HomeNews & MediaFeatured StoriesPredicting Virus Mutations Project Seeks to Transform Vaccine and Drug Development  

October 11, 2012

Predicting Virus Mutations Project Seeks to Transform Vaccine and Drug Development

influenza virus
Diseases like the 2009 influenza A H1N1 virus can quickly morph into strains that resist vaccines and immune systems. (Credit: Centers for Disease Control and Prevention)

In the last two decades, according to the National Institute of Allergy and Infectious Diseases, nearly half of the new pathogens that affect human and animal health have been viruses. As with the influenza A (H1N1) pandemic in 2009, most of these diseases can quickly adapt and morph into nastier strains that resist attacks by vaccines and immune systems.

The Defense Advanced Research Projects Agency (DARPA), through a program called DARPA Prophecy, has tapped Harvard University and APL to develop methods to predict how, and how fast, these viral agents might mutate.

"The current approach to dealing with viruses is reactive," explains Andrew Feldman, DARPA Prophecy project manager and principal investigator in the Research and Exploratory Development Department. "Existing vaccines and therapies are designed to protect against viruses that are already out there, and new vaccines take years to develop. But we are trying to get out in front of emerging diseases by predicting how viruses evolve."

In August 2011, DARPA challenged the Harvard/APL team, along with several others, to come up with a technical approach to this seemingly impossible task. This past August, the agency chose three teams and gave them 18 months to implement their ideas. Harvard and APL added partners with expertise in protein crystallography (which allows scientists to visualize protein structures at the atomic level) and computational chemistry. They are also drawing on capabilities from Johns Hopkins centers at the Bloomberg School of Public Health and the Johns Hopkins Hospital's Department of Emergency Medicine.

"Our approach combines high-throughput experiments informing computational models," Feldman explains. "Ultimately we will end up with models of viral evolution that will allow us to predict the probable emerging viruses before they appear, show us their trajectory and speed, and calculate how they will respond to the tools we have to fight them."

The project builds on APL's significant investment in DNA sequencing bioinformatics, which Feldman says has provided the team with unique insights into interpreting viral populations from "noisy" DNA sequencing information. The team is complementing the Homeland Security Business Area's work in syndromic surveillance, he says. "That's a very data-driven process, relying on nontraditional sources of data to detect public health events as early as possible. We are doing surveillance to see what might emerge before people start getting sick."

The technology the team is developing will provide the foundation for future biosciences work at the Laboratory. Other APL projects are already exploring its uses in identifying new drug-resistance mechanisms in bacteria in the environment; rapid detection and testing for drug-resistant malaria; and next-generation human forensics genetics by accurately sequencing individual DNA molecules.

The project has also brought new expertise to APL, Feldman says. "We are doing high-throughput screening using microfluidics, virus engineering, and computational protein-to-protein interaction—all new areas for us that you would typically find at pharmaceutical companies," he explains. "While these tools clearly will interest the commercial drug industry, there are unique defense applications. Current APL projects aim to provide new capabilities to protect soldiers when they go into future hot spots in Southeast Asia, Africa, and South America, where a lot of these diseases emerge."