San Francisco, CA, United States of America

James Lu

USPTO Granted Patents = 2 

 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2025

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2 patents (USPTO):Explore Patents

Title: Innovations by James Lu in Pharmacokinetics

Introduction

James Lu is an accomplished inventor based in San Francisco, CA. He has made significant contributions to the field of pharmacokinetics through his innovative methods and systems. With a total of 2 patents, Lu's work focuses on utilizing deep learning to enhance the understanding of drug behavior in the body.

Latest Patents

One of Lu's latest patents is titled "Population PK/PD linking parameter analysis using deep learning." This invention presents a method and system for predicting a set of linking parameters that relate pharmacokinetic (PK) and pharmacodynamic (PD) effects. The system involves one or more processors that receive a population dataset, which includes both PK and PD datasets. These processors transform the dataset into multiple data density images, allowing for the prediction of linking parameters based on the generated images.

Another notable patent by Lu is "Estimating pharmacokinetic parameters using deep learning." This invention outlines a method for predicting at least one pharmacokinetic parameter of an agent administered to a subject. The system trains a neural network using a simulated training data collection, which includes a time-series concentration dataset. The trained neural network is then used to predict the pharmacokinetic parameter value based on real-time data obtained from a subject.

Career Highlights

James Lu is currently associated with Genentech, Inc., a leading biotechnology company known for its innovative approaches to drug development. His work at Genentech has allowed him to apply his expertise in deep learning to real-world challenges in pharmacokinetics.

Conclusion

James Lu's contributions to the field of pharmacokinetics through his innovative patents demonstrate the potential of deep learning in enhancing drug analysis. His work continues to pave the way for advancements in understanding drug behavior and improving patient outcomes.

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