Implementing Electronic Lab Notebooks
This is the third article in a series on best practices in electronic lab notebook (ELN) implementation. The previous article identified five core areas that need to be managed to ensure a successful ELN deployment. This article discusses the second core area: documenting experiments.
A driving force for deploying an ELN is improving the scientist’s work in the laboratory. This is generally focused on improving efficiency in executing and documenting experiments. To accomplish this, first analyze how specific scientific groups (i.e., biology, process, discovery, analytical, etcetera) document their day-to-day activities. Understanding these processes and their impact on the configuration and deployment of the ELN is the next step in planning and managing a successful ELN implementation.
Analyzing scientific workflows
Scientific workflow analysis focuses on understanding and mapping the process(es) used by scientists in target groups when conducting and documenting their daily work. This analysis should be agnostic to the mechanics of creating and documenting the experiment. The analysis should focus on the specific needs created by the scientific workflow. In particular, the analysis should follow the data flow, i.e., data sources, data formats and data use.
The analysis should start with an understanding of the data collected when executing an experiment. This includes not only the data used to record the experiment setup, but also the result data collected during experiment execution.
Next, you need to identify the process(es) used to analyze or manipulate data. These can be data transformations, calculations, spectral integrations, etcetera. Pay particular attention to categorizing input data, output results and the processes used. Note whether the data is contained solely within the confines of the experiment or combined with other data.
Finally, the analysis focuses on identifying data that will be either queried or mined. The advantage of an electronic record is the ability to find documents based on data queries and the ability to mine and combine data from multiple experiments to turn data into information. This analysis will impact how and where data is stored and the ease with which it can be accessed.
During the scientific workflow analysis, it might be discovered that groups doing the same work in different locations developed divergent ways of recording experiment data. This is not unusual when using paper notebooks. The isolating nature of paper notebooks creates procedure silos. The collaborative nature of an electronic environment makes ongoing support of disparate processes not only expensive vis-a-vis total cost of ownership, but also works contrary to needs for searching and reuse of data recorded in the experiments.
Where disparate methods are identified, organizations should work to harmonize the processes as well as associated items, such as vocabularies and common terminology to make searching more intuitive and the data more cohesive for mining information.
Migrating from paper
After processes are mapped and similar methodologies are harmonized, the process of migrating from a paper to an electronic lab notebook begins. “Paper on glass” recreates existing paper notebooks in the ELN. The benefit of this approach is maintaining familiarity for end users. Direct transcription of forms and other paper-based mechanisms for recording data preserves existing processes and is least disruptive when transitioning users to an ELN.
Although the processes are familiar, they may not be the most efficient way to record experiments. Paper on Glass does not leverage the new functionality available in an electronic based system. Thus, Paper on Glass should be seen as a way station and not a final destination in the ELN deployment.
Beyond paper on glass
To move beyond paper on glass, the documented processes need to leverage the functionality available in the ELN so scientists can move past the two-dimension physical page. To guide data entry, forms can be created that include drop-down lists of values. This speeds up data recording and standardizes data entry to improve searching. Material lists and reaction schemes can be linked. Specialized sections for entering information about solution preparation or pharmaceutical formulations can automatically calculate amounts, concentrations and other values.
The process to leverage these capabilities starts with mapping the scientific processes to ELN out-of-box functionality. The result is an ELN deployment plan that includes a roadmap for maximizing out-of-box functionality and a gap analysis of needs to be addressed for most efficient use of the ELN. The gap analysis should include an impact assessment grouping items into three categories:
1. Must Have
2. Like to Have
3. Nice to Have
“Must Have” items should meet two key criteria. First, there should not be a way to accomplish the need by either adjusting the process or using a combination of out-of-box functionality. “Must Haves” also should be items which significantly increase user efficiency in either time to document experiments or data integrity. If the need passes these tests, the items should be addressed through custom services engagements. Electronic lab notebooks have a software development kit (SDK) that can be used to extend functionality using standard programming languages. These enhancements to the notebook can be done either by the customer or the ELN provider. Once all “Must Haves” are addressed, deployment can begin.
As the deployment plan is executed, the functionality provided by the ELN and the customization activities are aggregated into experiment templates that provide the functionality and guidance needed to effectively document experiments. Template sections provide general capabilities to record text or embed files, or specific capabilities to draw chemical structures and reactions, calculate solution concentrations and create design of experiment (DOE) data. These sections, along with the customizations, create templates that can either be loosely configured to allow users to select the required sections to meet their changing needs (e.g., discovery activities) or more closely controlled to address GxP work (e.g., GMP GLP, etcetera.).
In contrast to scientific workflow, which dictates the way scientists record experiment data in the ELN, document workflows direct and facilitate the review and signoff of experiments as they evolve from works in progress to reviewed and archived intellectual property. With paper notebooks, this was done by physically passing the notebook. Document workflows in the ELN include pathways to the various groups within an organization that must review and sign-off on experiments. The electronic document is “virtually” passed for review and signing. Because the document remains within the ELN during this process, there is no limitation on the location of users or groups who can be part of this process.
Revolution vs. evolution
If not done correctly, moving from paper to an ELN will be perceived by scientists as a revolutionary activity. When the outlined process is followed, daily routine will be fully mapped to the ELN functionality, enabling scientists to continue documenting their experiments with minimal interruption. The movement to the ELN will be evolutionary and not revolutionary.
The evolutionary process should not stop after the initial deployment. Over time, scientific workflows will change and new functionality will be introduced in the ELN. Each time this happens, the analysis needs to be revisited so that scientists’ needs and ELN functionality remain synchronized and the evolutionary growth of the ELN is sustained in the enterprise. This process also looks at items previously identified as “Like to Have” or “Nice to Have” to see if they can be addressed.
During this phase of the ELN deployment, organizations should start by evaluating their current processes to understand how data is created, recorded and used by the scientific community. Once the processes are mapped, the requirements are overlaid with the ELN’s capabilities. Gaps are identified and evaluated, and items deemed as “Must Haves” are addressed via customization activities using the ELN’s SDK. Document templates are created with the functionality needed to guide and support the end user scientists in their daily workflows.
Ongoing evaluation of scientific workflow and ELN functionality will ensure that the scientific community and the product evolve together, optimizing the ELN’s positive impact on scientists’ daily work.
1. Lass, Bennett D., “Implementing Electronic Lab Notebooks: How do you Define and Manage Success?” Scientific Computing, June 2, 2011. http://www.scientificcomputing.com/articles-IN-Implementing-Electronic-Lab-Notebooks-060211.aspx.
2. Lass, Bennett D., “Implementing Electronic Lab Notebooks: Building the foundation” Scientific Computing, June 21, 2011. http://www.scientificcomputing.com/articles-IN-Implementing-Electronic-Lab-Notebooks-Part-2-062111.aspx.
Bennett Lass is the Director of ELN Services at Accelrys Inc. He may be reached at editor@ScientificComputing.com.