Posts from February 2017

Varian to leverage Linguamatics NLP text mining within the 360 Oncology care management platform

Cambridge, UK & Boston, USA – February 20th, 2017 – Clinical NLP provider Linguamatics, and Varian Medical Systems, today announced that Varian will utilize Linguamatics’ natural language processing (NLP) technology as part of the data analytics within Varian’s 360 Oncology™ care management platform.

Varian 360 Oncology care management is a software solution designed to meet the full spectrum of needs in oncology care management for hospitals and cancer centres at the oncology department level. It is capable of tracking physician and cancer specialist referrals, integrating evidence, outcomes data, guidelines and care pathways, coordinating data from multiple sites and settings including patients and external caregivers. Varian will utilize the Linguamatics Health platform, powered by Linguamatics I2E text mining technology, to extract unstructured concepts from within pathology reports and convert them to discrete data elements for analytics reporting within Varian 360 Oncology.


Clinical Trials text mining can speed key decisions, effective site selection and trial design 

Clinical trials form the cornerstone of evidence-based medicine, and are essential to establishing the safety and efficacy of new drugs. Each new drug, before being approved by regulatory agencies, must pass through a set of gates. At the very basic level these include phase 1 for first-in-human safety; phase 2 for efficacy and biological activity against the target; and phase 3 for safety, efficacy and effectiveness of the new therapeutic.

At each of these phases, careful planning is essential for a successful study. The clinical study protocol covers objective(s), design, methodology, statistical considerations and organization of a clinical trial, and ensures the safety of the trial subjects and integrity of the data collected.

Over recent years, clinical trial designs and procedures have become more diverse and more complex. The impact of precision medicine means trials have to be more carefully planned to ensure adequate statistical power for smaller patients groups, and adaptive, umbrella, basket and n-of-1 trials are now more frequent.

The regulatory requirements and growing complexity of clinical trials translates into more numerous and more complex eligibility criteria for study enrolment, increased site visits and required procedures, longer study duration, and more rigorous data collection requirements. From: PhRMA Biopharmaceutical Industry Profile 2016


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.


Reading some of the FDA blogs review, I was interested to read that "for the second consecutive year, [the FDA] approved more drugs to treat rare diseases than any previous year in our history." This is great news for the patients affected by these rare or orphan diseases, and there is of course potential for applications of such drugs and the knowledge around these diseases across the wider population and in broader healthcare.

Text analytics can play a part in developing better understanding around the biology of these rare diseases. There's a great example of this application of text mining from Madhusudan Natarajan at Shire Pharmaceuticals. Shire develops and provides healthcare in the areas of behavioural health, gastrointestinal conditions, rare diseases, and regenerative medicine, and Madhu has presented his research using text analytics to uncover disease severity and genotype-phenotype associations for Hunter Syndrome (also known as Mucopolysaccharidosis II).

We hosted a webinar with Madhu, and in this webinar, he illustrates some of the challenges for R&D for orphan diseases, particularly around text mining for mutation and variant patterns, which can be reported in so many different ways in the literature. 

Webinar: A systematic examination of gene-disease associations through text mining approaches