Chapel Hill, NC, United States of America

Adrian Vrouwenvelder


Average Co-Inventor Count = 4.2

ph-index = 2

Forward Citations = 20(Granted Patents)


Company Filing History:


Years Active: 2013-2023

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9 patents (USPTO):Explore Patents

Title: Adrian Vrouwenvelder: Innovator in Clinical Trial Technology

Introduction

Adrian Vrouwenvelder is a notable inventor based in Chapel Hill, NC (US). He has made significant contributions to the field of clinical trials through his innovative use of machine learning technologies. With a total of 9 patents, Vrouwenvelder has developed methods that enhance the quality and success rates of clinical trials.

Latest Patents

One of his latest patents focuses on using machine learning to evaluate data quality during a clinical trial based on participant queries. This method involves a computing platform that receives study design information and query-related data from participants. By applying a trained machine learning model, the platform calculates a predicted data quality score and provides suggestions for improvement. Another significant patent involves facilitating the design and implementation of clinical trials with a high likelihood of success. This innovation allows for the prediction of multiple success scores based on varying parameter values, ultimately guiding researchers toward the best overall success score for their trials.

Career Highlights

Throughout his career, Adrian Vrouwenvelder has worked with prominent companies such as IBM and Merative US L.P. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking advancements in clinical trial methodologies.

Collaborations

Vrouwenvelder has collaborated with notable professionals in his field, including Nathan A. Baker and James D. Creasman. These partnerships have further enriched his work and expanded the impact of his innovations.

Conclusion

Adrian Vrouwenvelder stands out as a leading inventor in the realm of clinical trials, leveraging machine learning to improve data quality and success rates. His contributions are paving the way for more effective and reliable clinical research methodologies.

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