Build better models. Measure meaningful responses. Inform the next experiment.
01 / TUMOR MICROPHYSIOLOGICAL SYSTEMS
How do CAR T cells perform inside a vascularized tumor microenvironment?
I lead the development of a perfusable glioblastoma-on-chip platform that brings together endothelial barriers, patient-derived tumor spheroids, and cellular immunotherapies. The work examines immune-cell trafficking and tumor killing alongside T-cell phenotype and cytokine responses.
By pairing controlled microenvironments with complementary readouts, I investigate the spatiotemporal factors that shape CAR T-cell potency.
Vascularized GBM-on-chip, CAR T-cell potency, Multiparametric assays
AI-generated conceptual illustration of controlled release.
02 / CONTROLLED DRUG DELIVERY
Can controlled release help us explore new treatment combinations?
I develop Surfen-loaded PLGA microparticles and characterize their formulation, loading, and release behavior. This work investigates combination approaches with temozolomide and radiation across preclinical glioblastoma models, including an RCAS mouse pilot.
PLGA microparticles, Combination therapy, Preclinical models
AI-generated conceptual illustration of immune-cell bioenergetics.
03 / IMMUNOMETABOLISM
How does the tumor environment shape immune-cell energy and function?
As lead trainee and trainee principal investigator of a UGA CAES/CVM collaboration, I coordinate a project studying CAR T-cell mitochondrial fitness in the glioblastoma metabolic microenvironment. MitoCAR connects tumor-on-chip models with bioenergetic measurements to investigate the relationship between metabolism and therapeutic function.
Bioenergetics, Mitochondrial fitness, Cross-disciplinary collaboration
COMPLEMENTARY RESEARCH DIRECTIONS
04 / LABEL-FREE THERAPEUTIC EVALUATION
I use quantitative oblique back-illumination microscopy (qOBM) to investigate how glioblastoma spheroids respond to treatment without fluorescent labeling. Longitudinal imaging tracks changes in tumor structure and cellular morphology, providing complementary measurements for evaluating chemotherapy, radiation, and immunotherapy in preclinical models.
Label-free imaging, Longitudinal assessment, Therapeutic response
05 / MULTIMODAL PREDICTIVE ANALYSIS
I am developing Python-based workflows to integrate flow cytometry, confocal and label-free imaging, single-cell RNA sequencing (scRNA-seq), and intracellular metabolomics. The goal is to connect cellular phenotype, spatial organization, gene expression, and metabolic state to identify and validate quantitative predictors of therapeutic response for preclinical studies.
Python, Multimodal integration, Predictive measurements
06 / ACCESSIBLE TUMOR-ON-CHIP WORKFLOWS
I aim to automate microfluidic cell seeding and tumor-on-chip experiments to simplify operation, reduce operator-dependent variability, and improve reproducibility. By standardizing workflows, this research seeks to support broader adoption across universities, research institutes, and industry laboratories.
This direction aligns with FDA and NIH efforts to advance human-relevant new approach methodologies (NAMs) and microphysiological systems (MPS).
Microfluidic automation, Reproducibility, NAMs & MPS
Related initiatives: FDA New Approach Methodologies · NIH NCATS Tissue Chip initiatives.
These project descriptions summarize ongoing research. Conceptual illustrations are distinct from experimental images and results.
FROM PLATFORM TO INSIGHT
Microfluidic fabrication, perfusion systems, biomaterials, and controlled-release formulations.
Patient-derived spheroids, endothelial barriers, tumor microenvironments, and immune co-cultures.
Flow cytometry, confocal and label-free imaging, cytokine assays, and metabolic readouts.
Python-based image analysis, multimodal data integration, and reproducible experimental workflows.