Samuel Callisto, Ph.D.

Senior Scientist I

Samuel joined MetrumRG in 2019 after earning his PhD in Experimental and Clinical Pharmacology with an emphasis in Pharmacometrics from the University of Minnesota College of Pharmacy. His thesis work focused on modeling cognitive side effects of the anti-epileptic drug topiramate using a combination of pharmacokinetic-pharmacodynamic models and unsupervised machine learning algorithms. While in graduate school he also researched the impact of pharmacogenomics on the pharmacokinetics and pharmacodynamics of multiple drug classes.

Recent publications by this scientist

An Introduction to R Programming Language

April 3, 2024

Presented by Dr. Sam Castillo and Michael Heathman at the CTSI Disease and Therapeutic Response Modeling Symposium, February 2024.
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Illustrating Integration and Interpretation of the Deep Compartment Model Approach using Keras and R in a Population PK Modeling Analysis

November 14, 2023

Presented at ACoP14. Deep compartment models (DCMs) are a proposed alternative to traditional nonlinear mixed effect (NLME) pharmacometrics approaches [1]. DCM uses neural networks to represent estimated pharmacokinetic parameters which can then be used in either closed-form or ordinary differential equation (ODE)-based representations of pharmacokinetic models

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A Showcase of Open-Source Tools for Scalable, Reproducible Pharmacometrics Workflows

March 7, 2023

Sam Callisto, Tim Waterhouse. Presented at 12th Annual Indiana Clinical and Translational Sciences Institute (CTSI) Symposium on Disease and Therapeutic Response Modeling. February 23, 2023.

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