Kyle T. Baron, Pharm.D., Ph.D.

Group Leader PKPD, Senior Principal Scientist I, Fellow I

Kyle joined MetrumRG in 2010 after receiving his Pharm.D. and Ph.D. in Experimental and Clinical Pharmacology from the University of Minnesota. As a member of our translational and systems pharmacology group, Kyle has worked to support sponsor development programs in a variety of therapeutic areas, including chronic hepatitis C infection, HIV, calcium homeostasis and bone health, type-2 diabetes, and cystic fibrosis.

Kyle is the developer and maintainer of mrgsolve (https://mrgsolve.github.io) and also leads workshops at all levels to guide other M&S scientists in the effective use of this simulation tool in PKPD, PBPK, and QSP modeling. Kyle also serves as adjunct faculty in Experimental and Clinical Pharmacology at the University of Minnesota.

Recent publications by this scientist

Exposure–Response Relationships in Patients with Non-Small-Cell Lung Cancer and Other Solid Tumors Treated with Patritumab Deruxtecan (HER3-DXd)

April 14, 2025

This paper contributes to the oncology MIDD field by using robust exposure-response modeling to identify the optimal dosing regimen for HER3-DXd in EGFR-mutated NSCLC. Analyzing data from over 700 patients across four studies, it demonstrates that 5.6 mg/kg Q3W offers a favorable balance of efficacy and safety. The analysis incorporates patient covariates and compares fixed and up-titration regimens, supporting data-driven selection. These methods align closely with the goals of Project Optimus, emphasizing the importance of modeling and simulation in selecting doses that are both effective and tolerable, rather than defaulting to the maximum tolerated dose.

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Simulating Dynamic Adaptive Dosing Regimens from PK and PKPD Models Using mrgsolve

December 6, 2024

Presented at ACoP 2024. This poster describes additions to mrgsolve to facilitate adaptive dosing simulations. A case study is also presented where these tools were utilized to evaluate dose adjustment guidance for valemetostat in patients with non-Hodgkin lymphoma.

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Accounting For Dose Modifications In Exposure-Response Analyses In Oncology: The Case Example Of Brigimadlin.

December 6, 2024

Presented at ACoP 2024. A Bayesian model of the probability of dose modification as a function of platelet and neutrophil counts was developed to characterize the dynamic and probabilistic nature of dose decisions. The dose modification model was successfully integrated into a dynamic simulation framework accounting for the impact of safety on dose.

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