Hillary Husband, Ph.D.

Research Scientist II

Hillary joined MetrumRG in 2021 after earning her MS in Mathematics and PhD in Engineering from Louisiana Tech University. Her thesis work centered on utilizing physiologically based pharmacokinetic modeling for therapeutic drug monitoring. She has research experience in PK/PD modeling, survival analysis, item response theory modeling, and R package development. Hillary is excited to join Metrum because of a shared enthusiasm for open science and cross-disciplinary collaboration.

Recent publications by this scientist

Integrated Two‑Analyte Population Pharmacokinetics Model of Patritumab Deruxtecan (HER3‑DXd) Monotherapy in Patients with Solid Tumors

June 17, 2025

This work illustrates how integrated population PK modeling of antibody-conjugated payload and free payload analytes for an ADC can inform development strategies for targeted therapies—particularly in complex oncology settings.

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Pharmacometric Machine Learning: Integrating Neural Networks for Flexible, Advanced Covariate Analysis

June 13, 2025

Presented at ASCPT 2025 Annual Meeting. Neural networks can be integrated with traditional pharmacometric models using several free open-source programming languages. Both Julia and R environments are suitable platforms, but there are tradeoffs regarding development speed, built-in capabilities, and documentation. DCM simplifies the covariate modeling process and uncovers complex, non-linear relationships in computationally efficient workflows.

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Reinforcement Learning for Pharmacometrics: A Proof of Concept and Future Directions.

December 6, 2024

Presented at ACoP 2024. A proof-of-concept was conducted using deep reinforcement learning to optimize vancomycin dosing based on predicted PK profiles. The reinforcement learner was able to produce dose recommendations that (on average) exceeded the standard-of-care recommended dose, and future opportunities for using reinforcement learning within pharmacometrics are vast with a large potential for impact through personalized dosing.

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