Beyond Bi

Managing research data

Efficiencies can be achieved in research-driven companies through superior data management, says George Varghese

Today’s drug discovery process generates a staggering amount of data of all types along the entire value chain, including genetic, micro-array, proteomic, bioassay, toxicology and chemical structure data. And with growing data comes the challenge of integrating large amounts of data in a variety of formats scattered throughout the organisation at multiple locations.

Process, data integration and data capacity constraints are on the rise. And as research and discovery cycles continue to lengthen and costs increase, streamlining systems and boosting productivity are critical. Ideally, research organisations need a centralised data repository that can connect legacy systems and grow along with data volumes. It is therefore important that the information available should be easily transferred among systems and shared across departments.

A scalable platform is needed

It is pertinent that scientific organisations have a single, integrated Business Intelligence platform. This can increase organisational productivity by streamlining the research process, and centralising data and its analysis. It also helps in establishing consistency among groups, and driving common assessment criteria.

What is important is that the Business Intelligence solution that is implemented for scientific discovery should empower scientific research organisations to distribute shared intelligence across the organisation to optimise quality and performance, so that they can deliver safer, more effective drugs to the market more quickly and improve profitability. In addition, the solution for research data management should:

• Enhance organisational effectiveness by minimising the use of niche applications
• Allow users easy access to the solution and manage high-quality data that spans the entire research discovery process from a central location
• Manage all discovery data—structured and unstructured—regardless of format or type
• Integrate easily with R&D legacy systems
• Enable compliance with government regulations by providing security, audit trails and versioning

Streamlining the analytic process

The integrated data management solution should function as a “staging area” for analysing data formats and types across the discovery cycle, which includes all types of structured and unstructured data formats, such as genetic, proteomic, chemical, bioassay, toxicology, micro-array and chemical structure data. Using an integrated data management solution, one can create reusable analyses and data preparation modules that are stored in the system for easy accessibility by scientists and other non-programmers. What is more important is that as the solution is based on an integrated Business Intelligence platform, it is possible to centralise and manage scientific discovery data that translates into superior data quality.

Improving accessibility

An integrated data management solution provides a platform for centralising access, analysis and management of scientific research data. This simplification of data management easily accommodates users by providing a complete, reliable view of scientific

discovery data with secure access. Users can make sense of their data by transforming it into relevant information, storing it and delivering it in a format where quality is never a question. In addition, with an integrated data management solution based on a single, end-to-end enterprise-wide Business Intelligence platform, users can have easy access to libraries of stored analytic methods and data preparation modules that optimise productivity and minimise the need for application development resources.

Simplifying connectivity and customisation

It is important for organisations to establish the framework for customised analysis management system and create connectivity to existing systems throughout the organisation. This would enable scientists and other non-programmers to easily select the appropriate analysis and run the programs when they want to—no more waiting for results from IT or the bioinformatics group. This easy access will encourage common analysis criteria and consistent analyses across the research organisation.

Enhancing legacy system usability

An integrated Business Intelligence platform and research data management solution allows scientific organisations to leverage investments that have already been made in existing hardware, software and data, enabling them to easily integrate legacy and non-legacy data sources in a highly flexible and readily maintainable environment. This would provide an integrated information management platform with the research discovery intelligence necessary to keep up with market demands. So, when there is a need to use discovery data with clinical data, the established processes can also simplify implementation, enable consistent extraction and transformation, and establish traceability.