Recommended by: Janet Thornton, European Bioinformatics Institute
With physicians for parents, Julio Saez-Rodriguez has long had an interest in human health and the sciences, but life inside of a hospital and the pressures of making life-or-death decisions did not appeal to him. He ended up studying chemical engineering, but maintained a curiosity about the "biological basis of disease and how to treat it." During his graduate studies, he brought together these two areas of interest and began using engineering methods to better understand signaling networks within normal and diseased cells.
Now with his own lab at the European Molecular Biology Laboratory's European Bioinformatics Institute, Saez-Rodriguez is working with the Genomics of Drug Sensitivity in Cancer project — a Wellcome Trust-funded initiative to identify molecular features of cancers that can be used to predict their response to therapeutic interventions — to help manage and interpret the data derived from high-throughput screening experiments.
Overall, Saez-Rodriguez is focusing on developing mechanistic models to "understand and predict why drugs work," he says.
Paper of note
In a paper stemming from his postdoctoral work with Peter Soger and Doug Lauffenberger at Harvard Medical School and the Massachusetts Institute of Technology, Saez-Rodriguez and his colleagues developed a discrete logic modeling approach to link protein signaling networks with a functional analysis of mammalian signal transduction.
"People in the group … were developing relatively high-throughput methods to look at pathways," Saez-Rodriguez says. "The question was how to analyze that data."
"On one side, they were doing a lot of statistical models that were very powerful as predictors, but were black boxes in terms of mechanism," he adds. "On the other extreme, you had very detailed biochemical models based on reactions and biochemistries … [which are] very good to understand in detail the molecular mechanisms, but don't scale up. We developed an approach that fits somewhere between block-box statistics and biochemical detail."
And the Nobel goes to...
Saez-Rodriguez says he would want to win the Nobel Prize for using mathematical models to uncover a novel paradigm for treat cancer.