There’s a Clay Shirky quote I like, that focuses on the importance of communication: “When we change the way we communicate, we change society”. There are so many different ways of communicating these days, with web meetings, calls, email, skype, twitter, and more. Indeed, global communication has never been easier, and making connections with colleagues, collaborators and customers across the world can be carried out from wherever we find ourselves, from our desks, coffee shops, airport lounges or even remote resorts. While “thinking global” is often almost taken for granted these days, it’s important to keep in mind the power of local networks and face-to-face human interaction. 

At Linguamatics, we are fortunate to be based within one of Europe’s key technology clusters. The Cambridge technology cluster includes many different networks engaged in research and development in vital areas including genomics, personalized medicine, rare diseases, big data technologies, and more.  

Linguamatics has recently become affiliated with the Milner Therapeutics Consortium, a new network dedicated to the conversion of basic science into therapies. Its mission is to accelerate academic research towards medical advancement by forging close collaborative interactions with industry. 


With new and exciting technologies, it often happens that one particular application or use case leads the way initially… and then, when the euphoria turns into commercial reality, people start looking at other applications where the new technology can also bring value. In text mining, the same holds true. Pharma companies have now been using NLP text mining technologies for many years, in areas such as target validation, gene-disease associations, clinical trial optimization, and patent analytics, for example. As they become comfortable and, indeed, expert in these areas, attention has turned to areas where the core technology needs to be adapted or tweaked to meet a specific requirement.

For example, when looking to apply NLP to the time-consuming and costly business of discovering new, novel compounds, users hit a significant issue; trying to understand every single component part of some of the long chemical names. Not an insurmountable problem, but one that needed time, expertise and determination.


Linguamatics hosted our Spring Text Mining Conference in Cambridge last week (#LMSpring16). Attendees from the pharmaceutical industry, biotech, healthcare, personal consumer care, crop science, academia, and partner vendor companies came together for hands-on workshops, round table discussions, and of course, some excellent presentations and talks. 

The talks kicked off with a presentation by Thierry Breyette, Novo Nordisk, who described three different projects where text mining provided signficant value from real world data.  Thierry took the RAND Corporation definition: "Real-world data (RWD) is an umbrella term for different types of data that are not collected in conventional randomised controlled trials. RWD comes from various sources and includes patient data, data from clinicians, hospital data, data from payers and social data."

At Novo Nordisk they have gained business impact by text mining a variety of souces, including: social media to find digital opinion leaders; conversation transcripts between medical liaisons and healthcare professionals for trends around clinical insights; and mining patient & caregiver ethnographic data to see patterns in patient sentiment and compliance.


The Linguamatics Booth #345 at this year’s Bio-IT Conference (April 5-7 in Boston) offers the ideal opportunity to catch up with the latest developments in text mining.

Here are 3 reasons to meet the market leader in text analytics for life science and healthcare:


Guy Singh, Linguamatics Senior Manager, Product and Strategic Alliances, explains the key differences between keyword search and text mining.

See the full 52 second video below.

 

To learn more about how text mining works, check out our other video resources: