Introducing a Paperless Lab - Vialis

ELN
Andreas Schild
How optimization and simultaneous electronic support of actual laboratory
processes can boost efficiency
Ulf Fuchslueger
Introducing a Paperless Lab
Laboratories working in the
pharmaceutical industry in
the areas of R&D and quality
control find themselves
increasingly having to cope with
conflicting demands — tougher regulatory
requirements and harsher economic
realities. In order to meet these
demands, new ways of dealing with
process, data and system management
are necessary. This article shows how
the paperless lab (as an integrated
process, and not as a system implementation)
can meet these challenges
and boost efficiency.
WHY NEW CONCEPTS
FOR LABORATORY DATA
MANAGEMENT?
On the one hand, the authorities
require more data with more quality,
such as with the new EU GMP
Annex 11 and the more intensive FDA
inspections regarding 21 CFR Part
11. And, on the other hand, there are
the commercial pressures requiring
more data in less time, typically with
the same level of staff or less. On top
of that, advances in technology and
laboratory equipment mean that even
more data is being generated faster,
which creates almost insurmountable
obstacles for conventional
documentation and datamanagement
processes in
regulated laboratories.
These obstacles, in turn,
causes bottlenecks
for the development and approval
processes.
THE ROOT OF ALL EVIL:
HYBRID SYSTEMS
When you look at data management
in the lab, what you usually
see is a mixture of various independent,
non-integrated data-processing
systems on paper and in electronic
form. Often, paper is the preferred
documentation medium when you
have a mix of countless computer-
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ELN
Table 1: Typical key performance indicators for quality
control and development laboratories.
KPI Value*
Effort documentation and control 45%
Number of quality-relevant transfers 100
(per approved batch)
Number of redundant data transfers 250
Process time up to 20 days
Systems in operation (paper and 10
electronic)
*With the exception of the documentation and control effort, all numbers
refer to the approval or analysis of one batch. Quality-relevant
transfers have a direct impact on the result; redundant data transfers
provide references and cross-references.
ized systems, such as analyzers, offi ce applications
and higher-level systems like laboratory information
management or enterprise resource planning
(ERP) systems. Such a scenario results in producing
a hybrid system with numerous media gaps — this
is the real root of all evil, leading to ineffi ciencies,
quality and compliance risks and unnecessarily long
throughput times, which prevent businesses from
hitting their targets.
Table 1 shows the typical key performance indicators
of such a laboratory. The high level of quality
risk (due to the high number of manual
data transcription steps) is countered
with extensive control steps — but
that results in less effi ciency and longer
throughput times. The use of isolated
systems prevents the timely transfer
of information, which leads to further
unforeseeable delays and additional costs.
And last, but not least, it can result in a considerable
amount of the enterprise’s intellectual capital
being wasted. The cost of using various isolated
systems to collect data for modern knowledge-management-systems
(statistics, data mining, reporting,
exception handling, etcetera) is simply too high. So,
much knowledge that could be extracted from the
data collected remains untapped.
In the industry, there are three different approaches
to addressing this root problem. The fi rst — and
actually no real solution — is the optimization of the
existing hybrid system by adapting the existing processes
and systems. It goes without saying that such
an approach only brings selective and slight improvements.
The second is the introduction of electronic
documentation systems (often described as electronic
lab notebooks) that show the paper data in electronic
format. While the introduction of such a system
brings certain benefi ts for quality and compliance
purposes, the real problem is simply transferred from
paper to an electronic format (“paper on glass”) and
the hoped-for gains in effi ciency are only very small.
And the practicality of introducing electronic documentation
into the laboratory (using tablet-PCs or
other mobile devices) is highly questionable. The third
Acronyms
ELN Electronic Laboratory Notebook � ERP Enterprise resource Planning
� GMP Good Manufacturing Practice � LIMS laboratory information management
system � MES Manufacturing Execution System � PLM Product Lifecycle
Management � SDMS Scientific Data Management System � SOP Standard
Operating Procedures � SWOT Strengths, Weaknesses, Opportunities and Threats
approach, which we discuss in more detail below, is
the optimization and simultaneous electronic support
of the actual laboratory processes — the introduction
of the paperless lab.
THE WAY TO A PAPERLESS LABORATORY
Since introducing a paperless laboratory involves
more than simply implementing another IT application,
the procedure model we use here takes into account
other perspectives in order to build a sustainable
overall concept. These perspectives fall into three main
areas — the business needs, the user’s needs and the
technical perspective.
The business point-of-view defi nes the project’s
goals and vision and ensures that the introduction of
the paperless laboratory complements the company’s
overall business objectives. Typical goals for producers
are increasing net cash fl ow, reducing development
time and, thereby, generating additional sales or
reducing warehousing and stock costs to free up more
capital. Naturally, various other goals or combinations
of targets are possible — but what is decisive is that a
quantitative connection can be made between laboratory
activities and business objectives. This is achieved
by defi ning a business-specifi c cause-effect model and
implementing it into a corresponding fi nancial model. 1
That is the only way that you can ensure
that the implementation project meets the
company’s targets and that the cost-benefi t
analysis accounts for all relevant factors.
The user’s point-of-view is the central
element to developing the paperless
laboratory concept. Based on a thorough
process and system analysis, the user’s per-
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Figure 1: Distribution of tasks for a specific laboratory process as a
percentage of work hours. The colors display the categorization in four
categories; the documentation and control categories could be
substantially reduced by the introduction of a paperless laboratory.
Figure 2: Distribution of non-process activities per department as a
percentage of work hours.
spective will be summarized in the form of process descriptions and data streams. As well as the
actual laboratory procedures — such as sample fl ow and processing, supporting processes will
also be mapped (such as apparatus maintenance, reference substance management and reagents)
in actual state. For every process step, information will be collected from any systems used, any
responsibility changes and any data inputting and outputting. Key performance indicators will be
collected from the process analysis for later integration into the fi nancial model. Vital interfaces
with higher-level processes will be analyzed and documented. The analysis process is also the
foundation for the subsequently conducted multi-moment analysis — a methodology that allows
quantitative information to be derived from and for processes.
Multi-moment analysis 2,3 provides statistically sound and accurate information about the use
of resources per process step or sub-step — and for all processes. To collect data, every laboratory
worker is equipped with a mobile device or PDA (confi gured for their particular tasks) that
requires them periodically, but randomly (on average every 20 minutes) to select the task they are
currently performing from a list. The impact of multi-moment analysis on the workfl ow is minimal,
because just a simple click suffi ces — no recording of times or other parameters is required.
Over a typical period of two weeks, suffi cient data is collected to enable highly detailed statistical
analyses to be made on costs, time and clustering for processes, process steps and task categories.
Figures 1–3 show examples of various evaluations from a multi-moment analysis. The multimoment
analysis not only allows processes (independent of whether a new system is introduced
or not) to be optimized where the greatest need or benefi t lies, but also permits the work stages
to be categorized — thereby enabling a quantitative assessment of the potential benefi ts that the
implementation of a paperless lab would bring (Figure 3). That, in turn, provides the foundation
for a fact-based business case and for the comparison of various implementation scenarios and
their economic benefi ts. The qualitative process description (together with the key performance
indicators and quantitative statements from the multi-moment analysis) thus provides the crucial
information for the paperless laboratory concept development.
Taking the technological (i.e. IT and equipment) point-of-view — and looking at the existing
infrastructure, company standards and long-term strategy — enables a comprehensive concept
to be developed for the automation of the laboratory data-fl ow process. Only then will such a
concept be in line with the company’s commercial targets.
To develop the paperless lab concept — as well as considering the three perspectives outlined
above — you also need a set of principles that allow for a defi nition of process targets based on
the process description of the actual-state processes. The key principle and the vision of the paperless
lab is the self-documenting process — a process that produces GxP-compliant documentation
and eliminates unnecessary tasks from the workfl ow. That naturally means that manual
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ELN
data collection and transfer are eliminated
wherever possible by interfacing to and from
devices and systems — and where that is not
feasible, by using barcodes for fast, error-free
data collection. That also means that redundant
or fragmented data is eliminated, that the
“single-source-of-truth” principle is implemented
and that data is available to every authorized
user in real time. That, in turn, leads
to improved processes, faster decision making
and better teamwork.
The application of these principles to the
actual-state processes enables target-processes
to be defi ned and functional requirements to be
established. As part of the paperless lab concept,
the delta between the current functionality and
the required functionality will be generated in
the gap analysis. This is the only way the fi lling
of such gaps may be conceptually approached — naturally
always considering the underlying business targets.
Possible scenarios also include the modifi cation
of existing IT systems by adapting existing applications
to close functional gaps and multiple scenarios
to close the remaining gaps with other applications.
Once, the only kind of application specifi cally aimed
at laboratory use was a laboratory information
management system (LIMS). However, today there
are many types of applications providing overlapping
functionality. For example, electronic laboratory
notebooks (ELN), sometimes for quality control
referred to as laboratory execution systems or LES
(derived from manufacturing execution systems or
MES); archiving or raw-data management systems
(scientifi c data management system or SDMS);
specialized applications for device and system
Figure 3: Aggregate values for all process and non-process activities for
five different categories per department and as a total amount. The
documentation and control categories show the potential of the
introduction of a paperless laboratory.
integration, increasingly also software that was not
originally laboratory-specifi c, such as product-lifecycle-management
(PLM) systems or ERP systems.
Some software fi rms also offer combinations of the
above-named applications, and there is generally a
trend toward an extension and overlapping of functions
or convergence of applications.
There is no quick answer as to which application
combination is the best for a company. But, by using
SWOT analysis (strengths, weaknesses, opportunities
and threats) to compare the various possible combinations
— naturally accounting for the overall business
targets and not just the needs of the laboratory — the
selection can be reduced to one or two scenarios.
The next step is to select suitable products to fi t the
desired application combination for the developed
scenario. With a sound concept, defi ned target pro-
cesses and their functional requirements, that
is a relatively easy undertaking. As well as the
functional considerations, it is also necessary
to consider the complexity of the IT landscape
and soft factors, such as the readiness of the
software suppliers to cooperate.
Before making any fi nal selection — and to
clear up any technical issues and to get prospective
users involved at an early stage — it
is recommended piloting the whole solution in
small, well-defi ned stages. Such a pilot scheme
— which costs little in terms of money and
risk — should cover as many areas of the paperless
laboratory as possible and helps fi netune
the fi nal implementation planning. The
implementation of the fi nal solution is made
in accordance with widely accepted standards,
such as GAMP. 4 Because the pharmaceutical
industry is so highly regulated, the whole system
must be validated to meet strict requirements. 5,6 The
work invested in the procedure model (e.g. process
analysis, concept development, setting target
processes and piloting) pays off here, contributing
toward the necessary documentation. It should not
be forgotten at this point that the paperless laboratory
is not just the introduction of a system, but is
also — above all else — process re-engineering. It is,
therefore, necessary to support the new optimized
process landscape with all necessary standard operating
procedures (SOPs) and guidelines to maximize
the benefi ts of the paperless laboratory.
FASTER, MORE PRECISE AND MORE ECONOMIC
Because of its integrated and process-oriented
approach, the benefi ts of the paperless laboratory
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compared to using a specifi c application (such as an ELN) are several factors higher.
The automation of the data fl ow and the continued elimination of documenting and
related control activities signifi cantly boost effi ciency for laboratory staff and management.
Already through these effects alone, effi ciency gains of 20 to 30 percent are
feasible (depending on a company’s situation).
Additionally, the virtual elimination of manual tasks substantially reduces processing
times and quality risk. System-specifi c automatic checks ensure compliance and data
consistency and reduce control activities to atypical results (“review by exception”),
thereby accelerating processes and improving resource allocation. Since automatic documentation
also automatically generates numerous process-relevant parameters — such
as throughput times for certain tasks, equipment utilization or sample logistics — there
is an excellent source of data for laboratory management. The paperless laboratory
delivers key performance indicators for its own continual improvement, free-of-charge
— and enables the comparison of organizational units using high-quality data. And
the availability of real-time data benefi ts other areas outside the laboratory — such as
simplifying inter-departmental cooperation, supporting knowledge management and
improving follow-up processes. From the users’ point of view, the paperless lab substantially
simplifi es the workfl ow and reduces the number of systems implemented. It also
supports user-specifi c portals and sharpens focus on what is important.
It is clear that the sum of the paperless lab’s benefi ts is enormous. As with all investment
projects of this size, after implementation, evidence should be presented to show
that the estimated business case and the reality correspond. This can be done at any
time with the help of multi-moment analysis, which can also be used to quantify the
impact of any process change on the workfl ow.
REFERENCES
1. Ritter J. Reducing Cost by Automating Laboratory Workflow. G.I.T. Laboratory Journal. 2009;13(7
– 8):32 – 34.
2. Haller-Wedel E. Das Multimomentverfahrenin Theorie und Praxis. Munich (Germany): Carl Hanser
Verlag; 1969.
3. Simons B. Das Multimomentzeitverfahren, Grundlagen und Anwendung. Kologne (Germany):
Verlag TÜV Rheinland GmbH; 1987.
4. ISPE: GAMP 5, a risk-based approach for GxP compliant computer systems; 2008.
5. Food and Drug Administration: 21 CFR Part 11.
6. EU-GMP Annex 11.
Ulf Fuchslueger is the owner and Andreas Schild is a senior IT consultant at Vialis
AG, Liestal, Switzerland. They may be reached at editor@Scientifi cComputing.com.
April 2012