Demo: Electronic R&D

NuGenesis organized a seminar to demonstrate how their product can interoperate with other companies' products to form a solution for electronic R&D. The familiar plight of an R&D organization is that data and reports are generated by many different sources, and much of this information is required in still other applications for additional processing and reporting. The job of maintaining this content under the guidelines of the FDA and good science has become more and more difficult over the years.

The concept behind eR&D is to create a seamless electronic tool for the laboratory, so that researchers and lab technicians can get on with their work in the laboratory, rather than the tedious work of managing the copious output of lab instrumentation and the resulting analyses. This is an area that many companies are exploring, and the Collaborative Electronic Notebook System Association (CENSA) has been driving for about 10 years. (Website currently out of order.)

This particular demonstration showed an example lab, using InnaPhase's Watson LIMS to create a sample plan (which samples to run, number of standards, etc.); ship that sample plan to the instrument, where the data is collected and analyzed then stored in NuGenesis' scientific data management system; report the results back into the LIMS and do additional analysis, generating another report back into NuGenesis; pull data out of NuGenesis into CambridgeSoft's electronic laboratory notebook, create a report, close-out the notebook entry, and store the final back into NuGenesis; sign and witness the notebook page within NuGenesis. Data exchange between each of these components works fairly well, though the demo was a recorded "movie" of the computer screen.

The discussion didn't go into the nitty gritty of how data is transferred between these systems. I know that NuGenesis slurps raw data files into a large repository, and all human readable reports are "printed" into their database in the Windows Metafile format.

During the discussion, the leader gave us an interesting description of metadata: it is all about providing context. The best part was the example: "4.5 mg/ml" is just a piece of information that is not very helpful. But when I tell you that I used a specific instrument and this method with this dilution factor and this number of samples and the quality of the value (based on the range of values on the raw data), then you have a better understanding of how that value was derived and if it means something to you.