Eunjung Kim

Discovery of a potent anti-Zika virus benzamide series targeting the viral protein NS4B

This paper identifies potent benzamide compounds against Zika virus by targeting NS4B, showing superior potency and novel resistance mutation patterns compared to existing treatments.

Using neural networks to bridge scales in cancer: Mapping signaling pathways to phenotypes

The paper uses a neural network to model how intracellular signaling pathways influence cancer cell phenotypes under varying microenvironmental conditions.

Targeting the Untargetable: Predicting Pramlintide Resistance Using a Neural Network Based Cellular Automata

This paper develops a hybrid neural network/agent-based model to predict Pramlintide resistance in cutaneous squamous cell carcinoma and enable personalized treatment decisions.

Harnessing the lymphocyte meta-phenotype to optimize adoptive cell therapy

This paper explores using a lymphocyte meta-phenotype to improve adoptive cell therapy outcomes by integrating patient data with mathematical models.

Phase i trials in melanoma: A framework to translate preclinical findings to the clinic

The paper proposes a computational framework for virtual phase I trials in cancer using a calibrated mathematical model of melanoma treatment to optimize clinical trial design.

Dissecting resistance mechanisms in melanoma combination therapy

The paper develops a compartment model to analyze melanoma cell response to mono and combination therapies, showing that timing is critical for long-term efficacy but eventual treatment failure occurs.