Tear Down Walls, Increase the Speed of Innovation
Laying a Foundation for Collaborative, Inter-disciplinary R&D
In the research world, bringing a new product to market requires the contribution of a host of experts, as well as the intersection of many scientific disciplines. For example, as chemists focus on discovering molecules, compounds and materials that can be used in personal care formulations, biologists may be called on to test potential candidates for safety and effectiveness on skin cell cultures. In the meantime, informatics experts work to analyze raw experimental data and market development teams create predictive models that seek to identify the key attributes and features that will result in a winning product.
Historically, all these R&D stakeholders have operated within their own silos, using their own processes and systems, and speaking their own language. Increasing the speed of innovation requires tearing down the walls that separate research disciplines so that scientific information can more easily be leveraged by the organization as a whole, and the collaboration that leads to new discoveries can take place. But how?
Unlock and Integrate the Information that Drives Innovation
As any researcher knows, the issue of data integration is a thorny one. Data generated by a single scientist, much less an inter-disciplinary group, is often spread across a diverse array of formats, applications and proprietary systems, such as unstructured text documents saved in an electronic lab notebook, images generated by a microscope, or supplier details stored in a database. And the volume is enormous - data may span thousands of possible formulation ingredients and compounds, to millions of test results generated through high throughput screening and more. As a result, stakeholders can easily spend countless hours finding and gathering needed information; preparing data for analysis and collating; and formatting and distributing results. But the rise of service-oriented architecture and technologies that foster more effective collaboration are changing this.
A web services-based IT foundation for scientific information management can support the integration of multiple sources of information in a "plug and play" environment, unlocking data previously marooned within disciplinary, system, application and format silos.
By bringing together critical pieces of information from multiple research areas and disparate sources, organizations can create automated workflows, feeding an integrated pipeline that streamlines highly complex research projects. The automated aspect of this integration is key - it enables researchers to leverage all the rich data sources available to them (both within and outside the organization) without the time and expense involved in writing custom software for each workflow.
For example, one leading home and personal care company was facing a situation where a huge amount of time was being spent manually converting file formats so that critical data saved on one system could be used within another. The deployment of an underlying platform that automatically integrates chemical, biological and text informatics has enabled this organization to increase research efficiency tenfold, simply by giving researchers the freedom to focus on the science and not the IT.
Transform Data into Knowledge
Speeding R&D innovation involves more than simply accessing and aggregating information, however. Stakeholders ranging from bench chemists to process engineers need to be able to transform raw data into the knowledge that drives new discoveries. Thus, an ability to collaboratively analyze advanced scientific information related to chemistry, process engineering, materials science and more is important. An extensive array of statistical methods - ranging from simple dashboards to advanced modeling methods - should be able to cross disciplinary boundaries and analyze data from disparate sources and formats, such as text, images, models, tables, etc. Researchers should also be able to "drill down" to the information behind high-level analysis when questions or problems require more in-depth investigation. Automation is again a critical component here, so that the research organization can avoid delays or productivity losses that can happen when IT must be called upon to build and deploy required analytical capabilities.
Forcing rigid information management systems and processes on researchers is the single fastest way to stifle innovation. So while chemists, biologists, engineers and other project contributors need to be able to work together more effectively, they also need to have the freedom to do what they do best. Thus, a flexible approach to information delivery is required - one that empowers collaborators to view data in a format that best suits their research methods. These formats may range from a simple Web portal to sophisticated 3-D visualization. This degree of flexibility leaves room for the innovation so vital to the success of R&D initiatives, but at the same time provides a collaborative framework for faster decision making.
In the race to bring to market the next top selling baby shampoo, laundry detergent or industrial adhesive, today's consumer packaged goods, chemical and materials and manufacturing companies need to tear down the walls that inhibit innovation. They need to find more efficient ways to manage, share and integrate huge volumes of complex research data, derived from many different sources, systems and formats. Doing this requires a flexible, service-oriented architectural foundation able to unify and analyze scientific information across departments and disciplines so that more effective collaboration, and ultimately faster discoveries, can take place.
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