In “Why You Need an Electronic Laboratory Notebook: Part 1,” we discussed many of the benefits that electronic laboratory notebooks (ELNs) have over paper notebooks. In Part 2, our panel of experts will discuss the special features of ELNs and how to overcome the difficulties of ELN implementation. On the panel are Lauren Shields, Ph.D., head of customer success at Benchling; Sophie Daudenarde, senior product and design manager, BrightLab™ Software at MilliporeSigma; Guru Singh, head of growth at LabTwin; and Tea Pavlek, VP of marketing at SciNote.
What kinds of special features does your ELN offer?
Shields: When ELNs were originally developed back in the ’90s and early 2000s, they were intended to make laboratories more efficient. However, in reality, ELNs can still have many of the same restrictions and inefficiencies as paper notebooks. One 2017 review stated that 22% of ELN users thought their ELN was too difficult to use and 80% found it difficult to capture relevant information using their ELN.
You’d think that legacy ELNs would make it easier to copy and paste directly into other formats—but they still often require scientists to manually move data into other external, disconnected systems because they aren’t natively compatible with other data repositories. In addition, many ELNs make it difficult to capture metadata relevant to a given sample or experiment, meaning that data loses its context as it gets transformed or transferred to different systems and teams. In addition, many ELNs are clunky and hard to use. Because scientists today are used to modern software in other parts of their lives—YouTube, Gmail, Facebook—it’s understandable why they’re frustrated with ELNs that function like they’re from the last century.
A software solution should address the inefficiencies of manual recordkeeping. Software should be more than just an electronic version of paper and should be flexible in the face of iteration, rather than breaking when innovations arise. Scientists deserve modern software that fosters insights, supports collaboration, and drives predictive and adaptive planning.
Benchling solves these problems. Benchling is a fully unified platform to centralize and standardize all R&D data and is built for the complexity of large molecules and large molecule R&D processes. Its flexibility enables you to rapidly iterate on R&D workflows through a platform that’s easy to configure, integrate, and extend. Benchling was built in the cloud from day one to serve as a single source of truth for your R&D organization, through a unified suite of applications (Notebook, Molecular Biology Suite, Registry, Inventory, Requests, and Workflows).
This means that scientists no longer have to move data between disparate systems, and records are always contextualized as part of an end-to-end experimental history. For example, scientists can embed the plasmids they used in their experiments directly within their Notebook entries. Other scientists can then access the entry, click through directly into the plasmid, and even see which freezers contain cells that express that plasmid. And what’s more—Benchling is built to be as intuitive as consumer software. Taken together, the power and usability of Benchling mean that scientists use it as an active tool in their research, not as a static archive of data.
Daudenarde: MilliporeSigma’s BrightLab™ collaborative lab management platform is designed to streamline and centralize all the essential resources you need to keep your research running—from projects and protocols to instruments and inventory. Not only does the BrightLab™ platform include a cloud ELN with customizable, searchable modules, but it also can connect to real-time inventory reporting and data workflows from your lab instruments to provide a holistic picture of your lab’s activities.
Singh: LabTwin is voice-activated, which allows scientists to record and access data from anywhere in the lab without removing their gloves. LabTwin’s digital lab assistant integrates with ‘smart’ lab instruments to automatically record data. Our digital assistant also provides visual and audio information; for example, LabTwin can guide users step-by-step through interactive protocols and read out each step to scientists.
With our API, LabTwin will soon integrate with external data sources and provide scientists with instant, on-demand, scientifically accurate answers while they work.
Pavlek: The SciNote features that users point out the most are the following:
(1) Inventory management. SciNote allows users to track all their samples, reagents, instruments, and more. Every inventory item can be connected with experiments. Inventory tables are customizable, so users can adapt them to their needs and enter different data for their inventory items, such as barcodes, files, dates, images, and more. To make it even easier, users can upload their existing Excel sheets, so there is no need to set up everything anew in SciNote.
(2) Integration with Microsoft Office Online. SciNote is integrated with Microsoft office, which allows users to upload, edit, and view their Excel, Word, and Power Point files directly from SciNote.
(3) Integration with protocols.io, the number 1 science methods repository.
(4) Ease of communication and collaboration. Users in SciNote can easily tag and send comments to their colleagues, delegate tasks, confirm results or keep in touch with happenings in the lab while away on conferences.
(5) Automated reporting. Once their data is organized in SciNote, users can generate comprehensive project reports within seconds. Each report can be exported as an editable Word file or a print-ready PDF that allows users to significantly reduce the time needed to prepare reports on their work progress.
(6) The Manuscript Writer. This SciNote add-on uses AI to generate a manuscript draft based on the user’s data saved in SciNote.
What are some features that current ELNs, in general, are still missing before they will be adopted universally?
Shields: Electronic lab notebooks struggle to integrate with other lab software, from molecular biology tools to LIMS systems. As a result, ELNs are often used alongside multiple other siloed, point solutions. Because these software systems remain disparate, difficult to integrate, and too rigid to handle, they can end up hindering rather than accelerating R&D.
Life science is progressing every day, bringing us closer to novel gene editing and cellular therapies, sustainable fuels, and sustainable foods. To bring these technologies to the world, the industry needs comprehensive software that provides the features that legacy ELNs and LIMS systems promise but fail to deliver. The future of biological technologies is bright, and it’s time for life science to step out of the shadow of outdated software, leave behind the scattered papers, electronic lab notebooks, and LIMS of the past, and embrace intuitive notebooks on unified, cloud-based platforms.
Daudenarde: Old habits die hard, and researchers who grew up with paper notebooks will have a hard time letting go. In order for ELNs to gain wider acceptance, they will have to more naturally adapt and seamlessly integrate with the applications and workflows that researchers are already using every day. We expect that greater advances in predictive analytics and intuitive reporting tools will one day make ELNs an invaluable asset in the lab.
Singh: Most ELNs have not been designed to fit into scientists' workflows. When scientists are performing experiments, their hands and eyes are busy. They cannot easily type information into an ELN to record experimental conditions or capture results. Digital tools must adopt user-friendly, intuitive interfaces, such as voice, before scientists will widely adopt them.
Also, digital tool developers need to reassure scientists that AI will not take their jobs. AI and digital tools can support human scientists but cannot replace the creativity and lateral thinking required to design experiments.
Pavlek: From a broader perspective of things, the user-adoption challenge laboratories are facing is not about the specific set of functionalities that certain ELNs do or do not have. We need to be aware of the fact that switching from paper-based to digital systems is a big shift for some laboratories. If they wish to digitalize their processes, the entire lab team needs to be on board. This requires good team collaboration and awareness of the importance of seamless data management, data traceability, and reproducibility. Functionalities offered by most top vendors of the market will be able to satisfy most labs’ needs, but it is the shift in awareness that needs to happen first. For ideas on how to get the team on board, check out our blog post on implementing an ELN.