Eric Ariazi

Title: Eric Ariazi: Innovator in Methylation Sequencing and Machine Learning Diagnostics

Introduction

Eric Ariazi is a prominent inventor based in South San Francisco, CA (US). He has made significant contributions to the fields of methylation sequencing and machine learning diagnostics. With a total of 3 patents, his work addresses critical challenges in disease detection and diagnostic accuracy.

Latest Patents

One of Eric's latest patents focuses on "Methods and systems for high-depth sequencing of methylated nucleic acid." This innovation improves the quality and accuracy of nucleic acid methylation sequencing, addressing limitations of traditional bisulfite-based methods. The patent describes minimally-destructive conversion methods and specialized UMI adapters that enhance sequencing library quality. This advancement allows for greater accuracy and more comprehensive methylation-state information, which is essential for developing machine learning models and classifiers.

Another notable patent is titled "Machine learning implementation for multi-analyte assay development and testing." This system analyzes blood-based cancer diagnostic tests using various classes of molecules, such as cell-free DNA and circulating proteins. By employing machine learning, the system increases the sensitivity and specificity of diagnostics. It processes biological samples, separates molecule classes, and identifies feature sets for machine learning models, ultimately classifying whether the sample possesses specific properties.

Career Highlights

Eric Ariazi is currently employed at Freenome Holdings, Inc., where he continues to innovate in the field of diagnostics. His work is pivotal in advancing technologies that enhance disease detection and improve patient outcomes.

Collaborations

Eric collaborates with talented professionals, including Adam Drake and Daniel Delubac, who contribute to the innovative environment at Freenome Holdings, Inc.

Conclusion

Eric Ariazi's contributions to methylation sequencing and machine learning diagnostics exemplify the impact of innovation in healthcare. His patents reflect a commitment to improving diagnostic accuracy and advancing medical technology.