Informatics Rules

How global computer systems helped far-flung research centers work together
Jun 30, 2005

Less than a decade ago, the roche research centers in switzerland, California and Japan rarely shared results with each other, much less with sister centers in Germany, the United Kingdom or New Jersey. In keeping with the company's long tradition of autonomous research, independent project teams pressed their own research agendas at each site, posing questions, evaluating data, and reporting results as they saw fit. State-of-the-art computer systems guided much of the research, but each system was as autonomous as the researchers themselves. Well into the age of the Internet, the company maintained an archipelago of productive, but ultimately insular, electronic research islands.


Key Informatics Systems in Roche Discovery Research
Although the research centers ran the same types of analyses, such as binding assays for G-protein-coupled receptors, they lacked standard protocols and reported results in different units: percent of control, percent of inhibition, or pKi. Even if the researchers could share these results, comparisons would be meaningless without normalization. When researchers don't share data on a regular basis, they can begin to feel proprietary about their work—and even less inclined to disclose their results. In the worst case, the research structure fosters competition rather than collaboration with colleagues.

Despite its commitment to maintaining autonomous research centers, Roche's research management team began to see the electronic disconnect between laboratories as a liability that cost the company time, money and knowledge. As a result, it decided in 1998 to establish Global Research Informatics (GRI), an organization to standardize informatics tools at all research centers, and thereby enable global sharing of research results. Encouraging laboratories to share data would enable each scientist to work autonomously but draw conclusions from an enlarged perspective. GRI aimed to select, fund, and oversee a portfolio of projects that developed a set of globally applicable informatics tools. GRI projects were chosen only if they added value to Roche discovery research worldwide.

Today, scientists at the (now) five Roche research centers around the world routinely order experiments online at remote automated service labs, such as the cardiovascular safety center or the toxicogenomics center. Requesting an experiment is typically as simple as filling out a Web-based form. After the electronic request, every step of the experiment is guided by informatics.


Strategic Objectives for Research Informatics
If the request goes to the Process Biology Lab in Nutley, New Jersey, for instance, the system can propose candidate samples from a 3000-sample tissue collection based on pathology, donor information, and clinical parameters. The electronic inventory system scans a global database and locates, in a roomful of giant freezers, the particular tissue sample needed for the experiment. Robots follow standard protocols to retrieve the sample and prepare it for experiments that generate more than three million data points—far too many to handle without informatics. The data flow into an information management system, where they are archived. Scientists in the service lab analyze the results and return recommendations to the requester.

The global computer infrastructure has grown rapidly over the past seven years at Roche research centers, where GRI has sponsored nearly 400 informatics projects. About 80 of those projects improved the hardware infrastructure to accommodate new, advanced software. The remaining projects led to some 200 software implementations and system upgrades. Among them are key Web-based systems that enable Roche researchers worldwide to share assay results within a few hours.

Once GRI supplied the initial activation energy for Roche's global informatics systems, researchers began pushing for new technology to support a wider range of activities. Scientists began to standardize their own processes (e.g., screening and safety assays) so they could reuse comparable results.