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Data management that speeds—rather than impedes—advanced DNA sequencing applications
December 2011
SHARING OPTIONS:
In the post-Human Genome Project era, molecular diagnostics
and therapeutics, which promise to significantly improve patient outcomes by
linking genetic diagnoses to targeted therapies, have been hailed as the next
great advancement in human healthcare. Gene sequencing technology is
widely acknowledged
as the primary driver for these advances, powering both the research needed to
understand and leverage individual genome maps and
the clinical testing that
will enable physicians to diagnose and treat disease based on a patient's
genomic profile.
In this brave new world, it's hard to conceive that
something as mundane as the management of sequencing data could determine which
technologies succeed or fail. Yet today, sample management is the primary
bottleneck to sequencing workflows. In May 2010, a survey of laboratory
directors conducted by J.P. Morgan cited data
management as one of the biggest
hurdles to expanding next-generation sequencing (NGS). And in January 2011, a
survey by William Blair & Co. cited data management
software support as a
top priority in choosing an NGS platform, trailing only instrument throughput
and reagent cost.
The ability to positively identify samples and maintain data
integrity throughout the sequencing workflow will only
become more vital as
research labs aim to maximize throughput and extend research capabilities into
clinical applications. If information management
systems are to support the
continued evolution of sequencing and its application to medical diagnostics
and therapeutics, they must support the
de-facto
standards and best practices associated with using sequencers—the technology
without which there would be no evolution.
But sequencing isn't just about machines. Instruments
couldn't run and work wouldn't get done without
people. Informatics, in the form
of laboratory information management software, can help improve lab efficiency,
ensure that labs deliver better
quality results to customers faster and enforce
pertinent clinical and U.S. Food and Drug Administration (FDA) regulatory
requirements such as CLIA, CAP/ISO 15189 and 21 CFR Part 11. But informatics
can also inhibit
lab staff by forcing them into unnatural or illogical ways of
working.
Informatics for modern
sequencing labs must therefore
interact effectively with three very different constituents: the instruments
that perform the sequencing, the lab
technicians who run the instruments and
the lab directors who are ultimately responsible for the output and quality of
the lab's work.
Let sequencers lead
the way
Sequencers are the core technology driving next-generation
genomics research. The three major manufacturers of sequencing instrumentation
(Illumina, Life Technologies and Roche) are all developing instruments capable
of producing hundreds of gigabases of
sequencing data per run. It's therefore
imperative that data management software keep pace. Software can effectively
integrate with sequencers in four
ways.
1) Conform
to the wet-lab protocols provided by a vendor. The continued
raising of the
throughput bar has led instrument manufacturers to standardize the wet-lab
processes that will work best with their system into various
sample-prep kits.
Preconfigured informatics workflows that map to these vendor-specified
procedures enable labs to thoroughly track sample-preparation
activities.
2) Ensure
that samples are properly prepared to run on designated
instruments.
Instrumentation vendors have developed specific standards for the media onto
which libraries are loaded for sequencing. Preconfigured
informatics workflows
can speed sample preparation by automating routine tasks such as tracking and
loading concentrations, calculating dilution of
libraries to normalized
concentrations and tracking reagents.
3) Demystify
demultiplexing. Multiplexing, or library pooling, can increase sample
throughput. But two things limit the technique's utility: Scientists must be
able to rapidly organize prepared libraries or samples that can be effectively
pooled together, while also tracking what happens to individual samples
in a
pool before, during and after multiplexing. Preconfigured informatics workflows
can track a range of information associated with pending samples
that
technicians can search to build pooled libraries. Preconfigured informatics
workflows can also support the assignment of adapters, indexes or DNA
barcodes
to individual samples in a pool to keep them distinct and trackable when
multiplexed.
4)
Run,
monitor and track sequencing runs. Informatics can automate and track a variety
of tasks to make sequencing more efficient,
such as matching items sent to
sequencers with samples in the data management systems; generating necessary
files (such as run definition files and
sample sheets) to communicate with the
sequencer before and after sequencing; monitoring run status directly across
multiple instruments; capturing key
run parameter files and primary analysis
metrics; and automating demultiplexing and conversion of raw data files from
the sequencer into FASTQ format
for analysis.
Help lab techs work
better and
faster
Laboratory technicians, who interact most closely with
instruments on a daily basis, will appreciate tight integration between
instrumentation and informatics—yet such integration isn't all that
technicians
require from modern sequencing data management systems. Sequencing work is fast
paced and dynamic—labs can generate hundreds of gigabases a
day, and workflows
may change monthly to accommodate new protocols and instrumentation. In this
environment, labs succeed by pushing the boundaries of
innovation—and they
cannot afford to be constrained in their vision by the software they implement
to manage data and workflows.
Lab technicians are most interested in ways to optimize
their personal and team efficiency while minimizing the
amount of time they
need to spend on routine, repetitive tasks. Most technicians want to spend as
little time as possible recording information;
instead of telling a system
they've done something, they'd prefer the system anticipate the task and supply
as much information as possible to
complement work they plan to do.
Technicians also need fast and easy ways to track their work
and
the work going on around them. Dashboard views offer an ideal way for
technicians to review experiments in progress, guide samples effectively
through
complicated workflows and collect and organize samples into multiplexed
experiments to achieve greater efficiency. No matter how the interface is
designed, technicians require uncluttered and streamlined access to only the
information they need to initiate experiments, find samples on which to
work,
monitor work in progress and stay informed about other work occurring in their
labs.
Empower lab directors
to improve lab efficiency
The
overall operation and administration of labs falls on
lab directors. This means that unlike lab technicians, who need ways to
streamline day-to-day
tasks associated with preparing and managing samples and
running projects, lab directors require high-level views that they can use to
track lab
progress and verify that work is occurring and being recorded promptly,
accurately, proficiently and in compliance with applicable regulatory
requirements for clinical research and biopharmaceutical applications.
Most lab directors
rightly put their primary emphasis on
delivering high-quality results to clients and collaborators quickly. Data
management software can centralize
up-to-date information on runs so that lab
directors can compare sequencing performance and trend accumulated data over
time. When data from multiple
runs are archived and searchable, labs can make better,
more informed decisions about which samples to rework, whether to request more
samples for
further experimentation or how much time to spend on further
analysis.
Regulations will become
more of a factor for labs that
undertake clinical applications for sequencing. Three regulatory requirements
potentially impact clinical genomics labs
in the United States:
The data volumes
produced by modern sequencing applications
require new approaches to data management that center on the workflows
prescribed by sequencers and the
specific needs of two different types of
users: lab technicians and lab directors. From my perspective, how labs choose
to manage their data may very
well determine which have the most success in
applying DNA sequencing to the development of advanced molecular diagnostics
and therapeutics.
Bruce Pharr is vice
president of products and marketing at GenoLogics Life Sciences Software. He
has more than 25 years
of experience in technology product design, management
and marketing, including corporate and consulting roles with life science
R&D hardware and
software, pharmaceutical and medical device
companies. He holds a B.S. degree in
economics and business administration, and he has completed
executive programs
in strategic marketing management and marketing strategy for technology-based
companies at the Stanford Graduate School of Business.
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