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Academic scientists devote their lives to research, often toiling away on problems that few people outside their discipline fully understand. Perhaps some are driven by pure curiosity or competition, while others have a personal interest in the topic at hand.

For Shirley Pepke, a genomics researcher based in Los Angeles, the urgency to find answers comes from her own instinct for survival. Since 2014, she has been working on a tool capable of tailoring ovarian cancer treatment to each patient using genomics data and a machine learning algorithm.

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The first subject in this DIY precision medicine project was Pepke herself, who was diagnosed with stage IIIC ovarian cancer in September 2013.

“Some people get cancer and do fundraisers – I’m good at doing computational research on complex systems, so it seemed really natural for me to work on this,” she said. “Because I have really young children, I felt that I had to pursue every avenue to try and extend my life, and I owed it to them.”