INSIGHTS on Data Management Systems: Introduction

LIMSs dominate, but convergence rules

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The drive toward fully paperless operation is causing laboratories to rethink their investments in data management software, particularly in LIMSs and ELNs, and to ask how these tools could provide an integrated flow of information from instrumentation through to enterprise systems, helping managers make informed decisions while eliminating manual steps. “It’s all about operational efficiency and using information to inject responsiveness and agility into an organization,” says Trish Meek, director of Product Strategy, Life Sciences for the Informatics business at Thermo Fisher Scientific (Philadelphia, PA).

A holistic information strategy demands that users and vendors collaborate to identify gaps in information flow and understanding that thwart the implementation of end-to-end data “solutions” for laboratory organizations seeking to deliver a paperless lab.

“Customers keep relating to us the need to derive value from their information systems, while focusing not on systems themselves—the individual software packages—but on processes and workflows,” Meek adds. Among the evolving tools for process understanding are integration of software from different areas and levels of the workflow and data visualization tools. Together, these enable labs to take advantage of where information and processes originate and where the resulting data is eventually used. “Lab informatics relates not only to the lab generating data but to the wider environment or enterprise, for example, for decision-making during a critical juncture in manufacturing or for batch release.

Integration and advanced data handling technologies existed a decade ago, but laboratories lacked the desire or will to implement them. What has changed is how organizations now view information: not as a point event belonging to a single instrument or laboratory domain, but as a valuable deliverable from the laboratory with impact ripples organization-wide— what Ms. Meek calls an “end-to-end data solution.”

Data handling technology has changed, Meek observes, but “managers felt that integration projects were difficult, costly, time-consuming, and could not provide adequate ROI.” Today, with a greater appreciation for web-based services and more open architecture designs on the part of vendors, integrations are achievable—if not ready-made. “Integration has become more cost-effective, and people are beginning to see that.”

Specialization

A 2012 Gartner Group report by Michael Shanler advised potential buyers to focus on vendors with the greatest “domain expertise”—industry-specific experience— before selecting a LIMS. Shanler writes that while all products from top vendors are adaptable, they “require different levels of investment through customization or configuration.” Moreover, customers have reported that vendors lacking specific domain expertise often rely on excessive customization that adds to downstream complexity. Finally, companies with complex product portfolios should “resist the urge to consolidate into a single centralized LIMS.” The same could be said for complex organizations that perform discovery, R&D, product development, and manufacturing within a narrow product focus, for example pharmaceuticals or semiconductors.

Bob Meyer, executive VP at Lab Answer (Sugar Land, TX), a laboratory and science informatics consultancy, concurs. “The more specifically a vendor’s products attempt to solve a single problem, the more purpose-built the product will be.” The more vendors attempt to brand their data products as general purpose, the greater will be the need to add or modify to meet specific workflows.

Customers quickly come to recognize domain expertise. Agilent (Palo Alto, CA) plays in the laboratory data marketplace through its OpenLAB Enterprise Content Manager (ECM), a product it assumed through the acquisition of Scientific Software in 2005. Where LIMSs manage samples, ECMs are more comprehensive, gathering data from ELNs, LIMSs, instruments, and other data systems under one umbrella.

Chromatography Data System / Dionex Chromeleon 7.2 CDS / Thermo Fisher Scientific www.thermoscientific.com Senior R&D manager Dan Holmes estimates that 60 to 70 percent of the world’s pharmaceutical data is archived in ECMs. Pharmaceutical users are big on data systems because their data storage/retention policies span many decades—as much as one century. When everything was recorded on paper, business and scientific records were gathered periodically and stored in depots that resembled bomb shelters more than libraries. Today everything may be managed remotely through electronic data management. In the case of OpenLAB, the data exists in a technology-neutral, humanreadable format. That includes pictures, reports, tables, experiment data entry, and instrument data. “Customers can bring that data back and do what they need with it,” Holmes says.

Paperless outsourcing?

LIMS / HORIZON Data Exchange ChemWare / www.chemware.com 

“I’m amazed that modern notebooks still employ paper and manual processes and have not yet been transformed. This must change,” says Ken Rapp, senior vice president and managing director of the Analytical, Development, Quality, and Manufacturing (ADQM) solutions team at Accelrys Inc. He notes that while routine analyses involving hundreds of samples have caught on to barcoding and advanced data entry, much lab-bench experimentation still employs traditional record-keeping.

Paperless operations play into collaboration as well. “The landscape for externalized activities has completely reversed from ten years ago,” Rapp notes. “Back then, 70 percent of customers’ work occurred within their four walls, where today the ratios have reversed.” Last, few industries have exploited the value of visualization tools in the manner of online giants like Google. These tools spot trends but during laboratory and manufacturing processes can also pick up excursions that predict results that will be out of specification.

Convergence

LIMSs have emerged as the most easily recognized laboratory data systems, but they did not always provide the wide-ranging capabilities of today’s software systems. “In the early days all LIMSs did was manage samples,” explains Bob Meyer. “A LIMS took note of a sample, assigned a test, and captured the results. Then the operator would often run to his or her paper notebook and enter the data manually.”

ELNs provided greater functionality in their ability to store instrument traces, photos, and other data that was unsuited to LIMS. ELNs became searchable (provided data was entered into the proper format) and provided a validatable means to protect intellectual property. Another data product, approximately a decade old, was the laboratory execution system (LES), which is offered by several vendors interviewed for this article. LESs are primarily used in quality laboratories that run a lot of tests. Like ELNs and LIMSs, LESs provide a structured, all-electronic means of automating and controlling testing operations. Like LIMSs, LESs connect to instruments and can monitor calibration, training, and instrument usage.

Now, Meyer says, these three data packages have evolved to the point where they share significant functionality. “This is natural, as each of the vendors tries to capture more of the marketplace. They’ll say, ‘Well you don’t need a LIMS, you can do that with our ELN’ or ‘You don’t need a separate ELN, we’ve built it into our LIMS.’”

The convergence of LIMSs with other data systems, says Alan Vaughan, Content, Business Development and Training manager at LabLynx (Smyrna, GA), is “an ongoing process” but one of the hot topics in laboratory data.

Terry Smallmon, director for Life Science Sales at LABVANTAGE Solutions (Somerset, NJ), says “Lines have been blurring for a while, especially between LIMSs and ELNs.” Several companies now sell both products, and even more are porting the functionality of one package into the other.

Data system proliferation has given rise to an alphabet soup of “solutions” that include LIMSs, ELNs, SDMSs (scientific data management systems), visualization software, electronic data capture, lab execution systems, and clinical LIMSs. “The acronyms are confusing clients,” Smallmon adds. “It’s no longer black and white.” He believes that instead of discussing or specifying individual products, one should consider the process and the solution, which might incorporate several products. Or, if it’s configurable, maybe just one.

“The modern LIMS market has become a matter of connecting point solutions, islands of disparate data, and providing a portal. Take a step back and determine what specific problems you’re trying to solve. There’s definitely not enough of that happening. The players who survive when this all clears out are the ones who are conscientious in trying to solve problems.”

In addition to a problem-centered philosophy, these “players” should possess a baseline product on which they can build. Products will need to be more modular, more versatile, to accommodate the widely different needs among and within industries.

All major vendors recognize the utility of cooperating on data formats. Dan Holmes of Agilent relates that he has monthly contact with some of his competitors, focusing predominantly on data systems and software driver exchange. “Why should I write drivers for their instruments when I could repackage theirs and pull it into my data system, and vice versa? Why should they write drivers for an Agilent LC when Agilent knows the internals of that instrument better than anybody and can provide maximum performance for the customer?” he asks. “Nobody has equipment from just one vendor. Labs are heterogeneous environments.”

Categories: INSIGHTS

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Calculating Workplace Tragedy

Published: June 1, 2013

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