Quest for Innovation: Data-driven ways to cope with COVID-19

Language: English

Scottsdale, AZ – July 7, 2020 – Billions upon billions of bits of data — 2.5 quintillion bytes daily, to be exact — are produced by today’s vast array of robust information-gathering technologies, Dr. Chris Yoo told Arizona State University students competing in the most recent Devils Invent engineering design challenge.

Those who can mine that data and detect the patterns it reveals could help tackle some of the world’s most serious problems, Yoo said. Perhaps even the current COVID-19 pandemic.

Yoo is the CEO of Systems Imagination, the technology engine of its sister company Systems Oncology.  Systems Imagination makes use of data science and artificial intelligence to rapidly identify “actionable insights,” as Yoo calls them.  Systems Oncology has used System Imagination’s technology on massive data sets to develop more effective cancer therapeutics.

Eight hackathon teams comprised of approximately 70 engineering and science students, most from ASU’s Ira A. Fulton Schools of Engineering, were directed to emulate the companies’ business model and use publicly available data to devise ideas for how big data could help communities mount defenses against the continuing spread of COVID-19.

“Students are often able to bring fresh perspectives to wide open challenges like this,” Yoo said. “If you look at the history of invention and innovation you’ll see some of the most imaginative ideas come from younger people driven only by simple curiosity and who haven’t experienced being told what doesn’t work.”

Read the full story here on ASU’s website.


About Systems Oncology

Systems Oncology, LLC (SO) is an AI-based cancer therapy discovery and development company.  SO has a multidisciplinary team of scientists and a revolutionary cognitive computing platform (Expansive.AI) able to intelligently integrate, model, and mine big data from hundreds of molecular, genomic, and biomedical datasets.  This new kind of computational data mining has empowered the SO team to rapidly extract many therapeutically useful insights from complex multi-scalar systems models of cancer biology.  This scalable data-driven approach has been used by SO to translate many unique biological insights into dozens of discovery projects and research collaborations with leading universities, producing one of the fastest growing pipelines of innovative cancer therapies in the industry. For more information, go to

Media Contact
Systems Oncology
Katy Marhenke