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Finding the missing pieces of the puzzle

I think one of the most-used phrases of 2020 is “these are unprecedented times.”

I did hear another phrase recently that I liked: it is a “dark privilege” to be living through this global pandemic. No doubt, we live in an interesting time! In decades to come, people will talk about 2020 and the impact of coronavirus on so many global factors – economy, climate, travel, and of course population and individual health. As well as the dark clouds, there is of course light – and much light comes from the collaborative efforts of institutions, healthcare organizations and governments to find the best responses to this challenge, particularly in the areas of drug repurposing and vaccine development.

And this, to me, is where natural language processing-based text mining comes in. Whenever scientists, researchers and clinicians are faced with a challenge, one critical asset is identifying as much information about the problem as possible. Whatever information there is, locally and globally, that can be found, gathered and understood, will enable the right decisions to be taken. Relevant information on the biology of SARS-CoV2, from COVID-19 as a disease, patient demographics and co-morbidities, global or regional spread, and possible drugs that might treat the symptoms and impacts of this disease is all just the tip of a data iceberg. Much of this data exists in unstructured text: scientific papers, preprints, clinical trial records, adverse event reports, electronic healthcare records, even news feeds and social media can all provide information on epidemiological factors, for example.


Pharmaceutical leaders, from therapeutic experts to medical affairs directors, face challenges staying abreast of the latest development and research – leading them to spend significant time searching for information, rather than driving strategy and direction across the organization. As a result, they sometimes end up making decisions without having the full picture – potentially compromising innovation opportunities or delaying a response to competitive forces.

In an ideal world, leaders should be able to focus on key initiatives for their teams and organizations, rather than spend valuable time gathering and sorting through information. They need access to information that delivers the full view of their product or therapy area landscape.

The NLP Insights Hub is the latest evolution in our NLP technology offerings, designed to help pharma professionals solve their data deluge challenges. The NLP Insights Hub provides an end-to-end offering for business users, combining core NLP to extract critical information from text, with the power of dashboards to bring the data to life and enable understanding. Bringing together the key pieces of information from a wide range of structured and unstructured data sources in one hub, with visual analytics on top, enables efficient insights development, sparks innovation and optimizes decision-making.


We rely on obtaining as much information about a topic as possible to mitigate risk and unknowns in business and in our daily lives.  That knowledge becomes the backbone of our decision support. The trouble is, there is so much information produced daily, that in our hectic lives we can rarely go through it all, let alone sift through the information to only focus on pertinent knowledge to retain.  But are you finding the most up-to-date information? Is the information you are relying on for your decision support, years or even decades old?

Decision support straight to your inbox

Linguamatics NLP provides an Alerting capability to reduce the time required to review and provide results that are appropriate to your needs. Alerting allows you to schedule NLP search queries to be run at desired intervals, whether it is monthly, weekly, or even daily to keep up-to-date with your newest indexed information. 

This knowledge can be delivered via email to an individual or groups with the most recent and relevant information at your fingertips at all times. This broadens the benefits gained from an NLP approach – recipients of these emails can be across the organization, not just Linguamatics hands-on users.

The range and application of the alerting can be as broad as you need. You are not limited to one question but can schedule as many query alerts as you would like, to differing groups of recipients, as appropriate. This flexibility enables many different groups (e.g. different therapeutic area leads, medical affairs teams, safety assessment groups, to name but a few) to keep up-to-date.


Cambridge Healthtech Institute and Bio-IT World have awarded Roche a 2020 Innovative Practices Award in Focused Research for their use of the IQVIA Linguamatics Natural Language Processing (NLP) platform to glean patient insights from social media to improve clinical trial design.

Each year, Bio-IT World highlights outstanding examples of technology innovation in the life sciences. The Innovative Practices Awards are designed to recognize partnerships and projects pushing the industry forward, by sharing strategies that can be implemented across the industry to improve the quality, pace, and reach of the life sciences.

NLP over social media identifies clinical endpoints relevant to Parkinson’s disease patients

Bio-IT World judges selected Roche in the patient-focused research category for its work to discover if social media, particularly patient blogs and forums, can provide a good substrate to develop clinical endpoints relevant to Parkinson’s disease patients. Roche researchers established a series of NLP-based text mining queries to analyze patient discussions around Parkinson’s. The study identified symptoms confirmatory of the clinical trial endpoints, and also revealed new symptoms; a number of which have been added to the conceptual disease model used in the clinical trial.


Early Scientific Intelligence pipeline gives 360 degree view of “novelty” in diabetes and obesity

We hear a lot these days about evidence-based decision making. Particularly in the current climate, it’s critical that governments, businesses, health organisations and individuals are guided by facts and evidence, not fiction and hearsay. But what do we really mean by evidence-based decision making? Ideally, before making any decision, you want to be able to gather all relevant information, synthesized from different relevant sources. This approach allows you to see the overall picture, drill down to details, understand and weigh up the evidence and therefore make the best decision possible.

Creating a hub of evidence

Getting a comprehensive view of the whole picture is something Linguamatics pharma and healthcare customers need for their decision making in many different arenas - and that often means being able to integrate information from unstructured textual data streams together with data from structured sources. Capturing and integrating the information from a range of document sources can build a landscape of knowledge, a “hub” of evidence. Evidence hubs can be developed for discovery, development, regulatory affairs, safety, patient risk; with input data sources and output dashboards or alerts tailored as needed.

Novo Nordisk are using this integrated approach for an “Early Scientific Intelligence” evidence hub. Sten Christensen & Brian Schurmann (Novo Nordisk) presented on this innovative project at our virtual NLP summit on Thursday 4th June 2020.