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European Biopharmaceutical Review

Data Mine

The latest evaluations of the pharmaceutical industry reveal a decline in performance that can only be reversed by making significant changes to research and development methods. Effective information management is a particular problem, with researchers forced to waste a great deal of time sifting through massive amounts of information, delaying drug development.
However, good informatics solutions that can assist with pharmaceutical data mining and analysis do exist. Offering features that address researchers’ greatest needs, these dedicated discovery engines support the drug development process. In this article, we focus on both the characteristics and advantages of the ideal research informatics tools.

Overwhelmed By Data

Many recent assessments of the pharmaceutical industry have concluded that it is failing to meet expectations, with some insiders suggesting that productivity is on the decline (1,2). The question is, what can be done to defeat this worrying trend? Experts believe that the only truly effective way to see productivity rise is to make significant changes to R&D methodology and approaches to information management (3-6).
Many specific issues have been flagged up as the most critical problems – most notably, a massive information flow made more daunting because of the lack of integration of efficient informatics research tools (5-8). The information flow can simply be overwhelming for drug discovery researchers, confronting them with – as a PricewaterhouseCoopers report describes – data that is often unstructured and hard to search (9).
The result of having to wrestle with all this information is that researchers spend far too much time collating heterogeneous data and cross-disciplinary information (1,7). And the more time that is spent on fundamental data mining and analysis, the less time a lab will have to focus on its main goal – identifying leads and pursuing drug development.

Data Into Insights
While easy access to accurate and reliable data sources is crucial for modern research, it is not enough – researchers also require an interface that enables them to efficiently convert information into actual knowledge (5,7,10). Arjun Bedi, who specialises in working with major pharmaceutical companies on strategic business transformation initiatives, calls this conversion D2i, or ‘data into insights’ (5).
The simple fact is that it is very difficult to gather insights from the data without the help of dedicated informatics solutions (5). It was estimated in 2010 that labs in big pharmaceutical companies were producing more than 20 terabytes of data each day – a figure that has surely risen in the ensuing years (1). With these massive collections of data growing by the minute, informatics solutions are clearly needed for any pharmaceutical company that wants to remain competitive.

Data Management Solutions
Fortunately, dedicated data mining and analysis solutions are out there, and they can provide vital support for handling the constant flow of information. These research informatics solutions provide specific database access and interface design tailored to the pharmaceutical industry, offering features that support drug development by functioning in alignment with the particular needs of researchers.
The very best data management solutions are created with the assistance of experts who work in the target fields. It is important that they cover a variety of disciplines and focus on data to insight conversion. Recognising the trends and need for change in pharma’s approach to information management is key.

Ideal Characteristics
An ideal informatics solution must be capable of crossing boundaries between many scientific fields, because drug discovery is an interdisciplinary process (1). With labs located around the globe, multinational companies must deal with the reality that not all of their researchers are necessarily applying the same methodologies.
Additionally, when multinationals acquire new companies, the process of integration does not always homogenise the data output from each acquired facility. This means that there could easily be problems with ambiguities in terms and terminology, causing confusion and slowing down research (1). By making a serious investment in research informatics with D2i capabilities and an understanding of multiple disciplines, companies could head off these issues much more effectively (5).
The ultimate goal in choosing a research solution is to find a tool that will help R&D facilities make more informed assessments of their drug candidates (11). A solution that focuses on data for preclinical, clinical and post-release safety, pharmacokinetics, metabolising enzymes and transporters is highly valuable.
If researchers can use their informatics solutions to easily access regulatory precedents and comparative drug data, that allows them to better support decisions about the pipeline and to discover potential biological effects of various drug candidates. Functionalities such as the ability to search drug name or class, drug target information, and adverse effects or toxicity can prove particularly helpful, offering multiple possibilities for approaching data.
There are specialised features worth seeking out, such as those that allow researchers to perform very specific data analysis, enabling them to achieve more in a shorter amount of time. For example, query construction and result filtering make it possible to identify the effects of single or multiple variables on a drug’s performance, allowing the impact of factors, such as changes in time and dose, to be properly assessed. PharmaPendium, for example, is one such tool, connecting users to valuable data sourced from the Food and Drug Administration (FDA) approval packages from 1938 to the present, as well as the European Medicine Agency’s (EMA) European Public Assessments Reports, plus millions of pages of drug reviews (for example, AERS and Meyer’s Side Effects of Drugs), and full studies from medical and drug development journals. By having access to all of this data, researchers can make more informed decisions regarding whether or not to progress a candidate to clinical trials.

Regulatory Barriers

A solution that includes drug-enzyme and drug-drug interaction data provides better risk assessments related to late-stage drug failures resulting from changes in drug bioavailability or unanticipated adverse events. The regulatory approval process can be a ‘rate-limiting’ step in drug development, and even the FDA has indicated that effective research informatics resources are crucial in the medical research process (10).
When drug developers have access to FDA and EMA data – much of which has often gone unpublished in academic journals – they can more quickly locate regulatory precedents to support submissions and evaluate the issues that similar candidates have previously encountered during the development process.

Identifying Compounds
Another informatics solution that could prove highly valuable to pharmaceutical researchers is one that focuses on identifying lead compounds and opportunities for drug repurposing. Tools with this ability can assist in selecting the best candidate compounds before moving on to the preclinical phase. This offers a significant advantage for pharmaceutical companies because it can mitigate the financial risk of later-stage preclinical and clinical studies on compounds that are likely to fail.
Particularly desired functions for such a solution would be an interface that allows text or graphic input (for structural searches) and the ability to filter search results by multiple categories (such as compounds and fragments by name, structure and structural similarity). Reaxys Medicinal Chemistry – which covers millions of chemical compounds and thousands of proteins, acting as drug targets and aligning them with the results of biological experiments – is one such solution that provides researchers with these abilities.

Designed for specific researchers with their tasks and needs in mind, informatics solutions – that have the characteristics described above – can power the research and development work of large pharmaceutical companies. The right combination of informatics solutions can also help in overcoming the discipline barrier that often exists between researchers who are approaching drug development from differing academic backgrounds.
There has been a shift in the R&D landscape, making the need for smart tools to manage an overwhelming information flow more critical than ever before. If they hope to make major return improvements on R&D investments, pharmaceutical companies urgently need to seek out and implement superior research information solutions.

PharmaPendium® and PharmaPendium® trademark are owned and protected by Reed Elsevier Properties SA. All rights reserved.

1. Anriban G et al, Leveraging research informatics to accelerate drug discovery, 2010. Visit:
2. Goodman M, Market watch: pharma industry strategic performance 2008-2013, Nature Reviews Drug Discovery 8: p348, 2009
3. Ruffalo RR, Why has R&D productivity declined in the pharmaceutical industry? Expert Opinion on Drug Discovery 1: p99, 2006
4. Garnier JP, Rebuilding the R&D engine in Big Pharma, Harvard Business Review, 2008
5. Bedi A, Effects of the emerging pharmaceutical R&D model on informatics, Drug Discovery and Development, 2011. Visit:
6. Robertson G, Small molecule drug discovery: why we need a paradigm shift, 2011. Visit:
7. R&D efficiency, Tuft Center for the Study of Drug Development, Tufts University, 2009
8. Nicholaides D, The changing shape of pharmaceutical R&D, Chemical Innovation 31(11): p40, 2001
9. An industrial revolution in R&D, PricewaterhouseCoopers, 1998. Visit:
10. The sentinel initiative: a national strategy for monitoring medical product safety, US Department of Health and Human Services, FDA, 2008. Visit:
11. Visit:

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About the author

Pooja Jain is a Product Manager for PharmaPendium, Elsevier Life Science Solutions. She has over 10 years of research experience working in academia and the pharmaceutical industry. Pooja’s experience includes working at Mimetogen Pharmaceuticals, Eli Lilly and Hepregen. She obtained her MSc degree in Experimental Medicine from McGill University, and her MBA from Boston College.
Pooja Jain
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