Back in June of this year, I attended the ELNs, Data Analytics, and Knowledge Management (EDKM) Summit in Boston, MA. It was a very interesting get-together and the one discussion that stuck with me was triggered by the keynote presentation delivered by Kevin Gillespie of Momenta. Kevin talked about how to position knowledge management at the center of your laboratory informatics strategy. It really was an excellent presentation which triggered a fascinating discussion on whether it is even possible to “manage knowledge”. Kevin referenced the famous Peter Drucker quote, “You can’t manage knowledge. Knowledge is between two ears, and only between two ears.” This lead to one of Kevin’s conclusions, that the solution to the knowledge management problem is cultural in nature, not technological. John Trigg, who did a great job chairing the EDKM conference, added in his summary that, “Successful knowledge management is dependent on human factors applied to good information; technology is a bit player in KM.”

While I agree that human culture plays a huge role in an effective knowledge management strategy, I do think technology can play a bigger role, and certainly more than a bit part. Of course I may just being a naive vendor who believes their technology is the exception to the rule, but allow me the opportunity to explain.

In John Trigg’s summary of the EDKM, his second observation was, “The value of laboratory informatics tools will be realized when we are able to exploit the data repositories and extract meaningful information, leading to a predictive approach to laboratory science.” You see, this is what I believe ACD/Labs does. But before I go on to explain more about what we do, I want to say that the concept of knowledge management—this transformation of data to information to knowledge—is a daunting task. There are many different types of data and massive volumes being generated within and outside the walls of organizations at a pace that is very difficult to keep up with. This point really needs to be acknowledged in any discussion about global data and knowledge management. In an excellent publication authored by Thessen and Patterson they make the point that, “data cultures in life sciences are very heterogeneous, and no single approach can suit the needs of everyone. The most successful strategies are those that address needs in the context of sub-disciplines.”Do you believe it is important to build knowledge management strategies around different types of data, rather than taking a more universal approach to data and knowledge management?

At ACD/Labs,we focus primarily on the sub-discipline of analytical chemistry. Put simply, we are in the business of helping organizations increase their return on investment for the high cost of analytical data generation.

Each year, organizations spend millions of dollars on the generation of analytical spectroscopy, spectrometry, and chromatographic data (capital equipment, maintenance, FTE, consumables costs). We help these organizations get more return on their investment by providing quicker and faster access to the data, but most importantly by providing a platform that enables scientists to extract and capture the interpretation and knowledge gleaned from the data. The important point to emphasize is that we don’t just stop at managing or storing the data. Our capabilities and expertise for 20 years have been on the deep and intimate integration between ‘live’ analytical data and chemical structures and reaction-based schema. We believe by providing our customers with these “technological capabilities” they can employ them in a way that captures the link between data, the chemistry they are doing, and ultimately the key decisions they make based on this data.

We also take things one step further. I recently read an excellent book authored by Sir Ken Robinson called ‘The Element’. It is a great read highlighting many wonderful stories about how extraordinary people succeeded in life by finding their “element”. Robinson points to the definition of intelligence as the “capacity to acquire and apply knowledge by means of thought and reason.” To this point, the thing that makes ACD/Labs unique is our ability to capture the knowledge of the scientist as described above and create a more intelligent environment for them to work in through predictive approaches to laboratory sciences. While ACD/Labs has evolved over the last 20 years as a desktop and point solutions provider to a laboratory informatics provider, our very foundation and perhaps our most noteworthy accomplishments to dateare highlighted in our development of sophisticated, state-of-the-art scientific algorithms for things such as NMR prediction, Mass Spec fragmentation, physicochemical property prediction, chemical naming, etc. For many of our clients, the performance of these algorithms has been improved and enriched over time based on a focused knowledge management strategy to feed knowledge, interpretation, and information about novel compounds into the system. As a result, as more interpretations, assignments, and observations are shared within the ACD/Labs environment, the more accurate these predictions and evaluations become. This strategy has served as the background to success stories at Lexicon Pharmaceuticals, Eli Lilly, and Janssen Pharmaceuticals, creating a more intelligent laboratory environment for their scientists to operate in.

Would scientists in your organization benefit from access to and leveraging of analytical knowledge rather than raw data captured simply for IP and regulatory purposes?

I am really thrilled to share this webinar with a colleague and friend, Steve Thomas from GSK, who will show a terrific example of how the GSK DMPK group is efficiently re-using ‘live’ data in a corporate environment and capturing knowledge in a repository that, in Steve’s words, “doesn’t forget, doesn’t go senile, doesn’t retire and doesn’t leave the company for a competitor”. Steve has a great story to tell that emphasizes how his DMPK group turns structural data into knowledge, but more importantly is a strategy not strictly focused on data management, but the knowledge of metabolites and their outcomes. I am really looking forward to hearing Steve tell the story on the Business Review Webinars stage to expose it to a wide and diverse audience who are interested in a novel approach to knowledge management.

Please also take a look at ACD/Labs’ white paper entitled ‘Unified Laboratory Intelligence‘. Creating an intelligence-from-information ‘live’ cycle enables scientists to search, retrieve, and reuse unified chemical content with context throughout R&D, process development, and manufacturing for better chemical identification, characterization and optimization, improved productivity, and increased returns.