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Pek Lum, co-founder, and CEO of Auransa believes that a lot fewer drugs would fail in Phase 2 clinical trials if they were tested on patients predisposed to respond. The problem is finding the sub-populations of likely high-responders in advance and matching them up with promising drug compounds. That’s Auransa's specialty.

The Palo Alto, CA-based drug discovery startup, formerly known as Capella Biosciences, has a pipeline of novel compounds for treating cancer and other conditions identified through machine learning analysis of genomic data and other kinds of data. It’s closest to the clinical trial stage with a gene expression modulator for liver cancer (AU-409) and is also working on drugs for prostate cancer and for protecting the heart against chemotherapy drugs. 

The company says it discovered AU-409 as part of a broad evaluation of data sets on a range of close to 30 diseases. The company’s discovery process uses a platform called the SMarTR Engine that uses hypothesis-free machine learning to identify druggable targets and compounds as well as likely high-responder patients. Lum  calls it “interrogating gene expression profiles to identify patient sub-populations.” The company believes this approach can identify unexpected connections between diverse molecular pathways to disease, and that it will lead to progress in drug development for intractable conditions with poorly understood biology, including cancer and autoimmune, metabolic, infectious, and neurological diseases.

Lum co-founded Auransa with Viwat Visuthikraisee in 2014 and is the chief architect behind its technology. Before Auransa, she was VP of Product, VP of Solutions, and Chief Data Scientist at Ayasdi (now SymphonyAyasdiAI), a Stanford spinout known for building hypothesis-free machine learning models to detect patterns in business data. Before that, she spent 10 years as a scientific director at Rosetta Inpharmatics, a microarray and genomics company that was acquired by Merck. She has bachelor's and master's of science degrees in biochemistry from Hokkaido University in Japan and a Ph.D. in molecular biology from the University of Washington, where she studied yeast genetics.

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•TRANSCRIPT

Harry Glorikian: I’m Harry Glorikian, and this is MoneyBall Medicine, the interview podcast where we meet researchers, entrepreneurs, and physicians who are using the power of data to improve patient health and make healthcare del