NEW YORK (GenomeWeb) – Recently, Linguamatics released a new version of I2E, its natural language processing text-mining platform, that includes several new features designed to make it easier for healthcare and life sciences customers to search for and incorporate information from text more accurately and efficiently.

The company has also begun testing a new community site that will provide a forum for people within the pharma and life sciences community to exchange ideas, share best practices, and text mining strategies. In October, the company launched an early-access program for the site at its annual user meeting.

Version 5.0 of the software features tools for normalizing concepts such as gene mutations and improved search features designed to help users find key information in unstructured texts and allow large quantities of data to be processed in a more automated fashion. The release also includes a new query language called the Extraction and Search Language, EASL, — previously available in beta — that allows text mining queries to be described and written in a human-readable text format. EASLs can be generated outside the I2E platform, and support custom interfaces and enhanced workflow automation.


Other highlights include industry recognition for leadership in NLP healthcare solutions

Cambridge, UK & Boston, USA – January 25th, 2017 –Text analytics provider Linguamatics today announced that 2016 represented one of the company’s most successful years ever, further positioning the organization as the leading provider of Natural Language Processing (NLP) text mining solutions for healthcare and the life sciences. Highlights from the past year include the highly-anticipated I2E 5.0 release; the addition of further high-profile customers and strategic partners; and industry recognition from leading research firms KLAS, Forrester and Frost & Sullivan.


I am pleased to announce that the Linguamatics Community is now open for registration for all Linguamatics I2E users.

Peer-to-peer support and networking forum - discuss the software, as well as share queries and scripts.

Share I2E best practices - through forums, articles, blogs, videos, and presentations. You can find over a hundred Hints and Tips posts, how-to video tutorials, and customer case studies.

https://community.linguamatics.com/

Download Linguamatics software, resources and technical documentation - content previously accessed on I2Edia and the Download Site is being migrated to the Community, so your login gives access to everything you need from Linguamatics.

SIGN UP NOW


At the end of 2016, I attended the CBI 2nd Annual IDMP Update Forum in Philadelphia, a small but highly focused and effective conference with two days of meetings and discussions. There were presentations by industry leaders involved in understanding and addressing the challenges that IDMP compliance presents to the pharmaceutical industry, and also presentations by some of the vendors in this area.

The meeting kicked off with a keynote from John Kiser, Senior Director, Regulatory Policy and Intelligence, AbbVie.  This brought up some of the key challenges for IDMP compliance that were repeated again and again across the conference:

  • We need to think strategically, about master data management (MDM), not just about what is needed for IDMP compliance.
  • Even though the timelines are moving out, it’s really important not to take our eye off the ball. IDMP projects are being driven out of EU, and the US has to get moving to keep up. Don’t wait, start planning and kicking off pilots and proof-of-concepts with vendors now.
  • IDMP compliance planning shouldn’t just involve regulatory affairs and supply chain departments, as IDMP will impact quality, clinical operations, pharmacovigilance and safety, production, IT and more.

How text analytics using I2E can help

One comment that interested me was that while manual curation may provide the data elements for the current understanding of Iteration 1, other strategies will be needed to deal with potential changes in the implementation guidance, and to accommodate the flexibility required for Iteration 2 and beyond.


“It is easy to lie with statistics. It is hard to tell the truth without it.” -Andrejs Dunkels

This is a quote I first heard long ago, but was recently re-introduced to by a beloved colleague of mine. Anyone with a background in research can attest to just how true this quote is. Without good statistical power, life-saving pharmaceuticals never make it to the market. Undoubtedly, the ones that do, do so at a hefty cost. In 2012, Forbes.com published an article reporting that the average cost to develop a new pharmaceutical was $4 Billion, and could reach upwards to $11 Billion, staggering numbers, and that was 4 years ago[1]. Without any hesitation, I can confidently say, “those numbers aren’t going down.”

But WHY do pharmaceuticals cost so much?

There are genuine factors that contribute to these huge costs, and one of the most expensive phases of drug development are clinical trials. Those of us that have worked in research know that clinical trial recruitment is a huge factor that takes an exorbitant amount of time and money. If you don’t get enough eligible people successfully recruited, and finished in the study, the study won’t have the all-powerful “n”, the number of people that statistically is needed to prove that the study drug was safe and effective (or not).

How can Natural Language Processing (NLP) help in recruitment?