“Informatics convergence” has become a buzzword among ELN vendors and their customers. According to Steven Eaton, marketing manager for chemical analysis and informatics at Waters Corporation (Milford, MA), convergence encompasses an information environment in which the ELN is one component. Waters, for example, positions its ELN as part of its platform SDMS (scientific data management system).
“ELNs are not just replacements for paper notebooks, but facilitators that close the electronic gaps between and among data systems,” says Mr. Eaton.
Another noteworthy trend is the expansion of traditional ELN functions, particularly with respect to inventorying and sample management— competencies normally associated with laboratory information management systems (LIMS).
Integration has become critical for QA/QC. Pharmaceutical QC testing involves 40 manual transcriptions of instrument data. “With an error rate of between three and five percent, almost every record contains an error,” Mr. Eaton observes. By reading data directly from instruments, ELNs eliminate errors and costly retesting while streamlining data review.
One characteristic that ELNs have maintained over the years is application-specificity. “There is no one-size-fits-all ELN,” says Mr. Eaton. “I doubt we’ll ever see one that serves quality, biology, and chemistry workflows.”
John Newtown of LabWare (Wilmington, DE) views centralization and consolidation of laboratory data systems as an essential and inevitable consequence of the complexity of the data that labs generate and the systems employed to manage that information. Some companies use LIMS in one lab, an ELN in a second lab, and more conventional data capture in others. “Customers are demanding consolidation while emphasizing centralization and reuse of data,” he says. “The trend is definitely fewer systems, not more, and simplification through harmonization and centralization.”
According to a study by Atrium Research, just four percent of academic labs have adopted ELNs. Of adopters, 60 percent are chemistry labs, which lately have been urged by industry to use ELNs.
Why is there such low penetration at universities? Cost, inertia, and information technology complexity all come into play. To these issues, Prof. Jerry Wright of the Johns Hopkins School of Medicine adds scaling capabilities, user interface, customization, control of data sharing, image management, version control, and electronic signatures.
Academic labs do not feel the same kinds of productivity pressures as industry. Atrium cites a 20 percent improvement in throughput for ELN users, which is significant for high overhead industries. But faced with productivity bottlenecks, academics tend simply to work longer hours. Similarly, intellectual property protection, data verification, and validation are paramount in industry (particularly regulated ones) but of far less significance at schools.
While adapting ELNs to small research labs has been challenging, Web-based ELNs appear to suit academic laboratories particularly well. But even then, coaxing “temporary workers” to use them is difficult. A post-doc may spend one or two years in a lab, during which time he or she expects to publish several papers. “When you have one year to accomplish everything, detailed record keeping gets in the way,” says Dr. Wright. Given the choice between experimentation and learning a new software system, most researchers will select the former.
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