The search for the ‘unknown known’

The Hugh Kaul Precision Medicine Institute will help build the interface of the Biomedical Data Translator, a “virtual brain” that will host all biomedical data in the world. 

Written by: Mary Ashley Canevaro
Media contact: Bob Shepard

Engineer control welding heavy automation with smart connection new technology in the future.The Hugh Kaul Precision Medicine Institute will help build the interface of the Biomedical Data Translator, a “virtual brain” that will host all biomedical data in the world.Across the globe, scientists are on a quest to find the “unknown known” — a term that Matthew Might, Ph.D., Hugh Kaul Endowed Chair and director of the Hugh Kaul Precision Medicine Institute at the Heersink School of MedicineUniversity of Alabama at Birmingham, uses to describe the phenomenon of scientific facts’ hiding in plain sight.

It turns out there are two kinds of hidden facts: 

  • Facts that were once known, published and now widely forgotten.
  • Facts that have never been stated or acknowledged, yet whose truth is an inescapable consequence of other known facts.

Many of these facts hiding in the unknown known have direct implications for diagnosing or treating individual patients — or for new approaches to entire diseases. 

In biomedicine, massive data sets exist independently; but an effective method has not yet been deployed to connect the dots from disease to data, to treatment, especially for rare diseases. According to the National Human Genome Research Institute, rare diseases impact between 25 million and 30 million Americans each year.

“There are billions of facts sitting around,” Might said. “We know there is new data on diseases and treatments, theoretically; but no one has made the deductions yet.”

Finding the unknown known through AI

A young, cutting-edge consortium project called the Biomedical Data Translator, funded by the National Center for Advancing Translational Sciences at the National Institutes of Health, aims to make those missing deductions through artificial intelligence.

The project is transferring all scientific data in the world into the Translator and developing an automated reasoning agent, a “virtual brain” that will reveal the unknown knowns of diseases and associated therapeutics. It is the first of its kind. To date, no comprehensive biomedical knowledge source of this size has been built.

Matt Might in meeting looking at computerThe PMI team experience with data bases and artificial intelligence tools will be a key to developing Translator.“The aim of the consortium is to render all available biomedical knowledge as interconnected knowledge graphs and make them accessible through standardized APIs, or application programming interfaces,” Might explained. 

A partnership between Beshenich Muir and Associates, LLC, and the Hugh Kaul Precision Medicine Institute has been selected by the NCATS as the recipient of the Biomedical Data Translator User Interface Program Award, a federal joint contract that will support the development phase of the Translator’s user interface.

The funding, $1.3 million per year for three years, will allow PMI and Beshenich Muir to hire several full-time employees to develop the user interface, in conjunction with the consortium’s development of the core Translator system and knowledge base.

Building on mediKanren 

Due to their previous work onmediKanren, a reasoning engine for biomedical knowledge created by Might, PMI is uniquely situated to contribute their expertise to the Translator project. Like mediKanren, the Translator project has one major ambition: to accelerate biomedical research. To do this, researchers and technologists will structure all scientific data, inputting it into the Translator. It will then be converted into accessible biomedical knowledge. Then the Translator can make deductions on its own using automated reasoning. 

Several data types will be considered for the Translator, including diseases data, symptoms, biomarkers, genes, clinical trial data, diagnostics and much more. Over the course of 20 years, milestones will mark progress: compiling data into the Translator, applying reasoning over the data and exposing the knowledge for other scientists and physicians. Once complete, the Translator can answer researchers’ unresolved questions, such as predicting a treatment for a specific disease or learning how gene variants respond to specific drug treatments.

To develop the Biomedical Data Translator, several teams have been or will be deployed to integrate extensive, currently available medical research data. NCATS has issued awards to project teams of experts from different leading universities and research institutions.

Might explains that, generally speaking, three types of teams work on the Translator: knowledge teams, reasoning teams and, now, an interface team.

Toward a data-driven future

Environmental head shot of Dr. Matthew Might, PhD (Inaugural Director, Hugh Kaul Personalized Medicine Institute; Professor, Internal Medicine), 2018.Matt Might, Ph.D., director of the Precision Medicine Institute.Might said the beta version of the Translator interface will not be immediately available to the general public; but “our hope is that, one day soon, even this beta version will begin helping translational scientists and physicians accelerate their work.”

PMI hopes to pull in scientists from varying fields, especially from UAB, to understand the types of questions they are trying to answer. “If we know what scientists are trying to deduce, it will inform how the user interface is built,” Might said.

Leveraging data with artificial intelligence tools will shape the future of medicine.

“I’m excited about this opportunity — I have seen how powerful this is in the context of our own patients,” Might said. “In some sense, I can imagine what will happen, but I am excited about the unknown known too — to sit back and watch what researchers will do when they have access to all this knowledge.”

The Translator UI Award is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health. Partners on the award include Elena Glassman, Ph.D., associate professor of computer science at Harvard University, and experts from Colorado University, Melissa Haendel, Ph.D., and Casey Greene, Ph.D.