Millbrae, CA, United States of America

Steven Kothen-hill

USPTO Granted Patents = 1 

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations in Colorectal Cancer Detection by Steven Kothen-Hill

Introduction

Steven Kothen-Hill is an accomplished inventor based in Millbrae, California. He has made significant contributions to the field of medical diagnostics, particularly in the detection of colorectal cancer. His innovative approach utilizes advanced techniques in nucleic acid methylation analysis to improve cancer screening methods.

Latest Patents

Kothen-Hill holds a patent for "Methods and systems for detecting colorectal cancer via nucleic acid methylation analysis." This patent outlines a method for screening or detecting colorectal cancer by analyzing cell-free nucleic acids, such as cell-free DNA. The method employs the detection of methylation signals within a single sequencing read in specific genomic regions. This information is then used to train a machine learning model, which generates a classifier that can stratify populations based on their health status, including healthy individuals, cancer patients, and those with different disease subtypes or stages. The method is designed to predict, prognosticate, and monitor responses to treatment, tumor load, relapse, or the development of colorectal cancer.

Career Highlights

Kothen-Hill is currently associated with Freenome Holdings, Inc., where he continues to advance his research in cancer detection technologies. His work is pivotal in enhancing the accuracy and efficiency of colorectal cancer screening, which can lead to earlier diagnosis and better patient outcomes.

Collaborations

Some of his notable coworkers include John St John and Rui Yang, who contribute to the collaborative efforts in developing innovative solutions for cancer detection.

Conclusion

Steven Kothen-Hill's contributions to the field of colorectal cancer detection through his patented methods demonstrate the potential of combining machine learning with genomic analysis. His work not only advances medical technology but also holds promise for improving patient care in oncology.

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