How to Overcome Barriers in ELN Adoption
Electronic laboratory notebooks help to increase productivity and organize data. Learn about Revvity Signals ELN solution, designed by scientists experienced in drug discovery.
Since their introduction more than 30 years ago, scientific researchers have been urged to adopt the use of electronic laboratory notebooks, commonly known as ELNs. There are many benefits of using ELNs, including:
- Improved data organization: Easy searchability for data retrieval and a centralized repository for data and experiment design protocols.
- Streamlined workflow and data capture: Integration with lab instruments to automate data capture and data analysis.
- Compliance: Audit trials are vital in drug discovery and clinical trials, ELNs ease the time burden to support regulatory requirements such as FDA 21 CFR Part 11, ISO9001, and others.
- Better collaboration: Allows for the easy sharing of data, protocols, experiment design, and results among disparate team members working in multiple locations.
While electronic laboratory notebooks have long promised to reduce time spent on administrative and repetitive tasks and free researchers to spend more time on the science, adopting a new ELN in the research setting is not without its challenges. Savvy pharmaceutical and biotech executive looking to make the switch need to understand where their pain points are and how to choose the best ELN for the organization today—and into the future.
What to Look for in an Electronic Laboratory Notebook
The path to selecting the best ELN for your enterprise should be meticulous, structured, and include a cross-functional team comprising those who will ultimately be using it every day. Working together, your team should:
- Create a list of what improvements they hope to achieve in lab and in clinical trials management
- Develop a method to measure the fit of the electronic laboratory notebook options
- Build an implementation strategy that provides timelines for deployment as well as orientation and training for those who will rely on it in their roles
Perhaps the most important consideration for an ELN is that it is easy to use, is intuitive, and can improve the efficiency and productivity of the research and development team. An electronic laboratory notebook is supposed to improve productivity, not hamper it. Choosing one that is hard to use or doesn’t have the needed functionality can negatively affect adoption rates which lowers the value of your ELN investment.
Revvity’s Signals Notebook is an intuitive ELN solution that helps you capture and organize data while providing access at any time on any device from its secured, cloud-based application. The intuitive drag-and-drop approach allows for the easy handling and uploading of all forms of data and files. It allows users to search for data across multiple studies quickly and share that information with colleagues in a permission-managed notebook, fostering collaboration and improved productivity.
How to Ensure Your Electronic Laboratory Notebook is Scalable
Effectively managing organizational change is difficult, so ensuring this occurs with minimal disruptions to your drug discovery R&D efforts is vital. Revvity Signals’ services and solutions are built with the understanding that our pharma and biotech partners need a scalable, extensible software as a service (SaaS) solution that provides the built-in agility needed to respond to shifting market dynamics and opportunities all while growing with your company every step of the way.
Deploying a new ELN is expensive and time consuming. If your organization choses an electronic laboratory notebook that is good for right now, but doesn’t have the ability to scale, it could be faced with adopting another new ELN in just a few years’ time and risks delaying your most important programs. Further, within the R&D environment, the ELN is the key tool help your organization build and interpret data from multiple platforms and applications. Revvity Signals’ robust collection of APIs ensures your research scientists can easily access the data they need to keep the best candidates advancing through your pipeline.
A Purpose-Designed ELN That Fits Your Needs
Drug discovery is a complex endeavor that can incorporate not only data for the development of small molecules, but increasingly on gaining knowledge and insights on the potential of biologic drug candidates. These data sets are larger and more complex, and often require the participation of a diverse set of collaborators working in multiple locations spread across the globe. Adopting an ELN that doesn’t take into account this complexity and the challenges of integrating data from multiple sites, can put your R&D investments at risk.
All ELNs are not created equal—an ELN that was not developed by scientists and lab managers with direct experience in a robust R&D environment can’t provide you with the assurance that it is nimble and flexible enough to capture all the data needed to identify your best drug candidates and prepare them for an IND submission.
As a fit-for-purpose ELN, Signals Notebook was designed by scientists experienced in drug discovery to incorporate the best in chemical and biological intelligence to increase productivity and foster insights from the data created by your R&D teams. More than just an ELN, Signals Notebook serves as a research partner to help researchers comprehensively manage workflows, aid in inventory management, and create an environment that simplifies experiment design, fosters collaboration and accelerates research.
Revvity Signals has continued to empower scientists through research, adaptability, and innovation. To learn more about how you can improve data capture and choose the right ELN partner for your organizations’ research and development needs, visit the Signal One website to catch our latest demo.
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Zev Wisotsky, Ph.D.
Sr. Principal Marketing ManagerZev is a Sr. Principal Marketing Manager for Biologics in the Signals Suite. His scientific training and research background includes neuroscience, biochemistry, molecular biology, and drug discovery. He has spent 7+ years in software in go-to-market teams across industries with a heavy focus on biopharma/biotech R&D.