Kyle Barrett

Senior Data Science Engineer I

Kyle joined Metrum in January 2021 as a Data Science Engineer with research and lab experience in PKPD modeling, biological colloids, and image analysis, including a recent focus on software development, creating tools and automating certain processes using R/R Shiny, C++, and HTML/CSS. His programming experience has involved PBPK and PKPD modeling and simulation and R shiny app development, and he has also modeled anaerobic digestion and created numerous other web apps. Kyle intends to expand his knowledge base in software development and further develop skills in data analysis and visualization.

Recent publications by this scientist

Pharmacometric-Pharmacoeconomic Modeling and Simulation in Atopic Dermatitis: Informing Early Drug Development Decisions for a Hypothetical New Therapeutic.

December 6, 2024

Presented at ACoP 2024. Early drug development decision making, such as the definition and assessment of target product profile characteristics, rarely includes pharmacoeconomic (PE) considerations. The disciplines of phamacometrics (PM) and PE are closely aligned and intersect at the goal of a quantitative understanding of the system. Connection of these two disciplines is a logical extension of typical PM objectives and should lead to a more complete and accurate understanding of the probability of success for new therapeutics.

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pmparams: an R Package for Defining and Formatting Parameter Tables in Pharmacometric Modeling

November 13, 2024

Presented at ACoP 2024. The aim was to provide a simple, reproducible, and traceable method for generating parameter tables in R for NONMEM. models. Attainedvia a new package (pmparams): a stable and easy-to-use tool intended to integrate with, and extend the functionality of, existing packages in the Metrum Research Group Ecosystem (MeRGE)

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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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