Fostering Collaboration to Accelerate Discovery Research

A lone thinker, toiling in isolation, is the popular image of a researcher pursuing a scientific breakthrough. However, in the current era of networked, knowledge-led discovery, the next big breakthroughs will likely come from teams of people, working together to solve our toughest scientific problems. This is especially true in the pharmaceutical industry, which is utilizing teams of biologists, chemists and others to discover and develop next-generation drugs.

The use of multi-disciplinary teams is a key reality of the typical large-scale research programs found in pharmaceutical companies. Another important reality is a trend toward increased experimental throughput: the variety and volume of data generated by each discipline makes it more challenging to efficiently access, manage, interpret, share and apply the team's findings.

Deriving meaningful insights and inferences from large data sets becomes more intuitive when information is presented visually. Advanced, interactive visualization tools that are easy to manipulate can help users better understand relationships, patterns, trends and correlations between individual entities within a data set. Such tools let multi-disciplinary teams share their interpretations of the data and make appropriate decisions at each point in the discovery and development cycle.

Interpreting multiple data sets

Each team is driven by the desire to find answers to its questions and then map out a course of action. In drug development the questions often follow from a hypothesis about a disease: What's the cause? What's the most effective way to treat or cure people who have the disease? How can we prevent the disease?

Ultimately, researchers have to interpret the data and assimilate their respective perspectives into biological knowledge that provides a foundation for drug discovery. Increased understanding of the molecular mechanisms of disease and a desire to leverage that knowledge to test the biological relevance of potential therapeutics means target validation and pharmacology need to become intertwined—both upstream in the initial identification and assessment of a target, and downstream as clinical understanding of drug activity develops.

Researchers often use informatics software to perform detailed data analysis, but typical offerings can handle just one data set. To facilitate stronger collaboration between the disciplines, next-generation software such as the Agilent Synapsia informatics workbench is able to integrate the information obtained from multiple data sets. By providing a unified environment for the documentation of information related to a discovery project, Synapsia helps scientists connect disparate information sources and make decisions that are based on a more comprehensive understanding of drug and disease.

Creating a compelling narrative

Synapsia supports hypothesis-driven discovery across distributed organizations where team members from different disciplines contribute to the process. This is accomplished by creating a thread of documented evidence that includes pointers to additional experiments and the interpretations (and underlying reasoning) contributed by team members. Linking all of these elements makes it easier for the team to overcome the ambiguity of discovery, evaluate the validity of a hypothesis and map a course of action.

Synapsia lets users import heterogeneous data and explore it with a variety of visualization tools.

Structurally, Synapsia provides a single user interface that includes windows for viewing results, managing information and organizing discoveries. Data Viewers let users import data and results from experiments, then apply visualization and filtering tools. The Information Manager facilitates the collection and organization of data, results, visualizations and more. The Discovery Manager—the unique cornerstone of Synapsia—provides a user-configured narrative structure in which the team can document insights, ideas and project milestones. Working in concert, these Synapsia components enable scientists to quickly and securely access data, information and insights—and to contribute their expertise, perspectives and interpretations to evolving models.

Functionally, Synapsia helps users perform essential activities that enhance the drug development and discovery process:

• Explore data visually and interactively
• Utilize analysis tools such as Spotfire DecisionSite
• Synthesize a deeper understanding of the data
• Increase collaboration within and between the disciplines
• Capture and organize results from internal and external sources
• Automate the project workflow
• Assess project milestones and overall progress
• Document intellectual property for easy access

This combination of capabilities fosters new levels of collective understanding and insight that can help multi-disciplinary teams discover and develop next-generation drugs that target the root cause of a disease, deliver more effective treatment, and perhaps enable outright prevention.

For more information

Revolutionary tools such as Agilent Synapsia give scientists revolutionary new ways to collaborate as they pursue drug discovery and development. To learn more, please see the Informatics section of our Web site and a recent feature article about the creation of Synapsia. For additional information about these and other Agilent products and resources, please visit the Life Sciences/Chemical Analysis main page.