Importance of the Topic
Cloud-native electronic lab notebooks (ELNs) are critical tools for modern R&D teams in pharmaceutical and biotechnology fields. By centralizing data capture, analysis, and sharing, they help researchers manage the growing volume of experimental results and accelerate decision making across organizational and geographic boundaries.
Study Objectives and Overview
This whitepaper examines five core benefits of adopting a cloud-based ELN delivered as a software-as-a-service platform. It aims to demonstrate how such systems improve collaboration, connectivity, performance at scale, security, and total cost of ownership for both individual scientists and enterprise stakeholders.
Methodology
The authors review common industry challenges in data handling and compare on-premise ELN architectures with cloud-native, microservice-based solutions. They analyze integration patterns using RESTful APIs and discuss real-world deployment considerations such as system uptime, upgrade cycles, and disaster recovery.
Main Results and Discussion
Key findings include:
- Improved Collaboration: A shared cloud ELN environment allows internal and external teams to link experiments, add comments, and control access to sensitive data in real time.
- Enhanced Connectivity: RESTful API integrations connect ELNs with registration systems, LIMS, instrument data streams, and external chemical and biological databases.
- Performance at Scale: A microservice architecture coupled with modern NoSQL indexing delivers sub-second structure searches across tens of millions of molecules.
- Robust Security: Automatic data encryption, geo-redundant backups, and vendor-managed disaster recovery protect critical research information.
- Lower Total Cost of Ownership: Subscription-based licensing and vendor-handled maintenance eliminate the need for extensive in-house IT resources and ensure predictable operational costs.
Benefits and Practical Applications
Cloud ELNs accelerate digital transformation by streamlining project setup, enabling remote data entry from any internet-connected device, and supporting social media-style notifications. They reduce administrative burden on IT teams and foster interdisciplinary teamwork by providing a single, searchable data repository.
Future Trends and Opportunities
Emerging developments include deeper integration with machine learning pipelines, expanded support for real-time instrument connectivity, and federated collaboration networks that allow secure data sharing across companies. Adoption of semantic data models and advanced analytics will further enhance decision support and predictive insights in R&D.
Conclusion
Implementing a cloud-native ELN platform delivers immediate and long-term advantages in collaboration, data management, and cost efficiency. As research becomes more distributed and data-driven, cloud ELNs provide the scalable, secure foundation needed to accelerate innovation and maintain competitive edge.
References
- Wuchty S, Jones BF, Uzzi B. The increasing dominance of teams in production of knowledge. Science. 2007;316(5827):1036–1039.
- Weeks WB, Wallace AE, Kimberly BC. Changes in authorship patterns in prestigious US medical journals. Soc Sci Med. 2004;59(9):1949–1954.
- Microsoft MSDN. Microservice architecture. https://msdn.microsoft.com/en-us/magazine/mt595752. Accessed 2018.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
WHITE
PAPER
Five Benefits of a Cloud ELN
Introduction
Recent trends in the pharmaceutical and biotechnology industries
have influenced to the evolution of electronic lab notebooks (ELN).
Trends including IT budget allocations and an acceleration of
outsourcing efforts have resulted in data collaboration beyond
institutional boundaries. In addition, the efficient collection and
security of ever growing volumes of data is more essential than
ever given the realization that “Big Data” significantly improves
the speed and outcomes of clinical development.
The implementation of an ELN has a transformative effect on the
way research is conducted. Beyond ensuring that the needs of
scientists are met with capabilities specialized for their discipline,
the business needs to examine factors such as streamlining
implementation and system costs. R&D organizations that adopt
a cloud ELN can take advantage of immediate and long-term
benefits. Cloud-native ELNs delivered as SaaS (software as a
service) platforms enable scientists of all disciplines to easily
document and find their work, collaborate within and across
organizations, as well as enable IT to take advantage of more
efficient, cost effective storage and performance with automatic
updates and connectivity to other informatics platforms. In
addition to the five core benefits cited below, cloud ELNs can be
deployed quickly (environments can literally be set up in minutes),
and have high adoption rates and a lower learning curve because
of their browser-based, modern user experiences. This whitepaper
will cover a blueprint to identify and expand on these benefits
that impact both R&D organizations and individual users the most.
Benefit 1 – Improved Collaboration
Scientific collaboration is more strikingly prevalent today than
decades ago.1 The trend in many areas of research is toward
catalyzing collaborative efforts that bring together researchers with
diverse scientific backgrounds. These alternate perspectives help
address perplexing questions and solve complex problems that
benefit from an interdisciplinary or multidisciplinary approach.2
Collaboration is central in your organization and can occur
internally as well as with external commercial partners or
academical institutes. The most important aspect of any
collaboration is the value recognized upon the sharing of data,
the fuel that powers your research. A siloed, disconnected
informatics environment creates challenges in project
management, reporting, and scientific data exchange that
must be addressed if the team is to collaborate effectively
and achieve business goals.
In absence of an ELN as a central data repository, research data
and interpretations are shared in a non-confidential way- often
via email. Using an ELN to facilitate the sharing of data is more
efficient and secure, as a consortium of collaborators can define
who has access to which data while the data continues to be
stored in a secure environment. Collaboration internal to an R&D
organization may be as simple as being able to link experiments
or allowing multiple people to contribute to or comment on
2
the same work. Collaboration can also be more comprehensive.
For example, you may require an ELN to facilitate how projects
are spun up and down, how external partners access project-
related reports and documents, and how they communicate
and share experimental data. It is imperative to define how to
manage different types of data and data formats such as
chemical structure and quality data, calculated and measured
physicochemical properties, biological assay data and pre-clinical
data describing the characteristics of active pharmaceutical
ingredients across the partner landscape. In addition, there is
the consideration of how to distribute and archive the data
among partners when a project ends. Lastly, and arguably
most important, how the IP is managed throughout the duration
of the collaboration must be considered from the start. The
immense challenge of data management and technology
exchange becomes most apparent when one considers that a
typical external collaboration can generate tens of thousands
of data points throughout its duration.
With these challenges in mind, R&D organizations with many
partnerships are turning to cloud-native collaboration workspaces
that are accessible from anywhere with an internet connection and
provide a level of business agility and security that is not available
with server-based, on-premise ELNs.
Benefit 2 - Connectivity
ELNs are the heart of scientific data documentation, processing,
and compliance. At their simplest, they facilitate the capture of
data and documentation of experiments. At their best, they
assist the scientist and the business at every step of data
generation and analysis along the R&D value chain and facilitate
collaboration with external partners. ELNs that are easily accessible
and designed to be the central integration point in the informatics
electronic lab environment will provide the most value.
As previously mentioned, research is ever more distributed,
and scientists need to be able to access their information from
many different locations at any time of day and potentially from
different machines. Access to a cloud ELN is only limited by
internet connection. As there is no application installed on the
machine itself, scientists can review and enter data from any
internet connected device. Cloud ELNs effectively allow scientists
to work from anywhere and the heightened connectivity will
improve efficiency and productivity.
In addition to better connectivity to the ELN platform itself, there
is also the benefit of improved connectivity to other informatics
systems. Scientists, regardless of their discipline, use many
applications and tools essential to executing their daily work,
and often the data generated from these other tools need to be
incorporated into their experiments. Not only is the enterprise
software landscape of internal systems strikingly different from
one organization to the next, but there are also external systems
to consider. Internal systems that the ELN may be required to
integrate with can include, but is not limited to, chemical and
biological registration and inventory applications, and laboratory
information management systems (LIMS). In addition, valuable
external databases exist with information on available chemicals,
reaction planning, safety data, and sequence information etc.
There is also the possible need to connect to digitized equipment
including balances, pH meters, bioreactors or analytical instruments.
Figure 1. Intuitive collaboration in Signals Notebook: add comments, tag colleagues and use hashtags to link to relevant experiments.
3
Figure 2. Integration of Signals Notebook with ChemACX gives scientists immediate access to pertinent data around commercial availability of materials.
Cloud based ELNs are commonly built off RESTful API’s which
facilitate data trafficking between disparate systems. Using
such modern standards for API development, the programmatic
burden of integrating systems is significantly reduced. Integrations
can access the APIs of an ELN by an external application to
precipitate events such as automatically writing instrument data
to an experiment. Alternatively, a service within the ELN can
access a third-party API to access stored data about a sample
from a LIMS or to check the safety and regulatory profile of a
reagent from an external database. Whichever integrations are
achieved, the greater agility offered by such modern applications
allows the ELN to expand to provide the core of a connected
electronic lab environment.
Cloud ELNs have enhanced connectivity that is inherent in the
way they are designed and provisioned. There is no “one size
fits all” ELN, therefore integration with other systems must be
not only possible, but also streamlined.
Benefit 3 - Performance at Scale
Whether you’re a scientist, the head of IT, or an investor, you
can benefit from the exceptional performance of enterprise
software. An ELN user must be able to upload all different types
data, quickly find historical data, and have access to the most
modern, up-to-date functionality in a timely manner. The
business supporting the ELN will be concerned with ease of
implementation, accessibility or uptime, and scalability. Cloud
ELNs fulfill all these needs as they are delivered in a matter of
minutes, elastically scalable, updated automatically, and have
guaranteed uptime.
A well-designed cloud-native ELN will be built on modern
technology that on-premise ELNs cannot take advantage of. The
architecture of traditional on-premise ELNs are either a single
application process or a multi-tiered system of database, web
server, and application tiers. A cloud-hosted solution of a
traditional ELN is the same tiered architecture, just installed in
the cloud. Both have upper performance limits and require
additional cost, support, or services from IT to analyze the
system and optimize it in order to scale. In contrast, a well-
designed cloud-native ELN is built with a microservice based
architecture, meaning each dedicated component can operate
independently. If one component temporarily fails, others remain
unaffected and the system is still usable. Microservices are
resilient and self-healing. They are designed to auto recover from
adverse events that may impact the database, application servers,
or network services. This architectural approach has many other
benefits, including immediate scalability during periods of rapid
growth, and unrivaled search performance through hundreds of
millions of entries thanks to modern storage and indexing
technologies. This is simply not possible with an on-premise or
cloud-hosted ELN built with traditional architecture.
4
Figure 3. Benefits of a microservice architecture: services operate independently and utilization of best-of-breed for each type of technology.3
Cloud ELNs delivered as a SaaS solution also have the advantage
of elimination of “environmental” issues as well as a continuous
release cycle that allows the pushing of new functionality
frequently and, depending on the deployment, automatically. A
well designed SaaS offering will allow internal administrators to
configure their own unique workflows that are not impacted by
these updates. Cloud ELNs also have guaranteed uptime, as the
entire system is in a controlled environment and is not at the
mercy of the many variables on-premise systems are.
Benefit 4 - Security
Protecting and securing your data is paramount. Often at larger
institutions, entire teams are devoted to doing just that. Of
course, this includes the data you generate in-house at your
organization, but 25% of Pharma and Biotech work is
now outsourced. Data needs to flow into and out of your
organization every day and the right people need to see the
right information on-demand.
As data storage in the cloud is elastically scalable, cloud ELNs
can be automatically backed up daily and those backups can be
stored for an extended period. Organizations that implement a
well-designed cloud ELN will benefit from business continuity
and a disaster recovery plan that has been vetted by a large
number of customers, as opposed to an on-premise system that
may have less scrutiny.
Not only are there multiple copies of your data at any given
time at one data center, but cloud ELNs also provide the benefit
of data redundancy. Current best practice for cloud ELN
infrastructure is to have it deployed and maintained in at least
two physical and geographic locations to mirror your data and
guarantee maximum availability if hardware or network issues
were to occur. In the incredibly unlikely event that a disaster
occurs at one data center, the other can continue delivering
the ELN service without interruption or loss of data.
Cloud ELNs often have several deployment models that can
include multi-tenant and private cloud environments. A cloud
vendor should ensure security infrastructure is equally robust,
regardless of deployment model, though the perception that
private cloud offerings have better security often leads
organizations to that option. Regardless of the deployment
model, data is always encrypted in transit to and from the cloud
as well as when it is “at rest” in the system. With any cloud
platform, the vendor should ensure access to the system is based
on a well-defined role based policy, such that designated people
only have access to particular subsystems and conduct regular
proactive security assessments at the network, host, and
application level, remediating all vulnerabilities in a timely fashion.
5
Benefit 5 – Total Cost of Ownership
In the late 1980s, Gartner popularized the term “total
cost of ownership” (TCO) to define the long-term cost of
maintenance in addition to the upfront capital investment
in enterprise technology. It is imperative to consider what
total cost of ownership means when selecting an electronic
laboratory notebook for your R&D organization and how it
could influence your decision. The component most
people are typically concerned about is the initial capital
investment required when selecting and implementing a
solution. Let’s say your organization has reviewed multiple
vendors for their functional capabilities and the scientists
are satisfied with the technical aspects. Next, you begin to
evaluate the costs.
The complexity of the underlying IT infrastructure and
maintenance for a cloud ELN as a service, is all handled by
your cloud ELN vendor. Neither the end users or your
organization’s IT department must worry about hardware
maintenance, upgrades to the application, or what versions
of underlying databases are compatible etc. A cloud ELN is
managed by the vendor experts who developed and
understand the application inside and out. They are familiar
with all operations of the application and can make changes
to the cloud deployment to ensure maximum levels of
performance and robustness. Cloud ELNs are quickly scalable
and can grow with your organization as capacity needs
increase. With most traditional software, you are not
guaranteed on how well it will perform when installed on
your local infrastructure given all the variables at play
(database, servers, network, end user machines, etc.). With
a cloud ELN you are, and most vendors will guarantee that
your application will be up and available 99% of the time.
As mentioned previously, cloud ELNs eliminate the cost for
data backup, redundancy and recovery because these costly
and timely services are provided by the ELN vendor, but
they also eliminate sunken opportunity cost. Cloud ELNs
can be updated more frequently because everyone is on
the same source code and vendors don’t have to release
unique fixes for highly customized ELNs. These more
frequent updates ensure that the functionality continues
to be improved and modernized. Cloud ELNs also provide
the benefit of predictable costs for both licenses and
administration. Licenses are typically sold as yearly
subscriptions, so during periods of rapid growth you
will have a clear idea of what your costs will be.
Talk about performance! Sub-second structure
searching in PerkinElmer’s Signals™ Notebook
Chemical substructure and similarity searching is the
cornerstone of most cheminformatics systems and a
critical feature in electronic lab notebooks. However,
as the scale of cheminformatics systems has grown,
scientists are often frustrated with the performance of
their chemical queries. Mature ELNs in production for
well over a decade at global pharmaceutical and chemical
companies currently store tens of millions of chemical
structures and reactions.
PerkinElmer has been the industry leader in adopting
modern NoSQL technologies to build the next generation
cloud-native ELN and scientific computing platform, Signals™
Notebook. Chemical structure searching in Signals™
Notebook is facilitated by PerkinElmer’s ChemSearch NoSQL
chemistry cartridge, the first chemical search cartridge
compatible with scalable, NoSQL systems. ChemSearch
offers exact, substructure, and similarity search capabilities
with performance at scale. This new search engine is based
on the open source and battle-tested Elastic Search
technology- the search engine used by most online
shopping, airline, hotel reservation, and social media sites.
Elastic Search is an index, not a database, that consumes
documents and other electronic content, parses it, and
organizes it in a way that makes it easier to find.
PerkinElmer instructed Elastic Search how to perform
chemical searching and now ChemSearch allows Signals
Notebook to provide sub-second response time on
databases with hundreds of millions of molecules and
reactions. Indexing systems are also very efficient at
assigning relevance to results, as it is not enough to return
results quickly. The results must be valid, and the most
important ones should be returned first. The second step
in chemical searching is to evaluate which of the screened
molecules is really a valid substructure of the query
molecule. This is a complex and computationally expensive
process akin to a pass/fail relevance test. Matching
molecules are assigned a high relevance, failing ones are
dropped from the list of results. The good news again, is
that Elastic Search is particularly well suited to scoring the
results via a relevance function. It efficiently parallelizes the
scoring process by allowing hundreds or even thousands
of small computers to each handle a fraction of the results
to score. The net result is a system that is vastly more
scalable and performant than older SQL Cartridges found
in many on-premise ELNs.
6
Conclusion
A successful ELN implementation must meet the criteria of and
provide benefits to both the technical and business sponsors.
The ELN must enable scientists to quickly and easily narrate their
experiments, enter and analyze data, and more importantly,
share and collaborate on that data to move projects forward.
Project managers should be able to track experiment and project
progress and gauge efficiency. Investing in a cloud ELN will kick-
start your organization's digital transformation, lower the barrier
for cross institutional collaboration, and increase R&D efficiency.
PerkinElmer Signals™ Notebook is the next generation cloud
ELN and scientific collaboration platform for today’s scientists.
One of the most intuitive ELNs on the market, it looks and feels
like modern consumer apps used every day. Signals Notebook
employs a cloud-based micro-service architecture with advanced
data lake storage technologies for document storage and indexing.
PerkinElmer has architected Signals Notebook to grow with
organization’s needs and is quickly scalable. Collaboration is
supported with social media-like commenting and notifications
and creating contextual relationships between experiments.
Signals Notebook is a SaaS ELN and as such PerkinElmer owns
all the system maintenance and updates, which deliver new
functionality and bug fixes every 3-6 weeks.
Signals Notebook is the intuitive, searchable, scalable,
and secure platform designed to increase productivity,
enhance collaboration, and reduce risk. Request your
30-day free trial today and get started using it
tomorrow to see for yourself.
ChemDraw, the world’s leading chemical drawing
software, is embedded in Signals Notebook for
seamless support of synthetic chemistry workflows
and reaction planning.
More About Signals Notebook, Cloud ELN
Quickly document your procedures and protocols by
using quick keys to insert auto-text snippets and lists,
as well as materials or reaction properties linked to the
stoichiometry grid.
Signals Notebook’s intuitive user experience enables rapid user adoption – get your organization up and running in no time with an ELN
that looks and feels like modern consumer applications.
For a complete listing of our global offices, visit www.perkinelmer.com/ContactUs
Copyright ©2018, PerkinElmer, Inc. All rights reserved. PerkinElmer® is a registered trademark of PerkinElmer, Inc. All other trademarks are the property of their respective owners.
014419_01 PKI
PerkinElmer, Inc.
940 Winter Street
Waltham, MA 02451 USA
P: (800) 762-4000 or
(+1) 203-925-4602
www.perkinelmer.com
References
1. Wutchy, S., Jones, B. F., & Uzzi, B. (2007, May 18). The increasing dominance of teams in production of knowledge. Science,
1036-1039.
2. Weeks, W. B., Wallace, A. E., & Kimberly, B. C. (2004, Nov). Changes in authorship patterns in prestigious US medical journals.
Social science & medicine, 1949-1954.
3. Image adapted from https://msdn.microsoft.com/en-us/magazine/mt595752
Signals Notebook has many capabilities to facilitate
collaboration within and across organizations.
Teamwork is instantaneous with social media like
commenting, the ability to link multiple experiments
and notifications delivered in app or via email.
Searching has never been faster or easier. With
syntax free text and property search and proprietary
ChemSearch functionality for structure searching,
Signals Notebook delivers the exceptional search
experience scientists can’t live without.
