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Jan 15, 2010 (Vol. 30, No. 2)

Laboratory Automation Circumvents Bottlenecks

Improvements in Speed, Data Integration, and Efficiency Are Expanding the Possibilities

  • Service Architecture

    Jeffrey McDowell, Ph.D., senior manager, IS-research informatics at Amgen, agrees that integrated access to data is important for productivity and for providing a complete view of available information for making decisions. He suggests that there are three approaches companies can employ in order to facilitate the integration needed for automation and drug discovery.

    “The solution Amgen has implemented uses a service-oriented architecture approach to create a data-integration system. In general there are three approaches to solving integration, which vary depending on where the data connections are made. These are integrating either in the data layer, where a consolidated data system (either physical or virtual) is created by re-factoring the information into a single or federated system; in the application layer, where the application is responsible for implementing the rules used for making connections between data; or in the service layer, which is a set of independent components that reside external to individual applications and connect via a distributed technology like simple object access protocol.

    According to Dr. McDowell, ultimately the service-architecture approach focuses on creating discrete services categorized and published through a service registry. This type of architecture not only allows for integration but also is easily extensible and permits service consumers to discover new resources and makes data connections automatically at runtime.

    “The consumer application uses these services in a distributed manner first by discovering them at runtime by querying the registry using standardized categorizations. The registry returns services matching the request which the consumer can then invoke. The service approach is easily extensible as adding new resources simply involves adding services according to the standards defined by the architecture. Given that the approach is data agnostic, data-type restrictions are only as defined by the categorization schemes used, the architecture can be extended beyond its currently employed data types.”

  • Integration for Systems Biology

    Besides integrating data from various disciplines within an organization, another layer of complexity emerges when needing to integrate data from systems biology approaches. Systems biology studies the interactions and interplay of multiple levels of biological information. “Although integration is conceptually simple, we have about 15 years worth of software that costs hundreds of millions of dollars and often still doesn’t work efficiently,” John Boyle, Ph.D., senior research scientist and director of informatics at the Institute for Systems Biology, notes.

    It’s not all doom and gloom, though, reports Dr. Boyle. “What’s important is simply that people within organizations take a step back and decide what they really need. There are a lot of redundant software solutions, but scientists need to switch to those most pertinent for drug discovery. Optimally, you need to ask three questions when deciding how to handle the problem.

    “First, decide what will allow ad hoc data integration. Chips and instrumentation come and go, what is needed is a way to allow integration when things change.

    “Second, find something that is easy to use. Scientists don’t have the time to keep learning new systems. It’s inefficient, too. We’ve found the best systems are more natural and typically look more like a file system. This is a nonintrusive approach and easily allows other activities such as e-mail integration.

    “Third, the data-integration solution must be easy to adapt. Science constantly changes, new paradigm shifts and new scientific finds must be considered. New solutions must have built in flexibility so that they can rapidly be adapted to new usage since you never know what will be discovered next.”

    Dr. Boyle suggests that the field is in a growth spurt. “We’ve just started really. We have a few growing pains, but it is clear that some commonalities are emerging. We are going to have to design solutions to be less formal and to meet science halfway. Instead of companies going for the latest trends, they simply need to take some time and put in some effort to take a good hard look at what is out there and what is the best way to meet their needs now and for the future.” 


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