Aleksander Popel

Professor

Johns Hopkins University

United States

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About

Aleksander Popel is a Professor at Johns Hopkins University in the United States. His research focuses on quantitative systems pharmacology modeling, particularly in the context of immuno-oncology and biomarkers for various cancers. Recent articles include work on enhancing predictive biomarkers for PD-1 blockade and developing models for treatment strategies in advanced non-small cell lung cancer and uveal melanoma.

Articles (17)

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2024

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2021

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2020

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2020

Collaborators (4)

Brian Annex

Professor and Chair

Augusta University Medical College of Georgia

UNITED STATES

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Lu Lu

Assistant Professor

Yale University

UNITED STATES

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Samira Anbari

Johns Hopkins University

UNITED STATES

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Natsuki Furukawa

Johns Hopkins University

UNITED STATES

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Aleksander Popel

Research Interests

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About

Articles (17)

From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling

Quantitative systems pharmacology modeling of macrophage‐targeted therapy combined with PD‐L1 inhibition in advanced NSCLC

Signaling-biophysical modeling unravels mechanistic control of red blood cell phagocytosis by macrophages in sickle cell disease

Eliciting the antitumor immune response with a conditionally activated PD‐L1 targeting antibody analyzed with a quantitative systems pharmacology model

Identifying biomarkers for treatment of uveal melanoma by T cell engager using a QSP model

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

A transcriptome-informed QSP model of metastatic triple-negative breast cancer identifies predictive biomarkers for PD-1 inhibition

Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition

Quantifying Intratumoral Heterogeneity and Immunoarchitecture Generated In-Silico by a Spatial Quantitative Systems Pharmacology Model

Experiment-based computational model predicts that IL-6 classic and trans-signaling exhibit similar potency in inducing downstream signaling in endothelial cells

Quantitative Spatial Profiling of Immune Populations in Pancreatic Ductal Adenocarcinoma Reveals Tumor Microenvironment Heterogeneity and Prognostic Biomarkers

The tumor microenvironment and triple-negative breast cancer aggressiveness: shedding light on mechanisms and targeting

A systems biology model of junctional localization and downstream signaling of the Ang–Tie signaling pathway

A Spatial Quantitative Systems Pharmacology Platform spQSP-IO for Simulations of Tumor–Immune Interactions and Effects of Checkpoint Inhibitor Immunotherapy

Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer

Suppression of Ocular Vascular Inflammation through Peptide-Mediated Activation of Angiopoietin-Tie2 Signaling

Immunoactivating the tumor microenvironment enhances immunotherapy as predicted by integrative computational model

Collaborators (4)

Brian Annex

Lu Lu

Samira Anbari

Natsuki Furukawa

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