Making the Most of Your Knowledge

While greater access to data provides an opportunity for most organizations, it also represents a challenge in terms of IT. So how can laboratories ensure they are making the most of the scientific knowledge at their disposal? NGP talks to Pat Martell, Director of Waters Laboratory Informatics, to find out.

NGP. What can the benefits of a high quality bio-repository be for an organization, and what challenges do biotech and pharma companies face in managing that data?
PM. Companies derive the most value from intellectual rather than physical assets. In order to get the most value from a company’s intellectual assets, knowledge must be shared and serve as the foundation for collaboration. Generating value from such assets involves sharing them among employees, departments and even with other companies in an effort to devise best practices.

What do I mean by intellectual or knowledge-based assets? There are two categories of knowledge: explicit (tangible) or tacit (intangible). Included among the former are assets such as patents, raw data, reports, results, pictures, drawings, publications, ideas, etc. Explicit knowledge consists of anything that can be documented, archived and codified. Tacit knowledge or know-how, on the other hand, is contained in people’s heads. The challenge inherent with tacit knowledge is figuring out how to recognize, generate, share and manage it. Identifying tacit knowledge in the first place is a major hurdle for most organizations.

Effective knowledge management allows companies to foster innovation by encouraging the free flow of ideas, boost revenues by getting products and services to market faster and enhance employee retention rates by recognizing the value of employees’ knowledge. Lastly, more effective knowledge management streamlines operations and reduces costs by eliminating redundant or unnecessary processes.

NGP. How are new software applications available today enabling them to address some of these challenges and make optimal use of their information?
PM. Each laboratory has basic needs such as furniture, supplies, water, gas, power, etc. and scientists easily identify these requirements if someone asks them. But what about informatics? Informatics or ‘information science’ is often ignored at that stage, so companies miss the right point to start knowledge capturing. Companies then continue to sift through numerous paper archives, databases and applications to find the necessary information. They are not working in a consistent application environment, and as a consequence they are concerned about their company’s ability to manage data compliance and intellectual property throughout a global enterprise.

Fortunately, the market offers powerful solutions for capturing explicit and tacit knowledge – for example, Waters’ NuGenesis SDMS (Scientific Data Management System) and Waters’ eLab Notebook. Waters Nugenesis SDMS is the ideal solution to capture explicit knowledge and at the same time provide a unique data integration platform for a laboratory. SDMS provides laboratories with an effective foundation for scientific information management by making data easier to access, facilitating compliance with regulatory requirements, and aiding in the administration of intellectual property throughout its lifecycle.

The dominant lab area related to tacit knowledge is the use of paper-based notebooks. Most companies still use them to record their work and store their intellectual property (IP), and later use them as the basis for patents. Waters eLab Notebook is the general tool to record the tacit knowledge of scientists for later re-use in electronic form.

NGP. What role can these tools play in creating a leaner and shorter drug development pipeline?
PM. SDMS and eLab Notebook catalog all information automatically, so it can be searched, re-purposed and serve as the foundation for new knowledge. Searching is not only text metadata (attribute) based; chemical structures and raw data files can also be searched and found using special search techniques.

So the use of these tools (equivalent to the use of corporate knowledge) accelerates the research and development process to discover more promising leads sooner, and to identify failures faster. They help to glean knowledge from increasing amounts of scientific, clinical and market data. In addition, they integrate disparate data and applications to create a collaborative environment across scientific and business disciplines. They also allow taking full advantage of current and future technologies, legacy data and applications through the use of open standards.

NGP. What architectural changes are required to make these information systems cost-effective for R&D? How easy are they to integrate with existing systems and what ROI can a company expect?
PM. SDMS and eLab Notebook need to be regarded as infrastructure. Once introduced in a computer center, users may be added with minimal effort. SDMS and eLab Notebook technology can be implemented lab, department or enterprise-wide with short implementation times. They help to better integrate a variety of data sources, reducing interfacing cost, and are able to solve more complex data management tasks in a single technology environment, which also lowers hardware investments. Validation costs will stay in a convenient ratio compared to overall deployment costs.

Beside the return through the knowledge management aspect, the financial return is immediate: shorter validation cycles, lower validation costs and lower administration costs. A single platform facilitates synergies in departmental or enterprise purchases.

NGP. What might the future hold for this data management software? Are there any features you would like to see built in, and how could the ease-of-use, for example, be improved upon?
PM. The next generation of this kind of data management software will need to have a stronger portal character. A lot of the data management tasks will be handled by eLab Notebook-like infrastructures. All data is entered just once and then transferred to inferior processes. This requires richer user interfaces with smaller footprints, like web applications but without all the drawbacks. The goal is to access all information and knowledge and at the same time to minimize deployment and validation to an even larger extent.