Data Standardization in Analytical Chemistry: From Novelty to Necessity in 2018 and Beyond

The Word is Out: ACD/Labs and C&EN Survey Shows State of Analytical Data Management in 2018

By Sanji Bhal, Director, Marketing & Communications, ACD/Labs

Analytical data plays a critical role in R&D by supporting critical decision-making on a daily basis. Whether a synthetic chemist is looking to see if their reaction yielded the product they expected, a group of scientists in development are building an impurity control strategy, or experts in manufacturing are collecting data for regulatory submissions, applications of analytical data are ubiquitous. At a time when the volume of insight-rich data one can gather is extraordinary, chemists working in academic research, industry, and non-profit organizations alike face regular challenges in managing and sharing their data.

In 2015 we disseminated an industry survey, first at Pittcon and then through various industry channels, to gain an understanding of the obstacles scientists face in working with and managing their analytical data. We reported the results of that survey in a previous post titled ‘Survey says…analytical data management is still a pain’. Interestingly, over the last 6-8 years we’ve found that R&D organizations are increasingly seeking solutions to help manage and share their data. As such, when I bumped into folks from Chemistry &Engineering News (C&EN) at the American Chemical Society (ACS) Fall meeting in Washington D.C. last year we got talking about surveying researchers once more to see how much the landscape had evolved. Earlier this year the stars finally aligned and we commissioned a second survey to update our understanding on the state of scientific analytical data management. We wanted to know if researchers feel they now have the tools to sufficiently share, manipulate, and retrieve data, and if they are confident in its integrity.

Image001After gaining the perspectives of 731 individuals working in various capacities, from academia and nonprofit organizations to government agencies, we came to the conclusion that the state of analytical data management in research and development remains complex; while the situation is evolving, many are still struggling. In addition to pinpointing the core issues researchers face in data management strategies, our survey showed that companies are looking for solutions that help them integrate data from various analytical sources while also allowing them to accurately and securely share data with coworkers and outsourcing partners.

In terms of the specific challenges related to analytical data management, below is a synopsis of some key findings from the survey:

Reviewing and interpreting data remains inefficient

Our results showed that 66 percent of respondents want improvements in data manipulation, processing, interpretation, and analysis in their laboratories. When asked how results from experiments are typically analyzed the most popular responses were 66 percent noted they typically review data at the instrument with software provided by the vendor, 38 percent use a separate data management system, while only 28 percent access data from a central repository. While reviewing data at the instrument was the most popular choice among respondents, this practice can be costly to organizations as instrument time is valuable and using it to review and reprocess data is inefficient. As individuals increasingly work with collaborators and colleagues in different time zones, departments, and organizations (due to greater outsourcing) teams must adopt solutions to maximize knowledge sharing. While only 28 percent of participants use a central repository to analyze data, we at ACD/Labs believe organizations would benefit tremendously from this approach. We are lucky to have witnessed many examples of improved efficiency first-hand, through empowering numerous customers with a single, searchable repository to maximize productivity and accelerate decision-making.

Assembling data can be complex

The majority of respondents were not fully satisfied with their existing software products for analytical data management and interpretation. Our survey showed that the inability to easily move data and the need for error-prone transcription are major concerns. The lack of effective, integrated tools for analytical data management mean that using paper to share results with colleagues is an unfortunate reality for many. As you can imagine, it’s impossible to efficiently distribute data in this manner, or to share information that resides in others’ minds.

Dealing with various datasets is also problematic to researchers who lack the tools to analyze multiple types of data at once. In fact, 84 percent of respondents claimed they use two or more techniques on a regular basis. Steven Hollis, retired scientific director at Amgen, stated that he and his organization struggled with analyzing NMR, mass spectrometry, and HPLC data all at once using older systems. After implementing ACD/Spectrus software, scientists were able to seamlessly merge the data in one record, thereby simplifying the process.

Researchers want assurance that data is accurate, consistent, and secure

Accurate, consistent, and secure data is a more lengthy way of referring to data integrity, which has been a hot topic in our discussions with customers and prospects over the last 18 months. When prompted to share their experiences and opinions on this topic, 80 percent of respondents agreed that data integrity was important or very important, but only 25 percent admitted working in an organization that is actively undertaking data integrity initiatives, and 33 percent of respondents had no plans to address this challenge. For organizations launching data integrity efforts, 79 percent of respondents are focused on standardizing methods and processes, while 43 percent are investing in informatics solutions.

For topics such as these, there is a clear division not only between industry and academia, but also based on roles. The majority of data integrity initiatives, whether planned or underway, appeared to be in industry –particularly Pharma/Biotech, where this issue was also of greater concern to those in development over discovery. This is hardly surprising since these organizations are subject to rigorous regulatory requirements, which only increase as products get closer to human administration.

While human error is inevitable when manipulating data, reducing or eliminating transcription errors is an easy win. In our experience data transcription is often driven by the need to transfer results between systems because decision-making requires assembled data. ACD/Labs understands the need for a universal approach to recording and sharing data, which is why organizations have relied on our informatics solutions to maintain data integrity for the past 20 years. As researchers seek assurance of data accuracy, we look forward to continuing to work with them to meet the existing and emerging challenges of chemical and pharmaceutical R&D.

To learn more about our survey findings, check out our infographic and click here to access the full report.

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