March 23, 2016
by Sanji Bhal, Director, Marketing & Communications, ACD/Labs
As scientists, analytical data is extremely important to us. It plays an essential role within R&D to support decision making in drug development, product formulations, patent protection, competitive analysis and much more. Analytical data is also critical in identifying and characterizing samples, and providing responses to questions from regulatory bodies. In fact, 80 percent of R&D organizations say they rely on analytical data to make important decisions.
At ACD/Labs, we have spent two decades working with customer organizations to support effective analytical data management. While we are privy to the problems of our customers, we wondered how the wider R&D community has been addressing analytical data management and what challenges remained. With that in mind, we decided to conduct a survey last year to gather feedback from scientists (62% of survey respondents), managers, directors, and executives (26%), as well as IT and other professionals (12%) to better understand the R&D landscape.
Unsurprisingly, we found an overwhelming amount of survey respondents (70%) use up to ten different analytical techniques, as well as a variety of instruments and applications from multiple different vendors to collect and analyze their data. Not only that—once information is extracted after the analysis, a majority of respondents indicated that there is no one standard method used to share or record data. To make matters worse, survey respondents typically said they use up to four different methods to record data, including paper (56%) or internal PDF reports (74%), with the most common methods being paper documents (65%), conversations (55%), and images (55%). Data is scattered, unsearchable, and difficult to re-use. Most importantly, organizations cannot benefit from the millions they invest in analytical data generation—data that is used to make important decisions, every day.
In order to keep analytical data alive, scientists need a unified approach that manages data in a centralized place, which can be reviewed and re-interrogated should the need arise. A recent conversation with a customer resonates as I write this. While the frequency of analytical data needing to be re-interrogated/reviewed may be low, when the need does arise, it’s typically during high impact scenarios such as filing a response to a regulatory body or investigating an impurity in development/manufacturing. ACD/Labs understands how critical a universal approach to recording and sharing data is to an organization’s productivity, and that is why we developed ACD/Spectrus. This platform extracts knowledge from data sets across different instruments, software and techniques. No matter where the data is collected, ACD/Spectrus has helped scientists collaborate across departments, sites, and organizations to better communicate their findings and increase the speed and efficiency of the R&D process. With 70 percent of survey respondents agreeing that sharing data and interpretations between departments/partners is valuable to their organization – and more than 60 percent saying their organization should invest in additional analytical data management technology – it sounds like existing informatics technologies such as LIMS and ELNs have not successfully filled this gap. The increasing trend to outsourcing in the pharma industry is now highlighting the need for better data management strategies and systems within organizations.
Check out our infographic below to learn more about our survey findings and click here to discover ACD/Spectrus Platform.