ELN Buyer's Guide

ELN Buyer's Guide The Future of Data-Driven R&D

www.dotmatics.com

Contents Introduction

1

Why Move to an ELN

2

A History of the ELN

2

Dotmatics ELN - A New Breed

3

The Benefits of Dotmatics ELN: Breadth and Depth

4

The Ultimate ELN Checklist

8

References

9

Introduction With the evolution of research, most scientists have moved away from paper laboratory notebooks as they’ve realized the importance of digitally recording experimental information.

Unfortunately, some are still working with cobbled together systems, utilizing a combination of spreadsheets, shared files, and email to capture and share information digitally. These disconnected approaches aren’t ideal because they prevent scientists from sharing real-time results and collaborating for improved decision making. To address those shortcomings, most scientists have moved to electronic lab notebooks, more commonly known as ELNs. With an ELN, scientists not only have quick access to their own research for years to come, but they can also easily share their findings with other researchers in their organization. An ELN can help teams evolve from a ‘my data’ approach to an ‘our data’ approach. By enabling collaboration, an ELN can help scientists build on each other’s knowledge and avoid repeating unsuccessful work.

This eBook reviews the history of ELNs and highlights how collaborative cloud-based ELNs like Dotmatics ELN support today’s crossdiscipline research workflows. Be sure to check out the Ultimate ELN Checklist at the end to help you prioritize the features that are most important to your organization.

As we embrace the team approach needed in modern multidisciplinary scientific research, let’s ensure we make data truly accessible by all scientists wherever they are located by using a cloud based electronic lab notebook (ELN).

2 Why Move to an ELN An ELN lets scientists capture, track, and report their laboratory work. All experiments, results, and associated data can be securely shared across an organization, saving time and facilitating collaboration. This is essential in today’s R&D environments, where efficient crossteam collaboration is more important than ever.

R&D organizations, whether developing new drugs or innovating tomorrow’s sustainable materials, recognize that scientific advances rely on data from many scientific disciplines. As such, a key part of scientific innovation is the free flow of data. Organizations must choose a flexible and collaborative solution like Dotmatics ELN, which supports diverse workflows and makes it easy for researchers to share data across disciplines and sites.

A History of the ELN It’s been almost 30 years since the American Chemical Society devoted an entire day to discussion on the attributes of ELNs; these discussions were mainly driven by chemists who wanted to document and store their results electronically. Early efforts focused on data capture for intellectual property (IP) purposes, rather than on data retrieval. When ELNs first gained traction, drug discovery was dominated by small molecule therapeutics, and so early ELNs were geared towards supporting medicinal and analytical chemistry workflows, leaving biologists with traditional paper laboratory notebooks.

By 2007, 20% of Life Sciences organizations were reportedly1 adopting ELNs, and biologists increasingly began moving from paper notebooks to ELNs. These allowed biologists to record in free text and cut and paste experimental image results, but something was still missing–search and aggregation. This meant that data remained in inaccessible database “silos,” perpetuating the limitations of paper notebooks.

Today, drug discovery is no longer dominated by small molecules2. We increasingly see novel therapeutic types, often “chemically-modified

therapeutics” (CMTs), which are biologicallybased molecules containing some form of artificial chemical modification3. Pharmaceutical companies are evolving into biopharma organizations. As part of the transition, they are revisiting their legacy chemistry-based ELNs to gauge whether they are flexible enough to support both biology and chemistry workflows, while also using FAIR (Findable, Accessible, Interoperable, Reusable)4 guiding principles for data management and stewardship. Many biopharma organizations are consolidating separate legacy biology and chemistry ELNs onto a single platform. The combination lets them configure the ELN for any type of research—whether small molecule research, biologics discovery, or assay and process development—while also ensuring data integrity and enabling the free flow of data to drive R&D decisions.

The adoption of ELNs has also spread into other industries, like chemicals and material science R&D. Researchers in these industries have similar expectations for an ELN. They’re looking for a solution that will help them have better insight into their experiments, streamline

3 processes, and support innovation through better decision making. However, their needs are unique because they need a solution that can support complex workflows (which are oftentimes fluid and non-standardized), as well as handle wildly diverse data types, such as flavor or fragrance testing panels or tire road-testing results. While Dotmatics ELN can support this type of research, it is something many other ELNs, especially those that began as focused specialty solutions, are simply unable to support.

For the ELN, the process is the product. The better your R&D groups can track, integrate, and synthesize their processes, the more opportunities they have for innovation. For many organization this means their ELN must also work seamlessly with the other solutions used throughout their make-test-decide innovation cycles. They need a flexible and comprehensive ELN that is part of a bigger picture, not something that only a select group researchers use. This is where Dotmatics ELN stands out.

Because it’s part of a larger research platform, Dotmatics ELN easily serves as an access point to other Dotmatics solutions, including those for instrument-data collection, lab-request management (e.g., assay, catalysis, analysis, ADMET, environmental impact), registration (biological, chemical, materials), inventory management, data visualization, modeling and analytics, artificial intelligence (AI), and machine learning (ML). And because Dotmatics solutions are built on an open data architecture, organizations can also tie in proprietary and thirdparty vendor solutions.

Dotmatics ELN: A New Breed To meet the needs of today’s research workflows, many companies have developed next generation ELNs that aim to be both customizable and collaborative. What this means varies from vendor to vendor. For Dotmatics, it means letting users across the R&D organization quickly access the tools and data they need, customize their view for ease-of-use, and collaborate across scientific domains. Dotmatics ELN can support all users across the make-test-decide innovation cycle, not just those in select research groups. From a data integrity standpoint, Dotmatics ELN can provision the model quality data (MQD) that is needed for the AI and ML approaches that are seen as key to scientific innovation5.

"For the ELN, the process is the product. The better your R&D groups can track, integrate, and synthesize their processes, the more opportunities they have for innovation."

4 The Benefits of Dotmatics ELN: Breadth and Depth ELN options are now plentiful and wide-ranging— from broad solutions with generalized features to discipline-centric products created to support specific workflows. Finding the solution best suited to meet the needs of all stakeholders across your R&D workflow can be a challenge.

This is where a flexible and collaborative solution like Dotmatics ELN shines. Below, we’ve highlighted some of the key benefits of Dotmatics ELN.

Dotmatics ELN is a Central Research Hub Many organizations want their ELN to serve as the hub to all their research activities. Unfortunately, most solutions on the market simply can’t do this, either because they were built to address the needs of specific types of researchers or because they’re so broad they don’t have the features needed to support complex research workflows.

Dotmatics ELN is different. How? On the surface, Dotmatics ELN streamlines cross-discipline workflows by providing all researchers across an organization with quick access to the tools they need to make, test, and evaluate candidates.

Behind the scenes, Dotmatics ELN streamlines dataflows by connecting large amounts of diverse data on a single platform while facilitating the seamless flow of that data not only between teams, but also from one stage of the innovation cycle to the next.

For example, an organization can collect instrument data and annotations generated by scientists making materials and automatically load the data into Dotmatics ELN. The data can then be passed onto other groups who test various candidates, record observations, and input revised data into Dotmatics ELN. Next, Dotmatics ELN can facilitate the transfer of the evolving data into sophisticated data modeling, machine learning, and artificial intelligence tools that help decisionmakers make correlations and gain insight to inform next steps. So, every step of the way, Dotmatics ELN acts as a central hub through which both workflows and dataflows progress.

Dotmatics ELN Facilitates Secure Collaboration Most areas of scientific discovery today rely on collaborative efforts that bring together researchers with diverse scientific backgrounds. This interdisciplinary approach helps solve complex problems that no single domain expert can tackle; it also necessitates seamless sharing of information across internal and external groups to establish a united source of scientific data that helps promote better-informed decision making across the board.

To facilitate collaboration, many ELNs are now accessible via secure, web-based applications.

With this approach, team members can easily access the functionality they need. Some solutions, like Dotmatics ELN, let users customize the interface to streamline their workflows.

But beyond a pretty interface, it’s important to consider what happens with data behind the scenes. Unlike other solutions that keep your data siloed, Dotmatics ELN feeds everything into a unified platform. It captures all data being generated, follows that data through various iterations of analyses by cross-discipline team members, and helps you highlight subtle differences in the dataset along the way.

5 Another key factor in collaboration is security and Dotmatics ELN doesn’t disappoint on this front either. With Dotmatics ELN you can finetune permissions in many ways. For example, you can restrict user’s access to specific parts of the database, enable one-way data upload, limit registration capabilities to certain team members, or assign project/product aliases or codes.

Small to mid-size start-ups, large R&D companies, CROs, and academic institutions alike can benefit by using Dotmatics ELN to efficiently collaborate and quickly access data, regardless of who generated it. Academic and not-for-profit institutions will also value the reputational benefit of verifiable, reproducible scientific results for the purposes of publication, as well as for improving continuity in research groups that have high turnover of students and postdocs.

Dotmatics ELN Helps Protect IP To fully protect IP, an ELN must provide access to complete audit trails and countersigning capabilities. In today’s research environment, this often demands that an ELN have the power to capture electronic records in diverse areas of research, not just a select few. Organizations working across domains turn to Dotmatics ELN because it unites diverse data types and supports the registration of different types of entities, including mixed entities. You can trust Dotmatics ELN to play a key role in protecting your valuable IP.

Dotmatics ELN establishes a single source of truth ensuring that IP is rigorously protected and guaranteeing that all scientists understand each other, even if they speak different scientific languages

6 Dotmatics ELN Provides Global Access Dotmatics ELN Provides Better Insights Not only are data sets getting larger, but scattered teams across the world means data collection is increasingly complex. A collaborative ELN should take both these factors into account. Dotmatics ELN has the capacity to handle different languages, time zones, and work methods, allowing users to share data and work seamlessly with colleagues, wherever they are based. On top of this, it supports the automated and secure collection of vast volumes and varieties of scientific and instrument data in order to provide the data quality that is needed for advanced analytics methods, like machine learning.

Dotmatics ELN Creates a Single Source of Truth Innovative products often arise from crossdisciplinary teams collaborating more closely than ever. For example, novel chemically-modified biologic drugs are emerging thanks to the close collaboration of chemists and biologists.

Flavor and fragrance companies are creating unique mixed-entity, multi-component products developed through the collaborative efforts of diverse research groups.

To collaborate better, these teams need to work from a single source of truth. If data are contained in a disconnected, siloed environment, challenges arise across domains in terms of project management, reporting, and scientific data exchange. When these challenges frequently arise, it reduces the efficiency of collaboration.

Dotmatics ELN can help organizations avoid these challenges by creating a single source of truth.

Dotmatics ELN not only unites diverse data on one platform, but it follows data from team to team and through each iteration of the innovation cycle, handling small changes to the dataset after each round of analysis.

Scientists need to sift through and analyze increasing volumes of data to gain insight and interpret experiment results. For example, researchers participating in drug discovery projects need access to all the latest experimental data, structure data, assay/screening data, inventory data, and analytical data that flows from a variety of sources. Researchers working in chemicals and materials R&D may need access to diverse data from market analysis, field testing, catalysis studies, safety assessment, environmental impact studies, and more.

Dotmatics ELN is unique in its ability seamlessly flow diverse data generated by different groups, lab instruments and CROs into one united system and master data source. And because it’s part of a larger research platform, Dotmatics ELN can readily pass data into supplemental analytics and decision-support applications, positioning scientists to accelerate the research cycle by actively analyzing and collaborating on near realtime data.

Without a solution like Dotmatics ELN to capture and store research data and interpretations, scientists find workarounds, such as insecure file sharing via email; this can result in transcription errors, corrupted files, and other security issues.

Knowledge and information shared in this way leads to fragmented data silos and the volume of files becomes unwieldy when working with experimental data at scale.

7 Dotmatics ELN Boosts Productivity Scientists, irrespective of their discipline, have data coming from many sources and finding ways to efficiently manage their data frees time for exploration and innovation.

For example, many scientists use multiple applications while executing their daily work, and often the data generated from these tools must be incorporated into their experiments. When these data are from instruments in high throughput labs, scientists can easily become overwhelmed with the volume of files and data if they don’t have a means for automated upload and processing.

Additionally, if data are generated by outside partners, that data must also be incorporated into analyses. However, manually incorporating data from external collaborations has productivity costs (up to 2 days per week6) related to data cleaning, validating, and merging. Many

organizations license out data management projects to third-parties. In these cases, entire data packages need to be generated and handed over. Companies working on multiple projects with a variety of partners need to be able to retrieve and export this information in an agile manner.

Finding an ELN that can smoothly collate data coming from different instruments, teams, and collaborators is critical to be competitive. After all, a successful collaboration is one where scientific understanding is deepened with shared data that helps move a project across R&D phases quicker. Dotmatics ELN unites all project and instrument data, providing scientists with access to all their data from a single interface, delivering a seamless workflow, and removing the need to switch between applications. With Dotmatics ELN, rapid search and retrieval from one master data source enables knowledge re-use across teams and sites, increasing R&D productivity.

Dotmatics ELN supports all types of research and is designed to be a central hub for diverse lab data.

Permissions-based roles allow scientists to create and manage experiments across the globe.

The Ultimate ELN Checklist

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This checklist will help you prioritize the factors you’ll need to consider when choosing a collaborative ELN. Once you’ve identified your must-haves, we’d love to chat and see how Dotmatics ELN can address your needs by providing a solution that fully supports cross-team and cross-organization research, seamlessly handles vast volumes and types of data, and positions your R&D organization to make better decisions, faster.

Central Hub on an Open Platform: Streamline both dataflows and workflows by accessing wide-ranging R&D tools from an ELN that serves as a central research hub, offering access to out-of-the box solutions for biology, chemistry, formulations, and data management, as well as the ability to seamlessly integrate in-house or third-party software tools.

Federated Data Searching and Sharing: Knock down data silos with instant access to all of your diverse structured and nonstructured data, irrespective of where it is stored, with scientifically-aware, web-based search and aggregation across all R&D databases, allowing scientists to make better decisions, faster.

Let users interact with this data in the way they need, for example enabling chemists to search and view by structure and biologists by sequences, thus supporting users’ preferences while maintaining a single source of truth.

United Teams and Data: Unite your teams and data with a comprehensive and customizable ELN that has the power and flexibility to handle diverse data types, as well as the security to adjust to the specific needs of diverse research groups, external partners, analysts, and decisionmakers.

Make > Test > Decide: Cover each group in the Make-Test-Decide innovation cycle. Rolebased workflows give scientists a simple user experience with seamless connections between capabilities that capture processes, experiments, entities, and test results.

Real-time Collaborative Research: Attain true real-time research with instant access to the tools you need to obtain data, capture experiments, record results, register entities, log requests, and collaborate —all from one central ELN. Cloud-access means all users have a single point of access to all scientific data and functions across multidisciplinary groups. Scientists, collaborators, and partners can instantly interact with the same data and resources via the cloud, regardless of location and time zone (provided they have proper permissions).

Support for Novel Research: Manage crossdiscipline projects in a single system for improved IP protection, data quality, and cross-team collaboration. Find an ELN that can support the demands of novel research, whether that be handling diverse types of both structured and nonstructured data, supporting the registration of mixed entities or chemically modified biologics, or facilitating complex, nonstandardized experiments, such as those used in chemicals/materials research.

IP Protection: Secure IP with an ELN that provides an audit trail to track changes, electronic-signature capabilities, and secured archive PDFs on completion of experiment.

Lab Data Automation: Increase lab efficiency and data quality with automated data capture, analysis, and operational insights.

Data Visualization for Decision Support: Guide decisions with integrated visualization tools that allow scientists to feed insights back into the ELN, creating an open environment for innovation.

Low Total Cost of Ownership: Reduce total cost of ownership with a SaaS cloud ELN; all underlying IT infrastructure and maintenance is handled by the ELN vendor so end users don’t need to worry about hardware maintenance, upgrades to the application, or database compatibility.

Foundation for Growth: Position for growth with a cloud ELN that scales quickly and can grow with your organization as capacity needs increase, with predictable costs for both licenses and technical support.

Vendor Reliability and Stability: Have peace of mind picking a vendor who has a proven track record of being a strategic partner with long-term financial stability. Experience in implementing collaborative ELNs will give R&D teams the flexibility to evolve and adapt to new science and partner models.

9 References 1. Michael Elliott, Atrium Research. ‘The state of the ELN Market’. Scientific Computing World Magazine issue: DECEMBER 2006/JANUARY 2007 2. Brown, D.G., Wobst, H.J. ‘A decade of FDA-approved drugs (2010–2019): Trends and future directions’. J. Med. Chem. 64, 2312–2338 (2021) 3. LeBeau, A., Humphreys, T. ’Solving Critical Data Challenges for Chemically-modified, Biologically-based Therapeutic Candidates’, International Biopharmaceutical Industry, IBI Vol 4 Issue 2 – Summer 2021 4. Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; et al. (15 March 2016). ‘The FAIR Guiding Principles for scientific data management and stewardship’. Scientific Data. 3: 160018.

5. Savage, N. ‘Tapping into the drug discovery potential of AI’. Nature Biopharmadealmakers May 2021 6. Connelly, J. (retired) Sanofi at Bio-IT World Congress.

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