When Americans hear the word “bioterrorism,” they may be reminded of the series of anthrax attacks that followed in the wake of September 11, infecting twenty-two people and killing five. Exposure to toxins produced by that bacteria can prove fatal in as few as three days after the start of symptoms, and these often appear no more serious than a common cold.
Today, the Defense Threat Reduction Agency, or DTRA, is leading a proactive effort to ensure a fast, effective response to any future bioterrorist attacks. With $1.7 million in newly awarded funding, a research team at the Biocomplexity Institute of Virginia Tech’s Nutritional Immunology and Molecular Medicine Laboratory (NIMML) will head up a 5-year project to develop a system public health officials could use to immediately identify the best treatment strategy for anyone exposed to a toxic biological agent.
“Recent advances in data analytics and artificial intelligence systems are fundamentally transforming our ability to personalize treatments to the specific needs of a patient under treat-to-target paradigms,” said Josep Bassaganya-Riera, co-director of the Biocomplexity Institute’s Nutritional Immunology and Molecular Medicine Laboratory. “Our goal in this project will be to leverage the power of modeling and advanced machine learning methods, so a group of people exposed to a harmful pathogen or its toxins can receive faster, safer, more effective and personalized treatments.”
The progression of an infection can vary greatly depending on a host of factors, including the type of pathogen, how individuals were exposed to it, and in what quantity. Rather than relying on a standard response plan which may not suit the specific conditions of a biological attack, the Virginia Tech team aims to empower DTRA officials with a system capable of quickly generating customized treatment strategies.
This project will build on computational modeling systems previously designed by NIMML to create tailored treatment plans for patients infected by the toxin-producing bacterium, Clostridium difficile. In 2015, the Centers for Disease Control reported nearly half a million Americans had suffered from this disease—29,000 of those cases resulted in death within a month of diagnosis.
“Our computational models are used as platforms for integrating results obtained in the lab and clinical data from patients. In the event of an attack, they could be used to evaluate in real time the particular characteristics of the outbreak and accelerate the choice of treatment,” said Raquel Hontecillas, an associate professor at the Biocomplexity Institute and co-director of NIMML.
As a Leading Laboratory at the Biocomplexity Institute, NIMML’s overarching research program focuses on transitioning advanced computational technologies into new healthcare applications.
“We’ve spent the past decade building research programs that are collaborative, data-intensive, and backed by the latest in high-performance computing technology,” said Chris Barrett, Executive Director of the Biocomplexity Institute. “Our solutions are designed to be flexible so that during a crisis, when conditions on the ground are constantly changing, our partners can apply them with confidence.”
By using similar advanced computational approaches in a combination of translational methods, the NIMML team recently launched Landos Biopharma, an emerging biotech company that develops oral therapeutics for autoimmune diseases. The team has the expertise and capabilities to move new therapeutics from the discovery stages into clinical testing.
The Biocomplexity Institute regularly conducts research through federal, state and industry grants and contracts. This award is part of the institute's portfolio of research programs that has received more than $103M in new awards in the first half of FY 2018.