
Setting Tolerance LimitsUpper and lower tolerances around a
midpoint within thePAR of a parameter should be established to
provide accept-able attributes. In setting the acceptable
tolerances of a CPPoften the point of failure does not get defined.
It is acknowl-edged that the acceptance limits set for a CPP may be
self-limited by the initially selected design space. In this case,
themanufacturing science knowledge base may be limited; how-ever,
within the tolerance limits selected, conformance to thedesired
quality attribute limits will be achieved and themanufacturing
science knowledge is sufficient.
It is not necessary to take a process to the edge of failureto
determine the upper and lower limits of a defined process.The
defined limits, however, should be practical and selectedto
accommodate the expected variability of parameters, whileconforming
to the quality attribute acceptance criteria.
Development of a Robust ProcessA systematic team-based approach
to development is one wayto gain process understanding and to
ensure that a robust
process is developed. However, there is presently no guidanceon
how to develop a robust process. The purpose of this sectionis to
define a systematic approach to developing a robustprocess and to
determine which parameters are CPPs. Thissection will also present
a case study to give practical ex-amples of tools that can be used
in the development of arobust process.
It is important to realize that this is only one way thatprocess
robustness can be achieved. There are other methodsthat are equally
valid for development of a robust process.Note that this process
can be applied interactively through-out the product lifecycle.
Steps for Developing a Robust ProcessSix steps are described for
the development of a robustprocess:
1. Form the team.2. Define the process (process flow diagram,
parameters,
attributes).3. Prioritize experiments.4. Analyze measurement
capability.5. Identify functional relationships.6. Confirm critical
quality attributes and critical process
parameters.
It is important to note that documentation of results is
acritical part of this process, and appropriate records
shouldcapture all findings of the development process.
Step 1: Form the TeamDevelopment of a robust process should
involve a team oftechnical experts from R&D, technology
transfer, manufac-turing, statistical sciences, and other
appropriate disciplines.The scientists and engineers most
knowledgeable about theproduct, the production process, the
analytical methodology,and the statistical tools should form and/or
lead the team.
Figure 3. General concept for Fishbone (Ishikawa) diagram.
Figure 4. Case study example: Fishbone diagram for a direct
compression tablet.
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This team approach to jointly develop the dosage form
elimi-nates the virtual walls between functions, improves
collabo-ration, and allows for early alignment around
technicaldecisions leading to a more robust product. This team
shouldbe formed as early as possible, before optimization and
scale-up has been initiated.
Step 2: Define the ProcessA typical process consists of a series
of unit operations. Beforethe team can proceed with development of
a robust processthey must agree on the unit operations they are
studying anddefine the process parameters and attributes.
Typically, flowcharts or process flow diagrams are used to define
the process.This flowchart should have sufficient detail to readily
under-
stand the primary function of each step. Figure 2 illustratesa
simple process flow diagram for the case study of a
directcompression tablet.
The next step in defining the process is to list all
possibleproduct attributes and agree on potential Critical
QualityAttributes (CQAs). This list of product attributes is
typicallygenerated by the team using expert knowledge,
scientificjudgment, and historical information on the product of
inter-est and similar products. It should be emphasized that
someattributes are evaluated or monitored for process
reproduc-ibility, i.e., process yield, and some are for final
productquality, i.e., the critical quality attributes. For
example,critical quality attributes could include (but are not
limitedto) assay, dissolution, degradants, uniformity, lack of
micro-
Blending• Blend Time• Rotation Rate• Agitator Speed• Room
Temperature, Humidity
Dry Granulation (Roller Compaction)• Roll Speed• Feed Screw
Speeds• Roll Force/Pressure• Roll Separation/Gap• Room Temperature,
Humidity
Milling• Impeller Speed• Feed Rate• Room Temperature,
Humidity
Fluid Bed Granulation• Granulation Fluid Mixing Time•
Granulation Fluid Mixing Speed• Granulating Fluid Amount•
Granulating Fluid Addition Rate• Granulating Fluid Temperature•
Spray Nozzle Air Volume• Bed Mixing Time• Supply Air Flow Rate,
Temperature, Dew Point• Product Bed Temperature• Exhaust Air
Temperature, Dew Point• Filter Shaking Intervals
Wet Granulation• Granulation Fluid Mixing Time• Granulation
Fluid Mixing Speed• Granulating Fluid Amount• Granulating Fluid
Addition Rate• Granulating Fluid Temperature• Spray Nozzle Air
Volume
• Dry Mixing Time• Wet Mixing Time• Impeller Speed• Chopper
Speed• Power Consumption
Cabinet Drying• Supply Air Temperature, Dew Point• Drying Time•
Final Moisture Content
Fluid Bed Drying• Supply Air Flow Rate, Temperature, Dew Point•
Product Bed Temperature• Exhaust Air Temperature, Dew Point• Filter
Shaking Intervals• Final Moisture Content
Compression• Tablet Weight• Turret Speed• Main Compression
Force• Pre-Compression Force• Feeder Speed• Upper Punch Entry• Room
Temperature, Humidity
Film Coating• Coating Suspension Mixing Time• Coating Suspension
Mixing Speed• Coating Suspension Amount• Coating Suspension Spray
Rate• Atomization Pressure• Pan Rotation Speed• Preheat Time•
Supply Air Flow Rate, Temperature, Dew Point• Product Bed
Temperature• Exhaust Air Temperature, Dew Point
Appendix APotential Critical Process Parameters for Common Solid
Dosage Form Unit Operations
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bial growth, and appearance. For the case study of a
directcompression tablet, Table A lists the potential critical
qualityattributes that the team generated.
The final step in defining the process is determiningprocess
parameters. Categories of parameters to consider arematerials,
methods, machine, people, measurement, andenvironment. In some
cases, the parameters may be some orall of the actual attributes of
a previous unit operation.Several methods or tools can be used to
capture the param-eters. One suggested tool is called a Fishbone or
Ishikawadiagram. The general concept is illustrated in Figure 3.
Referto Appendix A for a listing of common unit operations
andpossible critical process parameters for solid dosage
formmanufacturing. A fishbone diagram for the case study of adirect
compression tablet process is shown in Figure 4.
Step 3: Prioritize ExperimentsA thorough understanding of the
process and the processparameters is needed to develop a robust
process. However,it is not practical or necessary to study every
possible rela-tionship between process parameters and attributes.
It isrecommended that the team initially use a structured analy-sis
method such as a prioritization matrix to identify andprioritize
both process parameters and attributes for furtherstudy. Unlike
more statistically-oriented techniques, the useof a prioritization
matrix generally relies on the processknowledge and technical
expertise of the team membersinvolved in the process under study,
although data may beincluded from designed experiments.
A case study example of a prioritization matrix for a
directcompression tablet is shown in Table B. In the table is
placeda quantitative measure of the effect that a particular
param-eter is expected to have on a measured product
characteristic.This effect is typically expressed on a scale from 0
(noinfluence) to 10 (directly correlated). A ranking of
parametersof importance is calculated by considering the expected
im-pact of a parameter on attributes as well as the
relativeimportance of the attributes. In this case study, three
processparameters, API particle size, compression force, and
com-pressing speed are anticipated to be the most important
(based on the ranking totals at the bottom of the
table).Therefore, for this case study, it makes sense to
prioritizestudies that focus on the effects of these three
parameters.The parameters that were of lower importance may not
bestudied at all, or may be studied at a later date.
Step 4: Analyze Measurement CapabilityAll measurements are
subject to variability. Therefore, theanalysis of a process cannot
be meaningful unless the mea-suring instrument used to collect data
is both repeatable andreproducible. A Gage Repeatability and
Reproducibility study(R&R) or similar analysis should be
performed to assess thecapability of the measurement system for
both parametersand attributes. Measurement tools and techniques
should beof the appropriate precision over the range of interest
for eachparameter and attribute.
Step 5: Identify Functional RelationshipBetween Parameters and
AttributesThe next step is to identify the functional
relationshipsbetween parameters and attributes, and to gather
informa-tion on potential sources of variability. The functional
rela-tionships can be identified through many different
ways,including computational approaches, simulations (small
scaleunit ops) or experimental approaches. Where
experimentalapproaches are needed, one-factor-at-a time experiments
canbe used, but are least preferred. Design Of Experiments(DOE) is
the recommended approach because of the ability tofind and
quantitate interaction effects of different param-eters
Properly designed experiments can help maximize scien-tific
insights while minimizing resources because of thefollowing:
• The time spent planning experiments in advance canreduce the
need for additional experiments.
• Fewer studies are required.• Each study is more
comprehensive.• Multiple factors are varied simultaneously.
PROCESS PARAMETERS
API Pre- Feed ExcipientBlend Lube Particle Compression
Compression Compressing Frame Particle
Quality Attributes Time Time Size Force Force Speed Setting Size
Importance
Dissolution 1 7 9 1 9 1 3 1 10
Assay/ Potency 1 5 3 10
Uniformity 7 1 9 5 3 5 10
Appearance 1 3 3 3 5
Stability 1 3 7
Yield 3 3
Ranking Total 95 95 187 10 126 134 90 60
Percent 13 13 25 1 17 18 12 8
Table B. Case study example: Prioritization matrix for a direct
compression tablet (Note that this matrix is for the case study
example onlyand may not be all inclusive).
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Design of experiments can often be a two-stage process,involving
screening experiments to identify main factors toconsider as well
as response surface methodologies to refinethe understanding of
functional relationships between keyparameters and attributes. An
example of a statistical DOEfor the case study of a direct
compression tablet is shown inTable C.
Step 6: Confirm Critical Quality Attributes(CQAs) and Critical
Process Parameters (CPPs)After a sufficient amount of process
understanding is gained,it is possible to confirm the CQAs
previously identified (step2). In the case study for a direct
compression tablet, thecritical quality attributes were
dissolution, assay, tabletuniformity, and stability. As defined in
a previous section, aCPP is defined as a process input that has a
direct andsignificant influence on a CQA. CPPs are typically
identifiedusing the functional relationships from step 5. In the
casestudy for a direct compression tablet, tablet press speed
andcompression pressure were found to impact the CQA ofdissolution,
and were identified as CPPs. In Figure 5, it canbe seen that there
is an optimum compaction pressure toobtain the highest dissolution.
In Figure 6, it can be seen thatincreasing the tablet press speed
resulted in increasingvariability in dissolution.
These functional relationships can be used and variousoptimizing
strategies employed to identify optimal processset points or
operating regions for press speed and compac-tion pressure. Suppose
the product’s goal is to achieve anaverage dissolution greater than
80% with less than a 5%standard deviation on dissolution. One
summary sourceproviding information on a potential operating region
is anoverlay plot; see Figure 7 for the case study of a
directcompression tablet. This visual presents a predicted
(yellow)area of goodness where average dissolution is greater
than80% and simultaneously the standard deviation of dissolu-tion
is less than 5%. The area where either or both of theseconditions
fails to hold is colored grey; the actual experimen-tal design
points are shown as red dots on the plot.Technology TransferProcess
understanding is necessary for development of arobust process. The
systematic, step-wise approach describedabove may require several
iterations before enough process
understanding is achieved. This methodology will
enablescientists and engineers to gain process understanding to
setthe groundwork for a robust operation in production. Impor-tant
to the product technology transfer is a well-character-ized
formulation and process design. It is recognized thatparameters
identified during the research and developmentphase may need to be
adjusted at scale-up to the pivotal(biobatch) or commercial batch
size. Therefore, employingsimilar steps that are used in the
development of a robustprocess, scale-up activities will include
the challenging ofpreviously defined CPPs and CQAs and
identification andprocess optimization of newly identified process
parameters.These activities will require an understanding of:
• the qualitative and quantitative composition of the
prod-uct
• API, excipient specifications and functional attributes•
potential increased variability in the API as a result of
scale-up of the API manufacturing process• manufacturing process
and controls, operator experience,
and skill sets• Assessment of equipment, used at the development
stage
versus the identified commercial manufacturing equip-ment, to
identify batch sizes and operating parameters.This equipment
assessment should also include equip-ment controls and
tolerances.
After CQAs and CPPs have been defined, the team shouldgenerate a
plan for controlling CPPs. This may involve, but isnot limited to
establishment of process operating limits, useof automation,
procedural controls and specialized operatortraining and
qualification. In addition, it is critical that theknowledge
transfer is well documented for the developmentand technology
transfer phases through to the commercialscale.
Figure 5. Case study example: DOE results showing effect
ofcompaction pressure on dissolution.
Run Compression. Press Speed Dissolution Disso SDOrder Pressure
(1000 tab/h) (Average %
(megaPascals) dissolved at 30 min)
1 350 160 83.12 2.14
2 150 160 81.54 2.40
3 250 280 96.05 3.73
4 150 260 80.38 6.18
5 390 210 69.32 6.08
6 250 140 94.81 1.14
7 250 210 96.27 3.59
8 250 210 94.27 6.37
9 110 210 70.76 4.03
10 350 260 83.71 7.10
Table C. Case study example: DOE results for a direct
compressiontablet study. In this example, the effect of compression
pressureand press speed on dissolution were studied. The results,
plotted inFigures 5 and 6 showed that compression pressure
affectedaverage dissolution, while tablet press speed affected
dissolutionvariability.
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As presented in the manufacturing section, with
moremanufacturing history and data over time, assessment
ofrobustness can be ascertained.
Process Robustness in ManufacturingThe Research and Development
(R&D) phase is character-ized by execution of a development
plan consisting of anumber of discrete experiments that are
designed to developa formulation, establish the proper
manufacturing process,and provide process and formulation
understanding aroundthe key relationships between parameters and
attributes.When the product is transitioned to Manufacturing, it
willmost likely encounter a much wider range of variation on
theparameters than seen in development. For example, at-tribute
variability may increase due to a wider range inincoming raw
material parameters that cannot feasibly bestudied in R&D. It
is upon transfer to Manufacturing thatassessment of the true
process capability and robustness aswell as any process improvement
or remediation will begin.
Manufacturing yields a large amount of empirical
processperformance data that may be used for a variety of
purposes.It should be periodically analyzed to assess process
capabilityand robustness and to prioritize improvement efforts;
thedata should be reviewed during the improvement effort toidentify
correlative relationships. Feedback to R&D mayoccur during
these activities to further build quality into thedesign process.
Although Manufacturing may benefit from alarger amount of empirical
data, the ability to perform plannedexperimentation is not trivial.
There are other techniquesthat have been successfully utilized to
further process under-standing and variability reduction. This
section discussestechniques that are applicable to analyzing data
to determinethe state of process robustness and ensure the
continuationof this state over time.
Monitoring the State of RobustnessAs R&D has established the
desired operating range ofparameters and attributes, Manufacturing
should monitorboth the parameters and attributes over time and
review theinformation at a pre-determined frequency, with
emphasison critical or key parameters.
The state of robustness may be monitored through
usingStatistical Process Control (SPC) charts combined with
capa-bility index calculations. SPC tools such as control charts
canbe used to ascertain the process’ stability, provide warningsof
any potential problems, and to assess the state of
control.Capability indices assess the product or process ability
tomeet specifications. To evaluate the true state of
robustness,information on process parameters and attributes should
becollected as per a pre-determined SPC sampling plan. Pro-cess
control charts (trend chart, run chart) are constructedand
capability indices calculated.
• Run Chart/Trend Chart: A run chart or trend chart is anx-y
plot that displays the data values (y) against the orderin which
they occurred (x). These plots are used to helpvisualize trends and
shifts in a process or a change invariation over time.
• Control Charts: Similar to a run chart, a control chart is
aplot of a process parameter or quality attribute over
time.Overlaid on the plot is information about the processaverage
and expected variability (control limits). Statisti-cal
probabilities form the basis for control chart rules thathelp
identify odd process behavior. Identifying and remov-ing assignable
causes of variability to the extent that onlysmaller or common
sources of variability remain producesa process that can be
considered stable and predictableover time, or under statistical
control and producing con-sistent output.
Table D. Development of robustness at various stages in the
Product Life Cycle.
Process RobustnessThe ability of a manufacturing process to
tolerate the variability of raw materials, process equipment,
operating conditions, environmental conditions and human factorsis
referred to as robustness. Robustness is an attribute of both
process and product design.
R&D Scale-Up and TT Commercialization
Post-Commercialization
Establish basis for formulation, process, Generate detailed
characterization of Maintain ideal process state and After a
sufficient time of manufacture,and product design. process and
product being transferred. assess process robustness. the
commercial scale assessment of
robustness can be ascertained.
Understand relationship between Establish the ability to
manufacture Monitor and where necessary, Understand process
capability andcritical process parameters (CPP) and product
routinely and predictably to the actively control process. modify
process if necessary to improvecritical to quality product
attributes desired quality and cost, in compliance
robustness.(CQA). with appropriate regulations.
Determine a design space that Confirm relationship between CPP
Confirm relationship between CPPintegrates various unit operations
to and CQA. and CQA.achieve an output in the most robust,efficient
and cost effective manner.
Tools: Tools: Tools: Tools:Flowcharts, Ishikawa Diagram, FMEA,
Flowcharts, Ishikawa Diagram, FMEA, SPC, Trend Plots/Run Charts,
Gage APR, SPC, Trend Plots/Run Charts,QFD, KT, Gage R&R, DOE,
Regression QFD, KT, Gage R&R, DOE, Regression R&R, Process
Capability – Cpk, PAT FMEA, QFD, KT, Ishikawa Diagram,Analysis and
Other Statistical Methods, Analysis and Other Statistical Methods,
Flow Charts, Pareto, DOE, RegressionPAT OC Curves, Tolerance and
Confidence Analysis and Other Statistical Methods,
Intervals, PAT, Tolerance Analysis PAT
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• Process Capability: After it has been determined that aprocess
is in statistical control, i.e., all assignable sourcesof
variability have been removed; the expected processcapability can
be calculated. The capability number pro-vides an assessment as to
what extent the process iscapable of meeting specifications or
other requirements.Common capability indices include:
- Cp: This index relates the allowable process spread (theupper
specification limit minus the lower specificationlimit) to the
total estimated process spread, +/- 3s.Generally, Cp should be as
large as possible.
- Cpk: This index relates the relationships of centerednessand
spread of the process to the specification limits. Ifthe Cpk value
is significantly greater than 1, the pro-cess is judged capable of
meeting specifications. Largervalues of Cpk are better.
Much has been written about control charts and processcapability
indices; there are formulas and statistical methodsavailable for a
wide range of data types, distributions, andspecifications beyond
the most common charts and indices fornormally distributed,
centered data with symmetric specifi-cations. It should be noted
that the distribution of the dataunder study must be matched to the
appropriate control chartand capability index; data normality
should not be assumedin all cases.Data can be captured and
processed in a variety of differentways. Electronic manufacturing
process databases can facili-tate monitoring the state of process
robustness.
Process Specific Improvement or RemediationIt is Manufacturing’s
responsibility to work with the processwithin bounds defined by
development and registration toattain and maintain a process in an
ideal state. If a problemhas been identified either by a trend
within the operatingrange or a single point outside the operating
range then aninvestigation should occur. Tools for investigation
include:
• Flowcharts: A pictorial (graphical) representation of
theprocess flow that shows the process inputs, activities,
andoutputs in the order in which they occur. Flowcharts aidprocess
understanding.
• Ishikawa or Cause and Effect (Fishbone) Diagram: Thistool
helps organize and display the interrelationships ofcauses and
effects. It is a form of tree diagram on its sideand has the
appearance of a fishbone.
• QFD: Quality Function Deployment is a structured analy-sis
method generally used to translate customer require-ments into
appropriate technical requirements. It is usedto capture and share
process knowledge and may be usedto identify and prioritize both
process parameters (inputs)and characteristics (outputs).
• FMEA: Failure Modes and Effects Analysis provides astructured
approach to identify, estimate, prioritize, andevaluate risk with
the intention to prevent failures. His-torically this tool is used
in the design of a new product,process, or procedure; it can also
be used to limit the riskinvolved in changing a process.
• KT: Kepner-Tregoe has developed four rational
processes(situational, problem, decision, and opportunity) that
pro-vide systematic procedures for applying critical thinkingto
information, data, and experience; application of thistool aids the
team’s understanding and decision making.
• Pareto Chart: A graphical means of summarizing anddisplaying
data where the frequency of occurrence isplotted against the
category being counted or measured. Itis used to pictorially
separate the significant few causesfrom the many and identify those
areas that are of themost concern and should be addressed
first.
Figure 6. Case study example: DOE results showing effect ofpress
speed on dissolution variability. (% standard deviation).
Figure 7. Case study example: Overlay plot of DOE resultsshowing
effect of compaction pressure and press speed ondissolution. The
potential operating window is shown in yellow.
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If either the variability of the process is larger than
expectedor the process average is not as expected, historical
dataanalysis may be used to help provide root cause
candidates.Process improvement or remediation activities may need
tooccur using Statistical Experimental Design.
• DOE (Design of Experiments): Uses a statistically basedpattern
of experimental runs to study process parametersand determine their
effect on process attributes. Theresults of these experiments are
used to improve or opti-mize the process and may be used to predict
the process’sability to produce the product within the
specifications.
• Regression/correlation analysis/ANOVA: These are math-ematical
approaches to examine the strength of the rela-tionship between two
or more variables. These methodsand models are useful in
determining root cause, in speci-fication setting, and
optimization. When applied to his-torical data analysis, care
should be taken in concludingcausal relationships.
• r/t-tests/F-tests: Statistically significant relationships
aredetermined using these statistics; in regression the t-testis
used, correlation analysis employs r, and ANOVA relieson the
F-test.
• Scatter Diagrams: A visual display of data showing
theassociation between two variables. The scatter
diagramillustrates the strength of the correlation between
thevariables through the slope of a line. This correlation canpoint
to, but does not prove, a causal relationship.
Plant-wide Variability Reduction ActivitiesIn addition to the
targeted improvement or remediationactivities just discussed,
process variability may be reducedthrough plant-wide process
improvement initiatives aimedat general sources of variability.
Recent industry initiativesand programs targeted at variability and
cost reductions andefficiency and flow improvements include
6-sigma, lean manu-facturing, and even lean sigma.
General sources of process variability include machines,methods,
people, materials, measurement systems, and envi-ronment. Examples
of variability reduction/process improve-ment activities that
address the general sources of variabilityand will lead to improved
processes include: instrumentationcalibration and maintenance, gage
R&R studies, operatorskills assessment, general plant layout,
and clearly writtenwork instructions.
• Materials can be a significant source of process
variability.It is important that the material functionality and
specificphysiochemical specifications are well understood. If
someaspect of the material is critical, then is should be
con-trolled.
• Instrumentation and Machine Calibration and Mainte-nance:
Machine and measurement systems are two of theprocess components
whose variability can contribute ad-versely to the product. Planned
maintenance, repeatabil-ity, reproducibility, and accuracy checks
should be per-formed as per a systematic schedule. The schedule
fre-quency should be appropriate for maintaining calibration.In
addition, it is critical that the preventative mainte-nance program
addresses equipment parameters that areprocess critical, i.e.,
granulator impeller speeds, air flow influid-bed equipment, and
film coaters.
• Gage R&R Studies: It is difficult/impossible to place
aresponse in control if the measurement system is notcapable. The
gage or measurement system R&R experi-mental design study
provides information about the re-peatability (inherent equipment
variation) and reproduc-ibility (operator to operator variation) of
the measurementsystem’s actual vs. required performance. More
generally,a measurement system analysis can be used to study
bias,linearity, and stability of a system.
• Human Factors: This contribution to variability is
bestminimized through education and training. The operatorskills
assessment provides a tool to track required skillsvs. personnel
capability. Variability in how a task isperformed can be reduced if
the work instructions are clearand concise. These instructions
along with the generalprocess flow should be periodically reviewed
and dis-cussed. Systematically error proofing is also a way
toreduce the influence of the human factor.
• Plant Layout: Along with other environmental factors
oftemperature, pressure, and humidity, etc., the
generalcleanliness, orderliness, and layout of an area provides
anindirect effect on the variation of a product. Environmen-tal
plans should be developed and maintained.
ConclusionCreating a system that facilitates increased process
under-standing and leads to process robustness benefits the
manu-facturer through quality improvements and cost reduction.Table
D summarizes the robustness roles by product life cyclealong with
useful tools for each stage. This system for robust-ness begins in
R&D at the design phase of the formulationand manufacturing
processes; emphasis on building qualityinto the product at this
stage is the most cost effectivestrategy. R&D quantifies
relationships between the inputsand outputs; the processes are
established to produce the bestpredicted output with the targeted
amount of variability.
Information about the process settings and key relation-ships
are communicated to Manufacturing. Upon transfer,Manufacturing
begins to verify R&D’s information on processrobustness through
process monitoring and data analysis.Both general and process
specific improvement activitieshelp Manufacturing attain and
maintain its goals.
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GlossaryCritical Process Parameter (CPP) - A Critical
ProcessParameter is a process input that, when varied beyond
alimited range, has a direct and significant influence on aCritical
Quality Attribute.
Critical Quality Attribute (CQA) - A quantifiable prop-erty of
an intermediate or final product that is consideredcritical for
establishing the intended purity, efficacy, andsafety of the
product. That is, the property must be within apredetermined range
to ensure final product quality.
Design Space - The design space is the established range
ofprocess parameters that has been demonstrated to provideassurance
of quality. In some cases design space can also beapplicable to
formulation attributes.
Manufacturing Science - The body of knowledge availablefor a
specific product and process, including critical-to-qual-ity
product attributes and process parameters, process capa-bility,
manufacturing and process control technologies, andthe quality
systems infrastructure.
Normal Operating Range (NOR) - A defined range, withinthe Proven
Acceptable Range (PAR), specified in the manu-facturing
instructions as the target and range at which aprocess parameter
should be controlled, while producing unitoperation material or
final product meeting release criteriaand CQAs.
Process Analytical Technologies (PAT) - A system fordesigning,
analyzing, and controlling manufacturing throughtimely measurements
(i.e., during processing) of criticalquality and performance
attributes of raw and in-processmaterials and processes with the
goal of assuring finalproduct quality.
Proven Acceptable Range (PAR) - A characterized rangeat which a
process parameter may be operated within, whileproducing unit
operation material or final product meetingrelease criteria and
CQAs.
Quality - Degree to which a set of inherent properties of
aproduct, system or process fulfils requirements.
Quality System - Formalized system that documents thestructure,
responsibilities, and procedures required to achieveeffective
quality management.
Requirements - Needs or expectations that are stated,generally
implied, or obligatory by the patients or theirsurrogates (e.g.,
health care professionals, regulators, andlegislators).
Repeatability - The variability obtained with one gage
usedseveral times by one operator.
Reproducibility - The variability due to different
operatorsusing the same gage on the same part.
Robustness - The ability of a product/process to demon-strate
acceptable quality and performance while toleratingvariability in
inputs.
ReferencesExperimental Design1. Cox, D.R., (1992). Planning for
Experiments; John-Wiley
and Sons.2. Box, G.E.P., W.G. Hunter, and J.S. Hunter, (1978).
Statis-
tics for Experimenters: An Introduction to Design, Analysisand
Model Building. New York: John Wiley & Sons.
3. Montgomery, D. C., (2001), Design and Analysis of
Experi-ments, New York: John Wiley & Sons.
4. Box, G.E.P., and N.R. Draper (1969). Evolutionary Opera-tion:
A Statistical Method for Process Improvement. NewYork: John-Wiley
& Sons.
5. Myers, R.H., and D.C. Montgomery (2002). Response Sur-face
Methodology: Process and Product Optimization UsingDesigned
Experiments, second edition. New York: JohnWiley & Sons.
6. Cornell, J., (2002). Experiments with Mixtures:
Designs,Models, and the Analysis of Mixture Data, third edition.New
York: John Wiley and Sons.
7. Taguchi, G., Y. Wu, A. Wu, (2000). Taguchi Methods forRobust
Design, American Society of Mechanical Engineers.
8. Ross, P.J., (1996), Taguchi Techniques for Quality
Engi-neering, The McGraw-Hill Companies, Inc.
Quality Control9. Montgomery, D.C., (2001). Introduction to
Statistical Qual-
ity Control, fourth edition. New York: John Wiley & Sons.10.
Juran, J.M., and A.B. Godfrey, (1999). Juran’s Quality
Handbook, fifth edition. McGraw-Hill.11. Duncan, A.J., (1974).
Quality Control and Industrial Sta-
tistics, Richard D. Irwin, Inc.12. Wheeler, D. J., (1999).
Beyond Capability Confusion: The
Average Cost-of-Use, SPC Press.13. Kepner, C.H., and B.B.
Tregoe, (1997). The New Rational
Manager, Princeton Research Press.
Measurement Systems Analysis/Gage R&R14. Automotive Industry
Action Group (2003), MSA – 3: Mea-
surement Systems Analysis.
Other Statistical Topics15. Odeh, R.E., and D.B. Owen, (1980)
Tables for Normal
Tolerance Limits, Sampling Plans, and Screening, NewYork: M.
Dekker.
16. DeMuth, J.E., (1992) Basic Statistics and
PharmaceuticalStatistical Applications, second edition. New York:
John-Wiley & Sons.
17. Hahn, G.J., and W.Q. Meeker, (1991) Statistical IntervalsA
Guide for Practitioners, New York: John Wiley & Sons.
18. Snedecor, G.W., and W.G. Cochran, (1980) Statistical
Meth-ods, The Iowa State University Press.
Quality Function Deployment19. Madu, Christian N., (2000) House
of Quality (QFD) In a
Minute, Chi Publishers.
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Who has notheard aboutavian flu? Athreat ofpandemicinfluenza
cameon the world’sradar screenwith theemergence ofthe H5N1influenza
strain.In this article,we will talkabout what wehave learnedfrom
previouspandemics; howto mitigate fearand uncertainty;and some
keyparts of astrategicbusinessmanagementplan forpandemics.
Avian Flu – Is My Company Prepared?
by Wendy Haines and Martin Rock
Who has not heard about avian flu?Avian flu articles have
appeared inrecent HR magazines, the HarvardBusiness Review, CFO
Journal, nu-merous news briefs have been posted on theCenters for
Disease Control and Prevention(CDC) and World Health Organization
(WHO)Websites, plus this issue also has appeared onthe national
news. The Kubu Simbelang vil-lage of North Sumatra, Indonesia got
the world’sattention through mainstream media when asingle extended
family contracted the H5N1strain of avian influenza and this
resulted inseven fatalities. According to the Ministry ofHealth in
Indonesia, there have been 54 con-firmed cases of H5N1 avian
influenza and 42have been fatal (as of July 20, 2006).1 TheH5N1
cases in Indonesia have gotten peoplespeculating – is this the
launch of a globalpandemic influenza?
What Have we Learned?George Santayana once said, “Those who
donot learn from history are doomed to repeatit.”2 What has been
learned from the pandemic
influenzas in this century? First, the most dev-astating flu
pandemic, the “Spanish Flu” (H1N1)killed more than 500,000 people
in the UnitedStates with estimates between 20 to 50 millionpeople
worldwide.3 According to epidemiolo-gists, one of the most
interesting findings, fromthe Spanish Flu was the shape of the
mortalitycurve.4 The mortality curve was a “W” shape,with three
peak age groups for mortality, whichmeans that the sensitive
populations were thevery young, adolescents, and the elderly.
Nor-mally, the mortality curve is a “U” shape. Thisshape means that
the mortality rate was high-est for both the young and the old.
Literaturesearches have revealed that epidemiologist donot have an
answer to explain the “W” shapedmortality curve of the 1918 Flu.
However, somesuggest that there was a possible pre-cursorwave of
flu that occurred 30 years prior to the1918 Flu. The pre-cursor flu
could have given alevel of immunity to the elderly, but this
immu-nity would not have been seen in young adultswho were not born
during this time.5 Similar tothe 1918 Flu, the sensitive
populations forH5N1 avian influenza has been the very young
Figure 1. Affected areaswith confirmed humancases of H5N1
avianinfluenza since 2003.(Source: WHO, 7 July2006).
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and adolescents.Second, there are more improved ways of
disseminating
information regarding a pandemic threat, but the rate inwhich a
pandemic influenza can spread is increased due to amore global
society. Consider this possible scenario. Fivepeople from different
countries board an airplane going to thesame three-day conference.
Two days later, Person A has asore throat, but thinks nothing of it
and continues attendingthe conference. Another two days go by,
Person A now has afever, sore throat, and muscle aches. Persons B
and C bothalso have a sore throat, while persons D and E have a
sorethroat, fever, chills, and muscle aches. All of these
peopleboard airplanes to return home to recuperate. What has
justhappened? Influenza has just been spread to five
differentcountries around the world by a single airplane
flight.
Third, a lot can be learned from countries that havesuccessfully
eliminated H5N1 from poultry. Hong Kong suf-fered multiple
outbreaks of H5N1 in 2003, but remarkably,they were H5N1 free in
2004. How did Hong Kong accomplishthis task? Hong Kong vaccinated
every chicken against H5N1and routinely tested chickens, pet birds,
and wild birds. Theyclosed live-poultry stalls so that they could
be disinfectedtwice a month and inspected markets and farms
continu-ously.6 Thailand also has spent a lot of time and effort to
getH5N1 under control. Similar to Hong Kong, Thailand testsducks
for H5N1 in order to help ensure only virus-free ducksroam free and
they have gotten the support of villagers toreport any chicken
die-offs. Thailand also has been able tohandsomely reimburse
farmers whose birds have been slaugh-tered.6
Therefore, sensitive population for H5N1 has been recog-nized,
means can be identified to reduce the spread of influ-enza by
globalization, and strategies can be learned fromcountries with
previous outbreaks of H5N1. The question iswhether this information
will be used effectively.
Hidden ThreatsThinking back to the airplane scenario, we have
alreadyilluminated one hidden threat – the delay between
infectionand the signs and symptoms of the flu. Flu symptoms
nor-mally appear two days following initial exposure; however,
people are most infectious 24 hours prior to symptoms.4
Similar to the airplane scenario described above, an em-ployee
can come to work one day, interact with their col-leagues and
co-workers, and show no signs or symptoms ofthe flu. The same
individual may be out sick the next day andwould have spread the
flu to the people he or she hadinteracted with during the previous
48 hours. Therefore,businesses will need to be pro-active with
educating theiremployees about personnel hygiene, keeping track of
expo-sures to sick people, and then advising employees to workfrom
home. Companies can obtain information from theCenters for Disease
Control and Prevention (CDC) Websiteregarding “good health habits”
to place on signs and postersaround the office.7 The other hidden
threat is asymptomaticfowl, which present no signs or symptoms of
disease. Dr.Robert Webster, a virologist for St. Jude Children’s
ResearchHospital calls the duck “the Trojan horse of this
outbreak.”7
Several publications indicate that ducks are able to be
in-fected with influenza, have no signs of disease, and are ableto
excrete large volumes of influenza virus in their feces.6, 8, 9
According to Dr. Webster, bodies of water with contaminatedfecal
matter infect many birds. This is “food for thought” tothink about
the next time you see someone feeding the birdsat a local pond or
lake. People will need to be mindful of ourhygiene habits and of
our extracurricular activities to helpprevent the spread of
influenza.
Fear and MotivationCertainly, most of us are familiar with
Maslow’s Pyramid ofNeeds. Abraham Maslow’s hierarchy of need theory
statesthat human beings will first strive to meet physiological
andsafety needs before they worry about belongings and es-teemed
needs.10 According to this theory, and based on actualexperience,
during a pandemic, people will be more concernedabout their family
and their own health and well being thanthey will about whether
their company will meet the businessquarter sales returns. Since
the overall mortality rate iscurrently over 50% for H5N1, fear will
be rampant and good,factual communications will be essential -
Figure 1, 2, andTable 1. Clear lines of communication will be
paramount tostopping rumors and for providing people with correct,
reli-able information to make intelligent, rational
decisions.Playing the “wait and see” game regarding a pandemic
flusimply does not make good business sense. Dale Carnegiesaid,
“When dealing with people, remember you are notdealing with
creatures of logic, but creatures of emotion.”11
Indeed, people’s behavior may be an important driver forthe
spread of a pandemic. Contemplate about how manypeople go to work
when they do not feel well? Now think abouthow many children go to
school and day care that are slightlyunder the weather and how
these events could have a “snow-balling effect” on the spread of
influenza. Businesses willneed to disseminate information, early
on, regarding keyfacts about influenza, what you can do to prevent
it, what arethe signs and symptoms, and the locations of
treatmentcenters. For example, companies may decide to provide
theirworkers with safe working environments and perhaps pro-
Figure 2. Pandemic Planning Update II. (Source: Dept. of
Healthand Human Services, 29 June 2006).
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vide living quarters for their employees and their families
inthe midst of a pandemic. In this situation, employees willneed a
site where they can have access to provisions andpossibly medical
resources. As part of the preparation pro-cess, businesses, local
authorities, and care providers need todetermine who they should be
teaming with to help thesurrounding community in the face of a
pandemic flu threat.
Knowledge and PlanningAs Louis Pasteur once said, “Chance favors
the preparedmind.”12 According to the WHO, companies should be
identi-fying pandemic teams, developing plans, and running
drillsnow to ensure preparedness.13 The WHO has developed atracking
system for the potential warning signs of pandemicflu - Table 2. As
you can see by the table, the world is currentlyin Phase 3 of the
Pandemic Alert Period - there is a novelinfluenza strain infecting
humans with no or very limitedhuman-to-human spread of the virus -
Table 2. As alsosuggested by a recent Harvard Business Review
article, nowis the time in which companies should develop risk
mitigationplans and run practice drills to elucidate any problem
areas.14
Let’s use Y2K as an analogy. From a business standpoint,
thesalary for a computer programmer well before Y2K wasdecent. The
cost-benefit for companies to hire and come upwith a possible
solution for Y2K was good if the company didnot wait until the last
minute. As we got closer and closer toY2K, the cost to hire a
computer programmer became astro-nomical due to the basic law of
supply and demand. Eventhough the worst fears about Y2K never
happened, we canstill learn something from this event. There is no
financial orbusiness benefit in waiting until the last minute to
prepare andyou cannot adequately prepare for this type of
contingencywhen it is already upon you. If a pandemic influenza
does notmaterialize this year, it could come another year or
someother type of epidemiological threat in the future could
havethe same effect. Experts have indicated that some type
ofpandemic occurs globally on a regular cycle and the next
pandemic is essentially inevitable.Remember, that forewarned is
forearmed. Companies can
“arm” themselves with the knowledge of pandemic influenzaand
guides that can be found on government Websites, suchas the WHO,
CDC, and PandemicFlu.gov. Organizationsneed to explain and put in
place appropriate policies regard-ing possible flexible leave
procedures, working ortelecommuting from home, or from remote
sites, flex-time,short-term disability policies, quarantine
scenarios, day carearrangements, sick leave, etc., prior to the
organization beingimmersed in a pandemic or other type of
epidemiologicalthreat. If every problem presents an opportunity,
then thethreat of a pandemic will allow companies to show how
muchthey care and value their employees.15 As mentioned
earlier,companies could provide safe living quarters for their
em-ployees and their families during a pandemic. Companiesalso
could have stocks of anti-viral medication available fortheir
critical staff.
Having a plan for possible pandemic influenza, if doneproperly
and kept up to date, will prepare a company or anorganization for
influenza or for any other epidemiologicalthreat that may occur in
the future. Businesses will need toidentify a risk management group
for pandemic influenzanow and add pandemic preparations to their
business conti-nuity plans. Nitin Nohara, the Richard P. Chapman
Profes-sor of Business Administration at Harvard Business
School,thinks of the threat of a pandemic as “survival of the
adap-tive.” She suggests that companies need to identify
decisionmakers during a pandemic that are able to apply “new waysof
problem solving in an unpredictable and
fast-changingenvironment.”16 As we know, people in the
pharmaceutical/biotech industries are highly innovative, they often
“thinkoutside the box,” and they can troubleshoot problems in
realtime. These skills will be required and in high demand
forbusiness continuity and for adaptation during a global
pan-demic. Another way to think about how to be prepared for
apandemic is to consider the analogy of marine expeditionary
Table A. Cumulative number of confirmed human cases of avian
influenza A /(H5N1). (Source: WHO, 20 July 2006).
Country 2003 2004 2005 2006 TOTAL
Cases Deaths Cases Deaths Cases Deaths Cases Deaths Cases
Deaths
Azerbaijan 0 0 0 0 0 0 8 5 8 5
Cambodia 0 0 0 0 4 4 2 2 6 6
China 0 0 0 0 8 5 11 7 19 12
Djibouti 0 0 0 0 0 0 1 0 1 0
Egypt 0 0 0 0 0 0 14 6 14 6
Indonesia 0 0 0 0 17 11 37 31 54 42
Iraq 0 0 0 0 0 0 2 2 2 2
Thailand 0 0 17 12 5 2 0 0 22 14
Turkey 0 0 0 0 0 0 12 4 12 4
Viet Nam 3 3 29 20 61 19 0 0 93 42
TOTAL 3 3 46 32 95 41 87 57 231 133
Total number of cases includes number of deaths. WHO reports
only laboratory-confirmed cases.
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forces, suggested by Nitin in the May 2006 Harvard
BusinessReview. The marines are highly effective in mission
criticalsituations because they not only practice as a team,
buteveryone on the team can lead the team.
In May 2006, US President George Bush released theNational
Strategy for Pandemic Influenza – ImplementationPlan. The
President’s plan outlines more than 300 criticalactions that may be
executed to address a pandemic influ-enza. There are three main
objectives to the plan: protectemployees; maintain essential
functions and services; andlines of communication. The plan also
advises companies andindividuals to access plans and check lists
that are availableon the CDC, WHO, and pandemic.gov Websites. An
Emer-gency Budget Request of $7.1 billion over the span of
severalyears has been submitted to Congress. In the 2006 fiscal
year,$3.8 billion was appropriated to help fund the
followingactivities: stock piling anti-viral medication; expand
domes-tic vaccine production; expand surveillance capabilities
do-mestically and internationally in humans and animals;
andinvestments in development of risk communication
strate-gies.
In addition to the President’s plan, the US Food and
DrugAdministration (FDA) developed a new team in response to
apossible pandemic influenza. In the fall of 2005, the FDAannounced
the formation of a Rapid Response Team (RRT).The RRT would help
ensure the following: an adequateamount of anti-viral medication is
stockpiled in the event ofa pandemic influenza; support the design
and implementa-
tion of clinical trials of novel treatments of avian flu;
andassist and evaluate studies using new technologies for vac-cine
development. Andrew von Eschenbach, MD, Acting FDACommissioner,
stated that the RRT would allow completereview of a drug in six to
eight weeks.17 The FDA is dedicatedto ensuring that the US has
enough medication to combatpandemic influenza.
Watson Wyatt Worldwide, a global human capital firm,conducted a
survey and found that 15% of companies havepandemic influenza plans
in place in the United States, 11%in Europe, 10% in Canada, and 9%
in Latin America.18
However, 32% of companies in Asia-Pacific had pandemicplans.
Another surprising finding was that one in five compa-nies are not
alarmed at all about pandemic influenza. Therewas an increase in
the percentage of companies consideringa pandemic plan: 52% in
Asia-Pacific, 48% in the UnitedStates, 47 % in Europe, 44 % in
Latin America, and 42 % inCanada.18 An important question to ask
is; why are themajority of companies just considering having a plan
and arenot devising a plan?
Collaboration will play an important role in strategicbusiness
planning for a pandemic flu event. A combination ofcross training,
an adaptive risk management group, andsupport by all employees and
contractors will aid in honingthe effectiveness of a plan.
Companies will need to do a “selfevaluation” and think about what
keeps them running andsuccessful, what are their supply chain
issues, who are theircritical staff, and how they can serve their
clients during a
Figure 3. Examples of some of the issues that companies will
need to consider when planning for a pandemic.
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pandemic - Figure 3. Does your company have sufficient back-up
supply relationships? Bear in mind that there is a differ-ence
between conception of a plan and the execution of a plan.Practice
drills will need to be run to illuminate holes orpossible problems
with your plan. Edward de Bono said, “Wemay need to solve problems
not by removing the cause, but bydesigning the way forward even if
the cause remains inplace.”19
The Business CaseHaving considered some of the salient
scientific and technicalfactors auguring for why organizations
should have a well-developed epidemiological plan, the next step is
a balancedand sober analysis of the strategic and business
managementissues. To play this game effectively, the organization
shouldhave both an “offense” strategy and a developing
capabilityfor advancing the business interests of the organization
andfor capturing the desired opportunities that arise; and
a“defense” that includes a preventative strategy for protectingthe
business continuity and cushioning the enterprise byproviding tools
and techniques for managing or coping withthe contingencies.
Among the advancement opportunities, the opportunity todevelop
sales through meeting anticipated and likely marketdemands for
products and services that would result from anepidemiological
pandemic, or even resulting from the fearand anticipation of such a
pandemic scenario, is certainly akey consideration. However, a
number of other benefits alsoshould be considered. For example, the
research develop-ments associated with response to the specter of
an epidemio-logical pandemic also may have significant spin-off
benefitsfor other market segments. In addition, the robust
opera-tional flexibility that can be achieved through an
investmentin well-designed epidemiological pandemic planning
pro-grams can pay significant benefits and dividends.
On the defensive or preventative side, there may be anequal
number of opportunities for strengthening supply chains,taking
advantage of contractual lead times, and identifyingkey resources
for optimal responses to various scenarios. Inother words, with
proper planning, the defensive or preven-tative strategies that
would pay big dividends during a majorcrisis scenario also may
enhance normal, day-to-day opera-tions. Similarly, the organization
may find greater successand viability during a minor crisis
scenario, provided thatthese objectives are considered and balanced
by the epide-miological team during planning and implementation
phases.
Spring Training and Practice DrillsThe case for the tangible
benefits of targeted and effectivetraining programs has been made
in many places, and afurther discussion of these benefits is not
needed here. How-ever, epidemiological planning presents a new
perspective onthis well-known phenomenon.
Training for epidemiological preparedness and businesscontinuity
provides an opportunity to develop and ingraingenuine strengths and
adaptability into the organizationalculture. For example, not only
does cross-functional training
Figure 4. The World Health Organization’s description of
thephases leading up to a pandemic.(Source: WHO).
help build teamwork and productivity, but also a new vitalitycan
result from overcoming epidemiological pandemic fears,and replacing
these with solid factual information, pervasivecommunications
channels, beneficial plans, and constructiveprocedures.
If the matter is properly managed, the time and resourcesspent
on epidemiological planning and preparation will notbe wasted if
the exact scenario or planned for event does notoccur. First, some
will believe that some type of epidemiologi-cal pandemic event is
simply inevitable and being preparedfor this type of scenario is
just good business. Indeed, manyexperts in the field already agree
with this assessment.Second, as alluded to above, a properly
designed epidemio-logical plan will pay benefits for a variety of
contingencyscenarios, and such planning can help with
maintainingsmooth business continuity despite minor “blips” or
“hiccups”over time. Indeed, one can argue that proper
epidemiologicalplanning and preparation will actually convert a
larger tsu-nami crisis into a more manageable “ripple” that is far
lessdisruptive.
Building your BenchWinning teams know that a strong bench wins
champion-ships. When a team has a strong bench, the bench players
willkeep the team in contention, even when the starters are outof
the game.
Tackling a problem such as epidemiological preparednesshas the
ability to build that bench strength. A global pan-demic will not
honor or abide by the organizational chart norstop at the doors of
the executive suite. The need for cross-functional training and for
backup leadership is as strong inthis situation as it is on the
battlefield or in professionalsports.
Business continuity will depend on flexibility and adap-tive
creativity. Yet building this flexible character also willcreate
additional benefits for the organization. When keypeople have a
strong, flexible understanding of the functionalrequirements of
their co-workers and supervisors, they willbecome more proactive
and productive; and fewer items “fallthrough the cracks.” This type
of thinking also can be appliedto the supply chain and to product
delivery. The result: Evennormal, day-to-day operations become more
effective and
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more adaptable to business fluctuations and to
unanticipatedcircumstances, honing that competitive edge.
Appealing to the CrowdSound preparation for an epidemiological
contingency alsocan appeal to customers and stakeholders of the
organiza-tion. Being prepared for appropriate contingent scenarios
isperceived as prudent business practice. Such planning willnot
only ensure a continuity of operations, but also will assureyour
customers and stakeholders that you are solidly “on topof your
game.”
Backup plans, work-around options, and provisions forstrength
and stability of operations will give your customersand your
stakeholders’ confidence in your organization. Thatconfidence
translates into sales, investor support, and advan-tageous business
alliances. Conversely, not being properlyprepared for the dreaded
contingent scenario, especially ifthe scenario actually occurs, can
undermine public confi-dence in your organization, and these
effects can be long-termor even irreversible. Being ready also
means being competi-tive, stable, and sustainable.
Timing is EverythingShould the pharmaceutical and bio-technical
industries beconcerned about the threat of a pandemic flu? Answer:
indus-try professionals should be aware of the issues and should
beprepared to respond appropriately to this threat.
Ask yourself whether your company or organization isfully and
adequately prepared for a pandemic flu or for other,equally
threatening epidemiological contingencies that mayoccur. As
indicated throughout this article, now is the time toidentify risk
management teams, to devise comprehensiveepidemiological pandemic
preparation plans, to train em-ployees, and to run practice drills
for purposes of assuringbusiness continuity. We have made many
advances as asociety since the last major pandemic, and our
knowledge andthe availability of new technologies can be used to
ouradvantage. On the other hand, modern technology, includingglobal
trade and intercontinental air travel, can rapidlyspread diseases
and illnesses around the world with noregard for national
boundaries. Essentially, this is the flipside of the burgeoning
globalization mega-trend of recentdecades.
In closing, consider this thought on globalization fromStas
Margaronis, “The time has come for Europeans andNorth Americans,
who have for years advocated globalizationin the outsourcing of
production, to begin practicing the needfor globalization in the
saving of human life.”
References1. “Avian influenza – Situation in Indonesia – Update
23,”
Retrieved July 20, 2006, from
http://www.who.int/csr/don/2006_07_20/en/index.html.
2. George Santayana (1863-1952) was a poet, philosopher,and
humanist.
3. “Focus on the Flu – Timeline of Human Flu
Pandemics,”Retrieved May 17, 2006 from
http://www3.niaid.nih.gov/
What is Influenza?Influenza is an obligate parasite, which
cannot reproduceby itself and requires a host to replicate. There
are threetypes of influenza: Type A, Type B, and Type C. Type
AInfluenza’s can infect a variety of hosts, including birds,swine,
horses, and humans. Type A and Type B areresponsible for the
seasonal flu outbreaks and they havethe ability to genetically
mutate to avoid the host’sdefense mechanisms.4 We are probably all
too familiarwith the common flu symptoms: fever; sore
throat,coughs, chills, and muscle aches. On the other hand, TypeC
influenza is responsible for non-seasonable mild illnessin
humans.
Type A InfluenzaType A Influenza strains are named based on the
subtypeof two important surface glycoproteins: hemagglutininand
neuraminidase. Hemagglutinin (HA) has 16 subtypes,H1-H16, and
allows the virus to attach to and enter a hostcell. Neuraminidase
(NA) has nine subtypes, N1-N9, andallows the mature virus to escape
from the host cell afterreplication. Humans and swine are natural
reservoirs forthe following influenza Type A subtypes: H1, H3, N1,
N2,and H2 (humans only). However, birds are a naturalreservoir for
all subtypes of Influenza Type A. The H5N1strain of influenza (Type
A) is the first known case of anavian flu being responsible for
directly infecting humans.
Medical Resources for Influenza – Vaccines andAnti-Viral
MedicationWhat about vaccines and anti-viral medication? Theannual
flu vaccine is a trivalent vaccine – made up of threedifferent
influenza strains. Normally, the flu vaccine iscomposed of two Type
A Influenza strains and one TypeB Influenza Strain. Dr. Joe Duarte,
a financial writer,stated that Novavax has two flu vaccines in
early stagesof development.21 However, we will need to isolate
theexact strain of pandemic influenza from patients and thenit will
take between six to nine months to have theeffective pandemic flu
vaccine ready for mass vaccina-tion. On the other hand, Gilead and
Roche and GlaxoSmithKline make Tamiflu and Relenza, which are
twoantiviral neuraminidase inhibitors. Neuraminidase inhibi-tors
appear to have fewer incidences to drug resistancethan the other
class of antiviral medication, M2 ionchannel inhibitors.
Vaccines are currently manufactured through the useof chicken
eggs. It takes approximately 300 million eggsto produce 90 million
doses of trivalent flu vaccine a year.4
If we have to slaughter chickens to remove the spread ofH5N1,
how are we going to have enough eggs to generatea vaccine against
H5N1? Luckily, there are also companiesworking on vaccines that are
not dependent on chickeneggs. The U.S. Department of Health and
Human Services(HHS) awarded more than one billion in contracts in
May,2006 for the development of cell-based vaccine technol-ogy to
the following companies: Solvay Pharmaceuticals($299 million),
GlaxoSmithKline ($275 million), NovartisVaccines and Diagnostics
($221 million), MedImmune($170 million), and DynPort Vaccine ($41
million).22 HSSalso is expected to award more contracts for the
construc-tion of new vaccine facilities or expansion/redesign
ofexisting facilities and for ways to reduce the amount ofvaccine
that is required for protection.
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focuson/flu/illustrations/timeline/timeline.htm.4. “Preparedness
and Community Response to Pandemics,”
On-line course by the University at Albany School ofPublic
Health, State University of New York, May 2006.
5. Olson, D.R., Simonsen, L., Edelson, P.J., and Morse,
S.S.,“Epidemilogical Evidence of an Early Wave of the 1918Influenza
Pandemic in New York City,” PNAS, Vol. 102,No. 31, 2005, pp.
11059-11063.
6. Appenzeller, T. “Tracking the Next Killer Flu,” RetrievedMay
17, 2006 from
http://www7.nationalgeographic.com/ngm/0510/feature1/index.html.
7. “Stopping the Spread of Germs at Home, Work, andSchool,”
Retrieved on July 20, 2006 from
http://www.cdc.gov/flu/protect/stopgerms.htm.
8. Webster, R.G. “Influenza: An Emerging Disease.” Emerg-ing
Infectious Disease, Vol. 4, No.3, 2005.
9. Webster, R.G, Yakno, M.A., Hinshaw, V.S., Bean, W.J.,and
Murti, K.G., “Intestinal Influenza: Replication andCharacterization
of Influenza Viruses in Ducks,” Virol-ogy, Vol. 84, 1978, pp.
268-78.
10. Maslow, A. H., “A Theory of Human Motivation,”
Psycho-logical Review, Vol. 50, 1943, pp. 370-396.
11. Dale Carnegie (1888-1955) was a lecturer and author.12.
Louis Pasteur (1822-1895) was a chemist and microbiolo-
gist.13. “Responding to the Avian Influenza Pandemic Threat
–
Recommended Strategic Actions,” Retrieved May 30, 2006,from
http://www.who.int/csr/resources/publications/influ-enza/WHO-CDS_CSR_GIP_05_8-EN.pdf.
14. Staples, J., “A New Type of Threat,” Harvard BusinessReview,
Vol. 84, No. 5, 2006, pp. 20-22.
15. Bennis, WG., “Leading for the Long Run,” Harvard Busi-ness
Review, Vol. 84, No. 5, 2006, pp. 23-24.
16. Nohria, N., “Survival of the Adaptive,” Harvard
BusinessReview, Vol. 84, No. 5, 2006, pp. 23.
17. Zawisza, J., “FDA Announces Rapid Response Team toCombat
Pandemic (Avian) Flu,” Retrieved September 5,2006 from
http://www.fda.gov/bbs/topics/NEWS/2005?NEW01248.html.
18. “Watson Wyatt Survey Finds Companies Preparing forAvian Flu
Across the Globe,” Medical Letter on the CDCand FDA, Retrieved
September 5, 2006 from
http://www.newsrx.com/library/newsletters/Medical-Letter-on-the-CDC-and-FDA/230329.html.
19. Edward de Bono (1933 - ) is a psychologist and physician.20.
Stas Margaronis is the publisher of Influenza-
Pandemic.com.21. Duarte, J., “Bird Flu Update: Science and
Stocks from Dr.
Joe Duarte,” Retrieved June 5, 2006 from
http://www.joe-duarte.com.
22. Leavitt, M.O., “Department of Health and Human Ser-vices:
Pandemic Planning Update II,” Retrieved July 20,2006 from
http://www.pandemicflu.gov/plan/pdf/PanfluReport2.pdf.
About the AuthorsWendy Haines, PhD, is currently a
ProjectScientist for the TOX Business Unit of OMNIProfessional
Environmental Associates, P.A.Prior to joining OMNI, Haines was
aLineberger Comprehensive Cancer CenterFellow in which she
performed pediatric can-cer research. She has seven years of
com-bined experience working for both the Envi-ronmental Protection
Agency (EPA) and the
National Institute of Environmental Health Sciences(NIEHS). She
has conducted research dealing with dioxin,lead, Electromagnetic
Field (EMF), insecticides, and chroma-tin remodeling. Haines
currently works with a variety oftoxicological services, including
epidemiology/business con-tinuity planning; expert scientific
testimony, environmentaltraining, and air quality issues. She has
degrees in pharma-ceutical sciences and biology from Campbell
University anda PhD in toxicology from the University of North
Carolina,Chapel Hill. She is currently the Chair of the Carolina
SouthAtlantic (CASA) ISPE Student Committee and CASA Boardmember,
as well as a member of the ISPE InternationalStudent Development
Committee. She is also a member ofthe Society of Toxicology (SOT),
Sigma Xi, and The ScienceAdvisory Board. She can be contacted by
telephone: (919)544-5442; fax: (919)544-5708; or
email:[email protected].
OMNI Professional Environmental Associates – TOXBusiness Unit,
P.O. Box 13404, Research Triangle Park, NC27709-3404
Martin E. Rock, PE, JD, is responsible fora broad range of
Environmental, Health, andSafety (EHS) engineering and
consultingservices at OMNI Professional Environmen-tal Associates,
P.A. Rock provides consulta-tion and expertise for projects,
including in-tegrated contingency plans and business con-tinuity
planning, environmental manage-ment systems such as ISO 14001, air
quality
permitting, including Title V operating permits and
Pharma-ceutical MACT compliance, water and wastewater manage-ment,
and hazardous waste management. He is also anexperienced trainer,
and he conducts training competenceand effectiveness reviews and
EHS training for several majorpharmaceutical and healthcare
companies. Rock is a licensedprofessional engineer in five states
with a master’s degree inengineering and he also is a licensed
attorney. He has twoengineering degrees from the University of
Michigan Collegeof Engineering, and he has a Juris Doctor (JD)
degree fromthe Lumpkin School of Law at the University of Georgia.
Rockis a member of the ISPE Carolina-South Atlantic Chapter,and he
will be serving as incoming Chapter President duringthe 2006-07
Chapter year. He is also a member of theAmerican Bar Association
(ABA), the AIChE (American In-stitute of Chemical Engineers), and a
business partner of theManufacturers and Chemical Industry Council
of NorthCarolina. He can be contacted by telephone: (919)
544-5442;fax: (919) 544-5708; or email:
[email protected].
OMNI Professional, P.O. Box 13404, Research TrianglePark, NC
27709-3404.
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This articlepresents anoverview of
thedifferencesbetweenregulatoryauthoritiesbetween firstworld and
thirdworld countries,and theprobl