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Confidential Computing for Enhanced Genomic Epidemiology

June 5, 4:40 PM - 5:00 PM
Grand Ballroom Salon B

Advances in DNA sequencing technology are expected to continue over the next decade, accompanied by continued decreases in cost. The COVID-19 pandemic clearly demonstrated the value of these technologies for infectious disease surveillance in various settings across public health, hospital systems, and government entities. However, the insights gained from genomics tools are most powerful when combined with complementary epidemiological and patient data.

Unfortunately, privacy and security challenges have hindered the combination of genomics data with relevant patient data. Confidential computing technology offers a solution to these problems by providing a secure, encrypted environment where genomics and patient data can be combined to drive insights while keeping both data and models secure. Palmona Pathogenomics has developed a platform (P3) for combining these data sets to improve the management of infectious diseases by fostering multi-party collaboration across stakeholders leveraging confidential computing.

We have implemented predictive models of pathogen properties based on genome sequences to predict antibiotic resistance and virulence risk. This information is combined with epidemiological data to uncover factors driving the spread of pathogens across regions and facilities. Insights related to patient risk based on demographic factors (age, gender, co-morbidities) are presented. Epidemiological factors such as travel history are incorporated for improved outbreak tracing. Trend analysis highlights changes in pathogens and resistance mechanisms across time and geographies.

The P3 Platform is currently used in Public Health, Medical Centers, Diagnostics, and Life Science Tools companies. This session will describe the use cases and insights offered to these customers, leveraging privacy-preserving architecture and supporting cloud, data, and AI technology.

About the speaker

Jonathan Monk

Co-Founder and General Manager, Palmona Pathogenomics

Jonathan Monk is Co-Founder and General Manager of Palmona Pathogenomics, a subsidiary of Avellino Labs, Inc. Jonathan leads the development of Palmona's infectious disease analytics platform. His background is in systems biology of infectious diseases and the development of AI/ML approaches to predict pathogen properties from genome sequences. His ultimate goal is to provide precision medicine for pathogens. Prior to co-founding Palmona Pathogenomics, Jonathan was a researcher in Dr. Bernhard Palsson's Systems Biology Research Group at UC San Diego. Jonathan received his Ph.D. from UC San Diego and his BSE from Princeton University. He has published over 100 peer-reviewed scientific articles.