Review
widespread within the pharmaceutical industry. There are valid reasons for this, including regulatory constraints, which need to be overcome if we are to use these data to improve outcomes for both business decisions and patients.
A process-based approach can reduce the overall cost of IT systems ownership by replacing multiple analytic systems with a single integration and reporting system. Applications for data integration, metadata management, blinding and unblinding, report execution, report storage and retrieval, workflows, and data visualization can all be built into the framework. The layering of analytics on top of a global data repository framework will reduce the global programming effort by providing a standard environment for generating the tables, listings, and figures for reports. Pooling of data from multiple sources can be sliced for formal reporting and ad hoc visualization. As well as enabling deeper insights by leveraging the available data, immediate real-time access enables a new kind of process improvement to what has previously been a more retrospective environment. This shift from retrospective analytics to prospective analytics will provide data to the right individuals at the right time to enable them to make informed decisions.
To further empower the end user, it is important to design the system from an information-centric rather than a data-centric perspective. Data repositories that can be maintained by clinical programmers and statistical programmers without the need for constant support from IT specialists will enable researchers to focus on extracting
scientific knowledge across the entire development portfolio, from microarrays to defining population subsets.
While these systems are within reach in the pharma environment, easily accessible pooled patient data in a useable format is a distant reality outside its confines, such as in hospitals and surgeries. Here there are yet more valuable data that could be brought into play, although the aspects of the arguments for and against accessing this data are for wider discussion.
Delivering Virtualized R&D The virtualization of R&D has begun. We are beginning to see the implementation of a worldwide network with R&D activities located globally to augment and acquire new assets. This integrated network structure utilizes flexible units that are able to take decisions more rapidly and establish collaborations with external partners. This virtualization is being supported by a global ecosystem of software vendors providing integrated applications based on open standards and using common data elements. These technologies, developed on secure and scalable infrastructure, provide support across different process flows and break down traditional silos. This change is driven by the need to access global innovation, access multiple parallel data sets, and enable more informed decisions more quickly. It is the evolution of biopharmaceutical R&D. The vision is the integration of life sciences and healthcare to provide an economically sustainable model that benefits the biopharmaceutical industry, industry partners, and patients. n
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VIRTUALIZATION IN PHARMA R&D
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