It is often said that the one constant is change. And in the world of pharmaceutical research and development in the last decade or so, this is particularly evident. 

Not only has the criteria behind intellectual property (IP) protection and patentability changed, but so has the size and shape of research organizations, as well as drug targets. Until recently, companies were primarily focused on meeting their organizational goals using small molecule drug design. Now, shifting research has led to large molecule biologics with properties that are more in line with physiological systems.

The mechanisms used to capture all this data and utilize it in a more productive fashion have also changed. Capturing research in a well-defined or structured system for data management is crucial to the success of any research organization. 

The key to gaining knowledge from experimental results is to have a mechanism that captures not only one’s research successes but also captures research mistakes—which can subsequently be used to guide a company’s future research and direction.

Harnessing this knowledge effectively can prevent needless experiments being undertaken and avoid repeating work that has already been completed. Ultimately, this knowledge can shape what direction research needs to take, without the need for additional experimentation.

In short, effective scientific data management helps organizations avoid wasting valuable research time on areas that will not accomplish the project goals. 

Dynamic data management systems

There are cutting-edge technologies on the market that have been designed specifically as enterprise platforms—aimed at empowering today’s research scientist in their journey of novel research discovery. Modern data management systems are dynamic and enable electronic collaboration for today’s technologically savvy scientist.

Within just days, or a few weeks, biotech and pharma companies of all sizes can be up and running using a unified SaaS platform with no downtime or delay in a company’s corporate research mission. The ability to  capture multiple elements of basic research data and analytics from biology and chemistry, enables a seamless transition to electronic data management.

One does not need to change the way the research is conducted; the change is happening purely from a dynamic standpoint for data integrity, compliance and IP protection. Time minimization and smooth data transfer  between applications, and the ability to avoid data transcription error are just a few examples of how web-based applications have unified many research organizations.

As different components or modules of these cloud platforms are incorporated into the data capture process, additional benefits are realized by the management of inventory. Dynamic structuring of research data and harnessing corporate collaboration both internally and externally are also key benefits. A unified platform approach not only captures IP in an organized fashion, but provides an intelligent mechanism to de-silo the different elements needed for accurate and strategic research development.

There are two initial phases to any successful deployment, with customer value generated at each step along the way. The initial “paper to glass” stage provides immediate IP protection and dynamic searching and collaboration out-of-the-box. Bringing additional capabilities, such as inventory management, into a second phase will augment the initial advantages with structural data management.

With the right solutions, other modules including biomolecule and chemistry capabilities can be added, combining functionality that allows the new era of large molecule discovery to overlap with traditional synthetic design. 

For scientists and researchers in biotech, time-wasting notebook keeping, process replication, and repetition of menial tasks can eat away time from what’s important; gaining meaningful insights and innovating. Fully integrated informatics technology provides the space needed to enable researchers to step back, think differently, and see the bigger picture.

Breakthroughs rarely come in one big “eureka” moment. Innovation is built from numerous small movements and insights along the discovery continuum timeline—made possible and accelerated by technology that helps to unite a team toward a common goal, despite differences in discipline, location or language. 

Although the pharmaceutical research and development landscape has changed significantly, organizations can now turn to technology to ensure they are in the best position to tackle the present and future challenges of unified scientific R&D data management. 

Reducing R&D journaling practices by 40 percent and saving as much as two to four hours per day, per scientist—benefits that can be easily obtained using the right technology—can be the leverage needed to reach the next “breakthrough” moment, for biotechs of all sizes. An intuitive, integrated system can offer the means to capture a research organization’s data in a secure and compliant fashion, creating a dynamic corporate resource to help drive discoveries.

About the Author: Scott Mayer is Lead Consultant at IDBS.