Quertle: Simplifying Biomedical Literature Discovery Using AI-powered Text Analytics

Jeffrey D. Saffer

Quertle is an artificial intelligence company focused on text discovery and understanding in the biomedical and life sciences fields. Published information is the foundation for the entire healthcare industry – from basic research to drug discovery to clinical trials to healthcare delivery and everything in between including business aspects. Quertle’s flagship product Qinsight™ enables unparalleled discovery of literature through AI-powered searching, integration, organization, and presentation including predictive visual analytics. Qinsight, which covers journal articles, patents, clinical trials, treatment protocols and much more, is in use by pharmaceutical and biotechnology companies, universities, research centers, and healthcare providers around the world.

Quertle was founded by Jeffrey Saffer and Vicki Burnett – Ph.D. biomedical scientists who were frustrated with the inefficiencies in discovering critical publications and the waste caused by missing information. For the pharmaceutical business alone, the impact of missed information causes hundreds of billions of dollars every year.

Dr. Saffer and Burnett throughout their careers as bench scientists had each engaged in many analytical and computational projects. They were solving biomedical big data problems before big data got its moniker. With that experience and the critical perspective of what biomedical scientists needed, they embarked on an effort to reinvent literature discovery.

Saffer and Burnett recognized that keyword searching could never achieve what was needed and that methods like natural language processing were insufficient to accomplish the required insights. Hence, they embarked on an ambitious effort to build an AI-powered application using algorithms they developed specifically for the problems in literature discovery. In 2009, they launched a beta application that served as a training platform for AI, with the first production application Quetzal® becoming available in 2016. Then, with the addition of AI-powered predictive analytics, Qinsight was launched a year later.


Meet the Transformational Leaders

Co-founders Saffer and Burnett have been strong proponents for improved use of information in the biomedical and life sciences for many years. Both have been at the forefront of advocating for modern analytical methods as well as being highly active in creating needed solutions. Saffer’s first company, OmniViz, revolutionized the use of information visualization methods for the industry, with Burnett a major contributor to that success.

Now, as the co-founders of Quertle, Saffer and Burnett continue those efforts and have been the sole inventors of Quertle’s biomedical literature-specific artificial intelligence algorithms. They also continue to advocate for the use of field-specific artificial intelligence in the industry and for their company.


Solving a Critical Need in Healthcare

Quertle’s use of artificial intelligence – built specifically for biomedical literature discovery – serves as an example for the industry of the need to customize the underlying AI methods to more effectively solve unique problems. The result of this approach, Qinsight, is now enabling Quertle’s customers to more deeply discover critical information in far less time. Qinsight is uncovering otherwise hidden information that minimizes risks in the pharmaceutical industry – positively impacting billion-dollar decisions. Besides, with speed to market being so critical, Qinsight shortens multiple steps in the pipeline enabling products to get to market months earlier.


AI Driving Innovation in Healthcare

Artificial intelligence approaches are already impacting innovation in healthcare. In regard to finding critical documents (text AI), Quertle progressed beyond keyword searching and beyond what natural language processing alone can do. AI can power deeper, faster discovery and enable intuitive exploration where information relevant to the user’s needs can be updated in real-time by the AI methods. In addition, AI-powered visual analytics can provide insights not obtainable by any other method. For example, predicting trends and interactions within biological systems require advanced analytical methods. With millions of new documents published every year, only AI can discover much of the critical information needed.


Gaining Perspective Through Skills and Interactions

Quertle’s innovation is driven by the critical biomedical perspectives provided by its founders. All too often, AI or data science experts have tried and failed to solve similar problems – largely because the nature of the issues and the path to the successful application requires a deep understanding of the life and biomedical science fields.

These critical perspectives also come from deep interactions between Quertle and its customers. As a partner to its customers, the company listens to their needs and with the founders’ field-specific knowledge can understand the issues, thus enabling constant adaptation to ensure Quertle’s solutions are relevant to the market. These interactions are central to driving innovations in Quertle’s applications.


Valuable Accolades and Testimonial

For its innovations in gaining value from the biomedical literature, Quertle won an award from the US National Library of Medicine. Also, the company was named a Top 10 pharmaceutical analytics solution provider in 2017 and a Top 10 Most Innovative Big Data solution provider in 2018. But it is the accolades from their users that best represent the value that Quertle provides.

For example, Alain Rinaldi, Chief Medical Officer for Overlord Pharmaceuticals said, “Qinsight provides me amazingly relevant information and saves considerable time in my searches.” This kind of enthusiasm from users is reflected in Qinsight being adapted in many pharmaceutical and biotechnology companies.


Insights into the Future

Jeffrey believes artificial intelligence is rapidly becoming essential across the entire range of healthcare activities. The drivers for this transition are two-fold: (1) the volume of data ranging from published information to research data to business intelligence to patient health records and (2) the continued recognition that personalized, or precision, approaches are needed for each patient. As a result, AI-powered big data analytics are critical elements in progressing toward healthcare breakthroughs. AI is expected to be used in every aspect and in ways that people do not even envision today.