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Ion Torrent Sponsors Development of 'Doctor in a Box' Software at Carnegie Mellon

NEW YORK (GenomeWeb News) – Life Technologies' Ion Torrent business is providing initial funding for a project at Carnegie Mellon University that aims to develop a computational system that will help doctors use genomic information to diagnose disease and guide treatment.

Robert Murphy, director of the Lane Center for Computational Biology in Carnegie Mellon's School of Computer Science, will lead the so-called "doctor in a box" project, which will also involve researchers from the Baylor College of Medicine and Yale University.

Ion Torrent is sponsoring the project with an undisclosed amount of funding for its first year.

The goal is to develop software that will be able to use a patient's DNA sequence to diagnose disease, identify susceptibility to disease, and predict which therapies might be most effective or cause the fewest side effects. Murphy said the team intends to make its software available as open source.

"The work the Carnegie Mellon team is undertaking opens up the possibility that practicing physicians will be able to diagnose disease, identify disease susceptibility and guide therapy selection as easily as they can now use Apple's Siri on the iPhone," Ion Torrent founder Jonathan Rothberg said in a statement.

During the first year of the project, the researchers will focus on identifying the specific genomic features associated with a single disease or patient population — neither of which has yet been identified.

Researchers at Baylor's Human Genome Sequencing Center and Yale's Center for Genome Analysis will perform whole-genome sequencing of patients and provide information from medical records, such as disease treatments and outcomes and results of clinical tests. The Carnegie Mellon team will then use machine-learning approaches to assess the relationships between genomic data and clinical outcomes for each of the anonymous patients, while incorporating information from the biomedical literature related to gene and protein expression and disease pathways.

This analysis will generate models that can be used to predict disease susceptibility and treatment responsiveness, as well as choose preventive therapies, the researchers said.

In order to kick off the program, Rothberg will sponsor an "Analyzing the $1,000 Genome" Conference that will be held at Carnegie Mellon this summer or fall.

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