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A Validation Approach for Laboratory Information Management Systems

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A Validation Approach for
Laboratory Information
Management Systems
By Douglas S. Tracy
Pfizer Pharmaceutical Group Global Business Technology
and
Robert A. Nash, Ph.D.
New Jersey Institute of Technology
❖
types of systems. Although many genaboratory Information Man❝…this
paper
eral principles are shared with Good
agement Systems (LIMS) are
Manufacturing Practice (GMP) and
an increasingly important
is to discuss
process validation standards, the
component of any modern laboratoa
potential
nature of software also demands a
ry. As these systems become the
approach to
slightly different approach. Additionmain source of records for the lab’s
al requirements are necessary to enwork, especially the quality managevalidation for
sure adequate validation – requirement aspects of work, they will be a
LIMS . Any
ments that non-Information Technolnatural target for Food and Drug Adogy (IT) specialists may not be familministration (FDA) inspections. In
effective
iar with. Compounding this problem
addition, by relying more and more
validation
is
that many IT specialists are not
on these systems instead of paperfamiliar with the demanding requirebased records, a firm is becoming exercise begins
ments of the pharmaceutical/biotechcritically dependent upon their sucwith thorough
nology industries. Therefore, a fresh
cessful and reliable operation. Any
look at validation for LIMS, blending
failure in these systems could cause a planning, based
the
best of both traditional FDA-regheavy increase in workload in the
upon a sound
ulated industry validation procedures
best case, and a catastrophic event for
approach. ❞
and software engineering validation
the lab in the worst case. Thus, it is
procedures, is worthwhile for organivitally important that a sound approach to validation be taken to ensure that adequate zations, which have or are considering, installation of
preparation for any potential inspection has taken place, these systems.
and that these systems will be reliable enough for conWhat is a Laboratory Information
tinued operations in the laboratory.
Management System?
The purpose of this paper is to discuss a potential
approach to validation for LIMS. Any effective validaBefore beginning to delve into the specifics of valtion exercise begins with thorough planning, based
upon a sound approach. However, for pharmaceutical idation, a brief review of LIMS is useful. Only by
understanding the scope of the components in these
professionals, this is easier said than done for these
L
6
Journal of Validation Technology
Douglas S.Tracy & Robert A. Nash, Ph.D.
systems is it possible to create effective validation
plans. In addition, since a LIMS itself is often a component of a much larger information system, validation needs may very well extend beyond the LIMS
into other systems and processes. Thus, what a LIMS
is, and how it may fit into the larger information systems landscape is very important when determining
the complete set of validation exercises required.
Purpose and Functionality
The basic purpose of a LIMS is to assist industry
personnel with managing large volumes of information
inside a typical laboratory. These systems first appeared in the early 1980s, and were first used to automate
the collection and reporting on stability data.1 Along
with stability testing, LIMS are also used for process
control and document management, providing a flexible and easily accessible platform upon which to develop and store process steps and documentation. As an
adjunct to this function, LIMS are very useful platforms for the Quality Control (QC) and Quality Assurance (QA) functions, as they provide a simple way of
sampling data and utilizing quality management tools
for process monitoring and improvement. Finally, LIMS
are also useful as an integrating mechanism, by being
able to accept inputs directly from many types of laboratory equipment and coordinating supplies, schedules, etc. with Materials Replenishment Planning
(MRP) or Enterprise Resource Planning (ERP) systems used for corporate logistics.
Major Components of a LIMS
As an example of a specific LIMS, the features of
the LabSys LIMS are in Figure 1 (listed by specific
module).2
In addition to the standard functionality of most
LIMS, there are specialized modules or complete software packages to meet many other needs. For example,
the Matrix Plus LIMS from Autoscribe contains a
“Quotation Manager” that “allows laboratory and commercial personnel to track the progress of a contract for
laboratory analysis work from initial inquiry to receipt
of purchase order and the login of samples into the system.” 3 LIMS also come in a wide variety of shapes and
sizes, from simple MS Access-based programs for
smaller labs, to larger-scale, complex relational database client-server-based systems for larger laboratories.
There is even one company, ThermoLabs, which is
Figure 1
LabSys LIMS Summary Functions
LIMS for
Quality Control
Set-up and
Configuration
Sample
Management
Allows the system to be configured to
site-specific requirements
Sample lifecycle, including all the
standard functionality normally
associated with a standalone LIMS
system. It supports many additional QA functions
Vendor Monitoring Controls different sampling plans,
and skips lot testing parameters
per vendor/product relationship. It
tracks vendor performance and
provides vendor performance
reports
ERP Integration
Allows data to be interchanged
between LabSys LIMS and ERP
systems.
Document
Allows links to documents and
Management Link external document management
systems for tests, samples, products, etc.
Process LIMS
In-Process
Sampling
Controls sample testing during
the manufacturing stages of a
batch process.
Batch Tree
Traceability
Full batch traceability with ERP
interface
Stability LIMS
Stability Trial
Template
Allows definitions of time-points,
conditions, and testing to be performed at each stage.
Trial Management
Used to manage all stability trials,
and provide reporting on each.
Stability
Scheduler
Automatically schedules samples
for testing when the time-point
arrives.
Instrument Connect
Simple
Instruments
Collects and passes data from
simple instruments, such as bal ances and meters, and can process this before reporting to LIMS.
Complex
Instruments
Collects and passes data from
complex PC-controlled instruments,
such as High Performance Liquid
Chromatography (HPLC) and Gas
Chromatography (GC). Can be
configured to deliver a worklist
from LIMS to the instrument, and
subsequently upload the results
from the instrument to LIMS.
November 2002 • Volume 9, Number 1
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Douglas S.Tracy & Robert A. Nash, Ph.D.
offering their LIMS via an Application Service
Provider (ASP) model, where the software is hosted by
ThermoLabs. The using company hooks up to the system over a secure Internet connection, and fees are collected by ThermoLabs on a monthly rental basis.4
Overall Validation Approach
The key to an overall validation approach is taking a system-level approach to the problem. In other
words, not to just validate the individual components of the process – software, hardware, user procedures – but to treat these components as part of an
overall system that needs system-level validation.
Thus, we must remember not to get too lost in the
details, but to focus on the overall outcome for validation, which is in essence a quality assurance process. As the FDA states in their Guidance on General Principles of Process Validation:
The basic principles of quality assurance have
as their goal the production of articles that are fit
for their intended use. The principles may be stated as follows:
1. quality, safety, and effectiveness must be
designed and built into the product;
2. quality cannot be inspected or tested into the
finished product; and
3. each step of the manufacturing process must
be controlled to maximize the probability that
the finished product meets all quality and design specifications5
Basics of Validation – Other Key Definitions and
Scope
We should also keep in mind a few key definitions,
as these will be vitally important to outlining a specific plan for our LIMS validation. First of all, we need
to review the basic definition of validation according
to the FDA, both in the context of process and software. In the FDA Guidance on General Principles of
Process Validation, they defines process validation as:
Process validation is establishing documented
evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-determined specifications and quality characteristics. 5
8
Journal of Validation Technology
The FDA also defines software validation separately in their General Principles of Software Validation guidance document, although in much the same
spirit:
FDA considers software validation to be “confirmation by examination and provision of objective evidence that software specifications conform
to user needs and intended uses, and that the particular requirements implemented through software can be consistently fulfilled.”6
Another key definition in the General Principles
of Software Validation document is that of software
verification:
Software verification provides objective evidence that the design outputs of a particular phase
of the software development life cycle meet all of
the specified requirements for that phase6
In addition, the definitions of Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ) are well known to most
pharmaceutical manufacturing personnel, but bear repeating here as specified by the FDA:
Qualification, installation – Establishing confidence that process equipment and ancillary systems are compliant with appropriate codes and
approved design intentions, and that manufacturer’s recommendations are suitably considered.
Qualification, operational – Establishing confidence that process equipment and ancillary systems are capable of consistently operating with
established limits and tolerances.
Qualification, process performance – Establishing confidence that the process is effective and
reproducible.
Qualification, product performance – Establishing confidence through appropriate testing that
the finished product produced by a specified process meets all release requirements for functionality and safety.7
Finally, we should keep in mind that validation
could become an onerous task if not approached in a
reasonable manner. One major consulting firm, Ac-
Douglas S.Tracy & Robert A. Nash, Ph.D.
centure LLP, estimates that pharmaceutical firms
often spend twice as much time and cost to complete
validated systems projects – often because of additional requirements imposed by company Standard
Operating Procedures (SOPs), and QA personnel
that are not mandated in regulations.8 After all, the
FDAin its General Principles of Software Validation
refers to using the least burdensome approach to
meeting the regulatory requirement.6 Thus, while we
should take a very serious and deliberate approach to
validation, we should focus on assurance of a repeatable and high quality outcome, and not on trying to
“boil the ocean” with unnecessary extensive testing
and/or overly detailed documentation.
Validation Master Plans
With these considerations in mind, the key document to produce before starting is a Validation Master
Plan (VMP). In this document, we need to outline the
major steps we are taking to validate this particular system. While we should make use of available company
SOPs and templates, this document should be specific
to the problem at hand. It should take a risk-based
approach to ensure that efforts are being focused on the
most likely trouble spots, while limiting the overall validation effort to one of reasonable size and scope.
Although this is similar to what the FDA defines as a
“validation protocol,” this document is at a somewhat
higher level. Detailed test results and “pass/fail” criteria
are not specified, rather the focus is on the guiding principles and scope of the validation effort, as well as a
high-level overview of the tasks, costs, and resources
required for validation. Other supporting documents are
used to provide detailed information on test results for
specific validation tasks. Nonetheless, this document is
extremely important, for it will provide the baseline for
all other validation tasks, and will likely be the first document that any inspector would like to review.
While this paper is not attempting to provide a
specific outline for a VMP, it will provide the basis
upon which to build such a plan. Arguably, the harder part of the plan document is determining an appropriate approach to validation. Once this is done,
it is a relatively straightforward exercise to flesh out
the details and blend in company SOPs, etc. Thus,
the remainder of this paper will concentrate on
developing the strategic approach in a generic fashion, with the understanding that this will need to be
tailored to an individual company’s situation in order to be “implementable.”
System Validation
As stated before, the goal of the validation exercise
is to have a complete validated system. It is useless to
validate part of the system, or the hardware and software separately, and then to assume that they will work
together in the end. The validation approach must be
holistic, certifying the system as a complete unit –
exactly as it is intended to be used operationally.
In this regard, there are several major phases in a
typical system validation. One is due to the fact that we
are almost always buying an off-the-shelf software
product, e.g. the basic LIMS package. Thus, since we
are not building this ourselves, this aspect of validation
must focus on the vendor in an attempt to reasonably
satisfy ourselves that they have a sound software development process in place. Another phase is the validation of those parts of the system that are either custombuilt, or configured for our specific implementation of
the system. In many cases, the functionality or integration capability of the package may be too generic for
our specific purposes – thus we need to have either the
system vendor or another systems integration firm do
some custom software development work to build the
complete system we need. In addition, in almost all situations, a LIMS requires some degree of configuration,
ranging from designing in specific workflows, to creating templates for standard lab data sheets or QA
reports. In either the custom-built or configured situation, validation is required for all of these activities.
Finally, we need to ensure that what we have created
will work properly in our environment – thus a final
validation step to ensure the system works in our environment is warranted. In summary, we could define our
system validation goals as follows:
• Did we buy the right product?
• Did we add the right features to the product we
bought?
• Will this customized/configured product function
correctly in our production environment?
Vendor Validation
Although many vendors tout their products as “21
CFR Part 11 compliant” and “fully validated according
November 2002 • Volume 9, Number 1
9
Douglas S.Tracy & Robert A. Nash, Ph.D.
to FDA standards,” the phrase “caveat emptor” or
“buyer beware” should be kept in mind by the organization. Since these companies are software organizations,
the FDAis not inspecting them, and their claims may or
may not be true. In addition, the final responsibility for
validation rests with the pharmaceutical or biotech company—and not with the software product vendor.
According to the FDA, in their Guidance for Industry:
Computerized Systems Used In Clinical Trials:
For software purchased off-the-shelf, most of
the validation should have been done by the company that wrote the software. The sponsor or contract research organization should have documentation (either original validation documents or
on-site vendor audit documents) of this design
level validation by the vendor, and should have
itself performed functional testing (e.g., by the use
of test data sets) and researched known software
limitations, problems, and defect corrections.9
Thus, the organization has a requirement to conduct a reasonable amount of due diligence on the
vendor for assurance of validation on their product.
So what would be a reasonable approach to validating the vendor entail? Basically what is needed is a
two-pronged approach. One is the validation of the
product itself, by reviewing the vendor’s documentation on what specific validation tests they conducted.
This should include a validation master plan, and a
sampling of test results – including any known product
limitations or defects. Since software products are
extremely complicated, and typically consist of thousands, if not millions, of lines of code, some defects
should be expected. In fact, one should be suspicious of
any vendor that claims their product is “defect free.”
This means that they are not sharing all of the information with you, or worse yet, they have conducted inadequate testing to uncover the bulk of the defects. The
other aspect of vendor validation is to look at the vendor’s Software Development Life Cycle (SDLC)
process. For this aspect, there are several reasonable
approaches, ranging from having the company’s internal IT department conduct a cursory review, to utilizing a report of an independent auditing group against
an industry standard, such as International Organization for Standardization (ISO) 9000, TickIT® or
Capability Maturity Model (CMM). Again, we are
10
Journal of Validation Technology
only trying to meet a reasonable standard here, so
spending an abundance of time on the vendor’s SDLC,
or reviewing their testing/validation procedures is usually not warranted. If there are concerns, the best approach is usually to pick another vendor and potentially avoid a problem. If there are any lingering concerns,
then schedule in more time to the testing phase of the
validation plan to fully address these issues.
Approaches to Customized System Validation
Now that we have a vendor we are comfortable
working with, we need to consider how we will validate the inevitable configuration and/or customization that accompany all LIMS implementations.
Again, there is a range of approaches available, with
some benefits and risks to each approach.
GAMP V-Model: Is this really a workable model?
The first approach is usually described as using the
Good Automated Manufacturing Practice (GAMP) VModel, as cited by a number of companies seeking to
sell their validation consulting services.10 This model is
illustrated in Figure 2, and is one that is troubling, to
say the least. While the pharmaceutical professional
may feel comforted by the familiar IQ/OQ/PQ phraseFigure 2
Good Automated Manufacturing
Practice V-Model
User
Requirements
Specifications
Functional
Specifications
Related to
Related to
Detailed
Related to
Design
Specifications
System Build
Performance
Qualification
(PQ)
Operational
Qualification
(OQ)
Installation
Qualification
(IQ)
Douglas S.Tracy & Robert A. Nash, Ph.D.
ology, the model does not fit together conceptually
with a logical approach for software system validation.
For example, how does the IQ relate to the Detailed
Design Specifications? The answer is that it really doesn’t in this context. Looking back to our definition of IQ,
we see that this really refers to compliance with appropriate codes, standards, and design intentions. This is
exactly what the user requirements document should be
stating. For example, a good user requirements document states which applicable regulations (21 CFR Part
11, etc.) need to be considered for the solution. In addition, the user requirements in their final state should
reflect the limitations of a particular software package.
Although a package is normally selected after the first
draft of user requirements, we must often adjust some of
the requirements to reflect what is available and achievable with a particular package. If we list out requirements that cannot be achieved within our cost parameters, then we either need to adjust our requirements, or
reflect that this will be a custom addition to the selected
package. But, in any case, we need to have complete
traceability between the user requirements and the final
solution – thus the need for adjustment.
For this model to be correct, we could possibly substitute Design Qualification (DQ) for IQ, and move the
IQ across from the user requirements, but it doesn’t
solve our problem completely, because we still don’t
have an equivalent for OQ and PQ. In addition, we
need to think about the need for intermediate testing. In
fact, the FDAstates that “typically, testing alone cannot
fully verify that software is complete and correct. In
addition to testing, other verification techniques and a
structured and documented development process
should be combined to ensure a comprehensive validation approach.”6 As another reference, the Institute of
Electrical and Electronics Engineers (IEEE), one of the
key standards settings bodies for software engineering,
refers to Validation and Verification as complementary
concepts.11 Thus, this model is not only flawed with
respect to terminology, it is fundamentally incomplete.
The Software Engineering V-Model: What about
IQ/OQ/PQ?
With the limitations of the previous GAMP Vmodel in mind, we can take a look at a standard software engineering approach to the V-model. Here we
see a much more comprehensive approach taken to
verification as a prerequisite to validation. As de-
picted in Figure 3, we see that for each stage of
refinement from the user requirements, there is a
verification process.12 What happens in this verification process is that a review of how well the output
of a particular stage maps back to the previous stage
takes place. This can take the form of a formal architecture/design/code review, or a series of more informal “structured walkthroughs.” In either case, the
outcome is the same, and we are looking for where
there were potential gaps or poor handoffs between
the stages. This is critically important for two reasons. The first is that these tasks are often done by
different people, and/or sub-teams with specific skill
sets, so some miscommunication or misunderstanding is likely. Secondly, as we understand more and
more about the solution, it is likely that additional
clarifying questions will be asked about the overall
solution. Some of these questions may prompt a
modification to the output of the previous stage.
Thus, to keep everything in synch, we need to perform the verification step.
The other difference from the GAMP model is that
we now have traceability, along similar levels of detail
for the purposes of designing tests. Specific code modules are tested by unit testing (both a verification and
Figure 3
Software Engineering V-Model
User
Requirements
Specifications
Related to
User
Acceptance
Testing
Verification
High-Level
Design and
Architecture
Related to
System
Testing
Verification
Detailed
Related to
Design
Specifications
Integration
Testing
Verification
Unit
Coding
Unit Testing
November 2002 • Volume 9, Number 1
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Douglas S.Tracy & Robert A. Nash, Ph.D.
validation step), the detailed design is tested by integration testing among code modules, and the overall
system design and user requirements are tested by
both system testing and user acceptance testing (the
difference being that system testing is conducted by
software developers, and is typically more comprehensive. User acceptance testing is performed by end
users, and is typically somewhat more cursory). The
danger with this approach, or perhaps the question it
raises, is just how far to go with testing. The best way
to gauge this is to take a risk analysis approach. Thus,
by looking at the risk inherent in failures of various
parts of the system, we can test to a reasonable level,
and avoid spending too much time on testing the
detail.13
However, even though this model is much more
comprehensive than the GAMP model, it still lacks
some final testing and validation. Remember, the
overall goal is to have a system that supports a particular process in a verifiable and reproducible manner.
In this model, although the system is tested and accepted by the user, there is no specific equivalent to the
OQ and PQ concepts as discussed before. Thus, we
need another level of validation to complete our validation approach.
A Combined V-Model for Pharmaceutical Systems
While the two previous models both had their
shortcomings, if we take both of them together, all
of the requirements of a comprehensive validation
approach are covered. Both the detailed validation
of software development activities (configuration
and/or customization), and the overall process
aspects are tested and confirmed. Thus, we have a
model (as depicted in Figure 4) that combines the
GAMP V-model and the software engineering Vmodel into one logical flow. The starting point is the
user requirements, as with the Software Engineering (SE) approach, and the flow continues along the
SE approach until the User Acceptance Testing
(UAT) as before. However, there is one important
point of exception. That is, the UAT and the IQ can
be done at the same time, since they are fulfilling
similar goals, but for slightly different audiences.
The UAT is the opportunity for the end users to confirm that the system fulfills the system expectations,
including compliance with appropriate regulations.
The IQ is the opportunity for the technical support
staff to confirm that the system (both hardware and
software), can be installed in an operational environment in a manner that is both repeatable and ver-
Figure 4
Extended V-Model for Pharmaceutical System
User
Requirements
Specifications
Related to
User
Acceptance
Testing/IQ
Verification
High-Level
Design and
Architecture
Related to
System
Testing
Verification
Detailed
Related to
Design
Specifications
Integration
Testing
Verification
Unit
Coding
Unit Testing
12
Journal of Validation Technology
Operational
Qualification
Performance
Qualification
Douglas S.Tracy & Robert A. Nash, Ph.D.
ifiable via testing. A successful conclusion to both
the UAT and IQ is a system that is functionally and
operationally qualified to place in the operations
environment. From this point on, a more traditional
OQ and PQ approach applies, as the system should
be “stress tested” and confirmed for acceptable operations and continuing performance in the actual
operating environment. In addition, although we
have broken out the UAT/IQ from the OQ/PQ, this
may be easily combined into one comprehensive set
of testing if the UAT/IQ takes place in the actual
operations environment. This is usually possible if
the system is going into a “greenfield” environment
where it is not replacing another system. However, if
the system is replacing another, most likely the
UAT/IQ will take place in a pilot environment –
either to reduce risk or keep the old system running
until there is sufficient confidence in the new system
to shut down the old system. In either case, we must
be vigilant about ensuring the adequacy of final testing, as there is a tendency to rush through after the
UAT phase. Although everyone is anxious to get the
new system into production, many UATs are not
comprehensive enough to fulfill both functional and
operational testing needs. Therefore, we should be
very cautious about arbitrarily combining the UAT
and the OQ/PQ into one testing phase. When in
doubt, keep the phases distinct to avoid confusion
and unnecessary risk in the process.
Preparing for Inspections
and Ongoing Validation
While having the basic validation process well in
hand is a must, there are a couple of other issues
concerning validation that are almost as crucial. One
is the documentation of the approach, plan, and
results of validation in a form that is not only logical, but can easily be presented to any potential
inspector – internal or external. The other is the need
for ongoing validation of changes to the software or
process. Simply validating the process one time is
never enough. There will always be improvements
to the process, bug fixes to the software, new releases of the software, etc. that will require ongoing validation for the overall process to remain “qualified.”
Thus, a few additional words on these topics are in
order.
Presentation of Validation Information
One of the goals of validation is to be able to demonstrate quickly to an outsider (management, internal auditors, FDA, etc.) that the process/system is indeed validated. Thus, early on in the process, part of
the validation approach should be a consideration of
what the required documents are, and how they should
be organized and stored. This will allow a top-down
approach to documentation, and make it much easier
to track through the validation process. In addition,
there may be some overall validation efficiencies
gained from following such an approach. As noted by
the consulting firm, Accenture, documentation is one
of the key reasons for additional cost with a validated
system.8 By focusing early on the documentation strategy, including defining the hierarchy of documents
and constructing templates to guide the work, we can
avoid some of the cost of excessive documentation,
while ensuring that we have adequate documentation.
Finally, we should make sure to implement a good
version control process on our documentation. Most
pharmaceutical firms have some type of document
management system/process already in hand for this
purpose, and it should clearly be used to store versioned copies of the system validation documentation.
Change Management – The Need for Ongoing Validation
Once we have a validated system in place, the
work is not over for our validation approach. We
must ensure that there is an effective change management process in place both to determine the potential benefits/costs/effects of changes, and to ensure that we test appropriately. From a validation perspective, there are really three things to keep in
mind. First of all, we must test the actual changed
code itself, which is pretty obvious and straightforward. In addition, we must conduct what is referred
to as “regression testing” to test system functionality that was not directly changed, but may have been
inadvertently changed as a result of another change.
In this area, obviously a great deal of judgment must
be employed to avoid both over-testing, by redoing
all of the tests, and under-testing, by making too
many assumptions about what the change will or
will not affect. One approach to this is to conduct
both testing of areas that may be likely to experience
a side effect of the change, and a limited sample of
November 2002 • Volume 9, Number 1
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Douglas S.Tracy & Robert A. Nash, Ph.D.
the other tests to confirm that the assumptions were
appropriate. A good reference when developing a
change management plan is to review IEEE Std
1042-1987, IEEE Guide for Software Configuration
Management as a baseline for the change.14
3.
4.
5.
Conclusion
6.
Successful validation of a LIMS is a challenging
task, but one that can be met if a sound approach to
the problem is used. Traditional process manufacturing validation techniques are not enough, and software engineering techniques don’t address all of the
concerns of pharmaceutical manufacturers. However,
by bringing together the best of the two into a blended approach, a successful strategy can be formulated.
When this approach is combined with a sound documentation plan and ongoing change management, the
fundamentals will be in place to not only have a
soundly verified LIMS, but one that is able to pass the
most demanding FDA inspection as well. ❏
7.
8.
9.
10.
11.
12.
13.
14.
About the Author
Douglas S. Tracy is the Director, Global Business Technology for the Pfizer Pharmaceutical Group (PPG). His
current responsibilities focus on systems and information processes within the safety and regulatory affairs
area of PPG. He has over 20 years of operational and
information technology management in both the public
and private sectors. Doug holds a BSEE with honors
from the U.S. Naval Academy, an MBA with honors from
Duke University, and an MS in Software Development
and Management from the Rochester Institute of Technology. He can be reached by phone at 212-733-5947,
or e-mail at [email protected].
Robert A. Nash, Ph.D., is Associate Professor of Industrial Pharmacy at the New Jersey Institute of Technology. He has over 24 years in the pharmaceutical industry with Merck, Lederle Laboratories, and The Purdue Frederick Company. Dr. Nash is co-editor of
Pharmaceutical Process Validation, published by Marcel Dekker and Co. He can be reached by phone at
201-818-0711, or by fax at 201-236-1504.
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2.
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Brush, M. “LIMS Unlimited.” The Scientist. 2001, Vol. 15,
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LabSys Ltd. System Appreciation Guide 2.1: LabSys LIMS.
http://www.labsys.ie. March, 2002.
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Autoscribe, Ltd. Plus Points newsletter #2. http://www.autoscribe.co.uk.
ThermoLabSystems, Inc. Pathfinder Global Services Group
Overview.http://www.thermolabsystems.com/services/pathfin
der/nautilus-asp, May, 2002.
FDA. Guideline on General Principles of Process Validation.
Division of Manufacturing and Product Quality (HFD-320), Office
of Compliance, Center for Drug Evaluation and Research.
May, 1987.
FDA. General Principles of Software Validation; Final Guidance
for Industry and FDA Staff. Center for Devices and Radiological
Health. January 11, 2002.
FDA. Glossary of Computerized System And Software Development Terminology. F D AO ffice of Regulatory Affairs Inspector’s
Reference. 1994.
Accenture LLP. Computer Systems Validation: Status, Trends,
and Potential. Accenture LLP. White Papers. 2001.
FDA. Guidance for Industry: Computerized Systems Used In
Clinical Trials. FDA Office of Regulatory Affairs Inspector.
April, 1999.
Invensys, Inc. Overview of Validation Consulting Services.
http://www.invensys.com. May, 2002.
Institute of Electrical and Electronics Engineers. IEEE Standard
for Software Verification and Validation, IEEE Std 1012-1998.
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Article Acronym Listing
ASP:
CMM:
DQ:
ERP:
FDA:
GAMP:
GMP:
IEEE:
ISO:
IQ:
IT:
LIMS:
MRP:
OQ:
PQ:
QA:
QC:
SDLC:
SE:
SOP:
UAT:
VMP:
Application Service Provider
Capability Maturity Model
Design Qualification
Enterprise Resource Planning
Food and Drug Administration
Good Automated Manufacturing Practice
Good Manufacturing Practice
Institute of Electrical and Electronics
Engineers
International Organization for
Standardization
Installation Qualification
Information Technology
Laboratory Information Management
Systems
Materials Replenishment Planning
Operational Qualification
Performance Qualification
Quality Assurance
Quality Control
Software Development Life Cycle
Software Engineering
Standard Operating Procedure
User Acceptance Testing
Validation Master Plan
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