Seth Green, M.S.

Manager, Data Science Engineering

Seth joined the Technology Solutions team at Metrum in January 2020. He has expertise in a range of Data Science disciplines including machine learning, applied statistics, big data engineering, and data visualization as well as experience in software engineering from his work building tools and platforms in the digital advertising and scholarly publishing industries. Seth’s credentials include an MS in Data Science and a BA in Philosophy & History, both from the University of Virginia, plus almost a decade on the road as a professional musician.

Recent publications by this scientist

simpar: an R Package for Parameter Uncertainty Simulations in Pharmacometric Modeling

November 15, 2023

Presented at ACoP14. This project is dedicated to integrating parameter uncertainty into pharmacometric simulations, which plays a crucial role in making informed decisions in drug development. Initially, the metrumrg package in R was instrumental for simulating both fixed and random effect parameters. However, this package has since been deprecated. Consequently, the primary objective was to create a new R package named simpar. This new package aimed to retain the essential functionalities of metrumrg while expanding its capabilities. The overarching goal was to significantly enhance the support for incorporating parameter uncertainty into pharmacometric simulations, thereby aiding more comprehensive and accurate decision-making processes in this field.

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Development of a dynamic Parkinson’s Disease database with user interface tools as a basis for internal and regulatory decision making

November 14, 2023

Presented at ACoP14. The objective of this work is to integrate multiple PD clinical studies, harmonize the data, and deploy a user interface for rapid data interrogation and analysis subset generation.

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A showcase of open-source tools for scalable, reproducible PMx workflows

October 31, 2022

Kyle Baron, Sam Callisto, Seth Green, Matthew Riggs. A showcase of open-source tools for scalable, reproducible PMx workflows. Pre Meeting Workshop presented at 2022 American Conference on Pharmacometrics (ACoP13). 30 October 2022.

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