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Atlanta, GA | Posted: November 4, 2015
Shelley Wunder-Smith
Stewart School of Industrial & Systems Engineering
404.385.4745
Summary Sentence:
A team of researchers from three institutions were awarded the prestigious INFORMS Daniel H. Wagner Prize for their work.
Full Summary:
No summary paragraph submitted.
Eva K. LeePHILADELPHIA, PA, November 4, 2015 – The Institute for Operations Research and the Management Sciences (INFORMS®), the leading professional association in analytics and operations research, today announced that the winner of the Daniel H. Wagner Prize is a team comprising researchers from the CDC, Georgia Tech, and Emory University for creating a model that uses genetic signatures to predict the efficacy of vaccines on an individual by individual basis.
The winner of the INFORMS Daniel H. Wagner Prize competition was named on Tuesday, November 3 at the 2015 INFORMS Annual Meeting in Philadelphia. The competition is judged by CPMS, the association’s practice section. Over 5,500 academics and practitioners attended the conference.
Machine Learning Framework for Predicting Vaccine Immunogenicity, is by Eva K. Lee, Fan Yuan, Georgia University of Technology; Bali Pulendran, Helder Nakaya, Emory University; and Ferdinand Pietz and Bernard Benecke, Centers for Disease Control and Prevention.
Eva K. Lee is the winner of numerous INFORMS awards. She was named an INFORMS Fellow at the INFORMS annual meeting.
The ability to better predict how different individuals will respond to vaccination and to understand what best protects them from infection marks an important advance in developing next-generation vaccines. It facilitates the rapid design and evaluation of new and emerging vaccines. It also identifies individuals unlikely to benefit from the vaccine.
The authors created a general-purpose machine learning framework, called DAMIP, for discovering gene signatures that can predict vaccine immunity and efficacy.
Using DAMIP, implemented results for yellow fever demonstrated that, for the first time, a vaccine’s ability to immunize a patient could be successfully predicted with greater than 90% accuracy within a week after vaccination. A gene identified by DAMIP decrypted a seven-decade-old mystery of vaccination. Results for flu vaccine demonstrated DAMIP’s applicability to both live-attenuated and inactivated vaccines. Similar results in a malaria study enabled targeted delivery to individual patients.
The project guides the rapid development of better vaccines to fight emerging infections and improve monitoring for poor responses in the elderly, infants, and those with weakened immune systems.
Importantly, the project’s work is expected to help design a universal flu vaccine.
The other four finalists for the 2015 Wagner Prize were:
