GRI released the first version of Rodin in 1998 as the global source of high-throughput screening (HTS) results (a measure
of binding by experimental compounds to biological receptors). HTS is an automated process conducted throughout Roche by robotic
equipment. Because of their uniformity, HTS results were the only viable candidate for global dissemination through Rodin.
Once Rodin was up and running, researchers at any Roche site could view up-to-date assay results produced at other locations
and compare them in a meaningful way. In addition, researchers could browse the structures of the compounds used in the assays.
Given a taste of global access to HTS results, researchers expressed interest in sharing other types of assay results. In
laboratories where pharmacological assays are conducted, informatics specialists installed ActivityBase to capture and manage
the assay results uniformly. This move enabled researchers to achieve a consistent workflow from site to site. In addition,
the informatics specialists designed interface software to upload validated assay results to Rodin's global data warehouse.
The next incarnation of Rodin provided new user and workflow interfaces, which made it possible for researchers to examine
both pharmacological and HTS results associated with compounds and with individual research projects. For example, researchers
conducting a kinase project at one site could view the results obtained in other kinase projects, past or current, regardless
Roche researchers instigated the next step in Rodin's evolution. They began to scrutinize the data generated by critical assays
for determining the ADME (absorption, distribution, metabolism, excretion) properties of experimental compounds. They recognized
that the results of an assay conducted on the same compound, but at different research sites, might not be comparable. Each
site's protocols for conducting assays had its own flavor, so results would vary from site to site because of differences
in the assay rather than the compound tested.
This realization spawned the corporate Multidimensional Optimization (MDO) Project to:
» identify the most effective assays for evaluating ADME
» develop consistent globally-applied protocols for conducting these assays
» create validation procedures for harmonizing the assay results from all research centers
» upload the assay results into Rodin's global data warehouse to make them accessible to all researchers
» measure global progress toward achieving the preceding goals.
Supported at the highest levels of research management, the MDO Project became a corporate mandate for the globalization of
key assays in discovery research. It also emerged as a significant milestone in the global sharing of research information.
As a result of this mandate, a subsequent version of Rodin gave researchers rapid access to MDO assay results in addition
to HTS and pharmacology.
Later chapters in Rodin's history tell a similar story. Rodin continued to evolve with the addition of preclinical assay results
such as bioanalytical, drug metabolism, pathology, and toxicology studies.
Today, Rodin's global data warehouse ties together information from several international systems developed by GRI. These
systems support all phases of discovery research—from initial target identification to clinical candidate selection. The GRI
systems' ability to retrieve information from diverse databases enables users to discover unexpected relations among compounds,
research projects, targets, and assay results.
Informatics triggered the initial move toward standardization, but the fruitful informatics environment encouraged researchers
to share data and to globalize research methodology.
The Challenge Ahead
In addition to Rodin and its companion systems, GRI has conceived and supported a host of genomics, predictive, and molecular
modeling systems to aid in identifying drug targets and clinical candidates. The 2005 project portfolio includes a line-up
of advanced informatics tools with knowledge-sharing, correlation, and prediction capabilities.
Yet there is far to go. The downside of informatics abundance is that researchers have to operate each tool separately and
meld the yield of data to reach some conclusion. GRI's next major challenge is to design and build an intelligent global system
to evaluate relevant data from diverse, cross-disciplinary sources. The new system will be designed to find correlations,
make predictions, and deliver recommendations.