ELNs are not the hub for capturing every piece of laboratory data. There will always be a need for LIMS, SDMS and other informatics repositories that are specifically designed to handle structured or unstructured information. ELNs are, however, leading the way into a new era of converging functionalities. ELNs are changing the way scientists interact with information. Not only is data captured in an ELN fully searchable within and across experiments, but an ELN can also automatically provide third-party information to scientists. For example, without leaving their notebooks, scientists can look for commercial compounds or known synthesis pathways and populate the experiment with details. ELNs further improve the collection, analysis and reporting of experimental results by integrating with lab equipment such as balances and analytical instruments, including HPLC, GC, LC/MS and NMR.
The latest ELNs serve as a base to support the convergence of instruments, software and R&D workflows in an electronic lab environment. This convergence is enabling scientists to work more efficiently in project teams while also better orchestrating daily experimental activities involving compound registration, laboratory execution and experiment analysis, data collection from instrumentation, sample management and tracking, materials/ inventory management, laboratory information management systems (LIMS)/scientific data management systems (SDMS) and data warehousing systems. Today’s systems even reach beyond the lab into business information areas such as enterprise resource planning and financial reporting. Further convergence is achieved through integration with third-party applications such as spreadsheets, statistical analysis packages, kinetic modeling/data visualization tools, and chromatography and scientific data management software.
Respondents’ primary reasons for purchasing ELNs for their lab
|Accelerate the documentation and reporting of experiments||23%|
|Infrastructure to capture, access and share information about experiments||21%|
|Increase capacity to existing systems||15%|
|Centralize data repositories||9%|
|Setting up a new lab||8%|
|Enable scientists to collaborate effectively on multistage
projects and across geographic boundaries
|Improve communication between instruments and related software||5%|
|Streamline regulatory compliance||5%|
|Enable web-based access to information||4%|
The challenge for lab managers struggling to deal with the enormous amount of information generated by today’s labs is best addressed through an information-driven approach to R&D that enables scientists to leverage the information and knowledge of others in order to improve experimental design and analysis and thus overall R&D productivity. To deliver an optimal information-driven R&D strategy, companies are investing in flexible, multi-disciplinary electronic laboratory notebooks (ELNs) that can be used internally across the enterprise or worldwide across business ventures. These latest-generation ELNs offer centralized data repositories; infrastructure for capturing, accessing and sharing experimental information; improved communication between instruments and related software; and workflow orchestration tools that support the diverse needs of different disciplines, without extensive customization. This approach is accelerating the documentation and reporting of experimentation while also enabling scientists to collaborate effectively on multistage projects and leverage existing information for improved experiment throughput and success.
Do you use electronic lab notebooks (ELNs) in your lab?
|No, but planning to purchase||36%|
|No, and no plans to purchase||55%|
Looking to the future, ELNs will extend existing generation capabilities with hosted services, placing the ELN “in the cloud,” so that virtual project teams distributed across disparate geographic locations and business boundaries can easily share information and communicate using a common notebook. Next generation ELNs will reduce cost of ownership and enhance operational agility—enabling organizations to expand and contract R&D resources and IT infrastructure as necessary to meet changing business needs. The critical capability to store structured and unstructured data extends notebook functionality, enabling scientists to answer many challenging questions they encounter in the course of R&D workflows.
Some of the questions repsondents are hoping to get answers to with the purchase of an ELN
|What information already exists?|
|What data searches or experiments do I need to repeat?|
|What can I do to make sure that my first experiment is successful?|
|What can I learn from my colleagues’ experiments?|
|What are the best results?|
|How can my colleagues’ data help me reach a better
decision or come up with a new approach?
More and more labs are becoming comfortable with using ELNs as they see that these systems can eliminate transcription errors, accelerate data review, improve decision making, and reduce paper usage--resulting in decreased operational costs and accelerated product delivery. In addition, many labs are beginning to allow digital signatures rather than printing the paper and signing it. There are also companies that are beginning to discuss machine witnessing, with some having already implemented it. With machine witnessing, instead of having a notebook witness review things and sign off, the machine (i.e., your computer via the software running the ELN) checks that everything is finished and witnesses it. However, this is more likely to occur in truly structured areas. For example, in early research, where processes are less rigid, machine witnessing would not be used. But if the work is in a later stage where processes are less flexible, such as development or quality control, it is more likely to be a candidate for machine witnessing.
For those labs that are confused about which ELN to choose, there is no point in evalutaing the various systems until they decide what they actually need. Getting all the systems coordinated requires good planning, company-wide buy-in, and a good amount of work. For labs looking to buy an ELN for their laboratory – industry vendors and end-user companies that have already gone through the process will tell you that it is most important to know your requirements. Your lab will need someone specifically dedicated to preparing a full project path prior to purchase; negotiating with vendors; implementing and/or programming, and training.
Biggest challenges respondents expect to face with the purchase of an ELN
|Staff adoption and training||33%|
|Data migration into the new system||14%|
|Integration with other systems||13%|
|Investing in software that will become obsolete||9%|
|Gaining user buy-in||8%|
Completed Surveys: 323
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