Understand the scientific landscape with pharma insights generated from multiple disparate data sources

 

Request a demo

The challenge of seeing the whole picture

Finding the right information in a sea of structured and unstructured data sources is a real challenge. Important contextual information is often missed and there is insufficient time to spend on strategy development and decision making.

Unstructured data and document sources can cover a broad range of sources, such as literature, conference abstracts, medical liaison notes, news, social media, regulatory reports and more. Conventional scientific search methods can be very time-consuming and imprecise for targeted evidence review. Searching and combining information from many sources can be a repetitive process across therapy areas or topics of interest, which can lead to search fatigue and reduced staff productivity.

NLP text mining can extract the key facts, using relevant ontologies and focused queries, transforming data from different evidence streams into actionable intelligence for decision making. Capturing and integrating the information from a range of document sources can build a landscape of scientific, strategic and commercial knowledge, a pharma insights platform or “hub”.

Pharma insights in the hands of the business from molecule to market

The NLP Insights Hub integrates and transforms the information from a variety of document streams into easy-to-consume pharma insights dashboards. The Insights Hub allows you to see “the whole picture” and enables evidence-led decision-making, in a timely manner.

With the NLP Insights Hub you can:

  • Understand domain-specific landscapes
  • Optimize decision making
  • Spark innovation
  • Enable access to critical insights

An NLP Insights Hub provides visualizations and common search strategies created by domain experts and NLP data scientists to give users a head-start with their tasks.

Key Benefits:

  • Gain a holistic view of your product or therapy area through broad insights powered by truly integrated data sources
  • Leverage business targeted dashboards for quick and intuitive analytics and insights, e.g., for medical affairs insights
  • Identify an issue or question that is trending and take timely actions
  • Connect with systematic, comprehensive insight generation to assemble rich intelligence quickly
  • Extract concepts, relationships and context with bespoke results ranking methodologies
  • Focus and collaborate on key organizational initiatives without spending valuable time gathering and sorting through information
Overview of NLP Insights Hub - understand the pharma landscape

Key features

  • Pharma dashboards and visualizations are flexible and interactive, designed to answer your questions quickly
  • Focused NLP search queries, crafted by our experts, provide high-value domain-specific answers to pharma business questions
  • Self Service outputs reduce the process burden of requesting data analysis from other teams
  • Incorporating external and enterprise sources gives a complete picture from relevant textual data feeds
  • User-centric design speeds adoption and encourages usage
  • Role-based controls add a layer of flexibility and security

 

Pharma insights hub use cases

NLP Insights Hub use cases have been developed for discovery, development, regulatory affairs, commercial and more. Multiple data sources are integrated and combined to provide the necessary landscape of information to solve critical problems.

Innovation
Novo Nordisk are developing an innovation insights hub for Early Scientific Intelligence, to enable their R&D community to uncover innovative and new development potentialities. Combining data flowing from scientific papers, conference abstracts, patents, news feeds, and tech transfer offices from universities around the world. This provides an early view of potential opportunities for e.g. in-licensing or external collaborations, to improve their R&D pipeline.

Knowledge management across discovery and development
Merck developed a knowledge integration platform, SIM (selective information modules); with an automated NLP workflow to enable a federated search of external biomedical content in drug discovery and development, providing data for alerts and dashboards. (Published in McEntire et al (2016); https://www.sciencedirect.com/science/article/pii/S1359644616300757.)

Regulatory affairs
At GSK, the Biopharm Product Development and Supply (BPDS) integrate both internal and external regulatory information (e.g. RTQs, FDA Warning letters, BLA review reports), to capture changes in regulatory guidelines, requirements, risks etc. This Insights Hub supports Biopharma regulatory affairs, risk management and regulatory surveillance, providing targeted information on the changing regulatory environment globally.

Chaya Duraiswami, GSK, presented at Linguamatics TMS 2018.

HEOR evidence landscape
HEOR evidence landscape for IBD, Crohn’s, and ulcerative colitis across Latin America; project for top 10 Pharma to integrate sci literature, conf abs, CT.gov, FAERS; including Spanish, French, extract and dashboard key epidemiological metrics to assess unmet need and market potential.

Real world data
Real world data for 360˚ world view for a newly launched product for medical affairs and product teams.
Novo Nordisk US have built a cloud-hosted insights hub integrating a mix of MSL conversations, medical information requests from HCPs, literature, news, conference abstracts and social media.

 

COVID-19 NLP Insights Hub

The COVID-19 Insights Hub enables users to tackle short, medium and longer-term questions to confront the COVID-19 pandemic, such as:

  • Short-term
    What are the best potential drugs or drug combinations for repurposing efforts, or to treat critically ill patients? How can we find new candidates, and prioritise (with data on efficacy, safety, mechanism of action, and more)? How do I find recent trials, the most up-to-date research, the key opinion leaders and researchers in this field?
  • Medium-term
    What’s known about SARS-CoV-2 to enable vaccine development? Who in the population is most at-risk for severe disease? What are the key co-morbidities and are there therapeutics that can prevent COVID-19 impacting these populations? How can I track adverse events for relevant therapeutics and vaccines?
  • Long-term
    How will my patient population respond to current drugs, after COVID-19 infection? What additional care pathways are needed? What potential new chronic conditions will be seen in patients who have recovered from COVID-19 and how can we treat these?