Amir Shalan

• Characterized AI-designed peptide-MHC binders targeting cancer antigens to support the development of novel T-cell-based immunotherapies.
• Performed ELISA, flow cytometry, qPCR, and contributed to computational protein modeling and data analysis in a translational oncology setting.

• Worked in a cross-functional team to establish and validate a qPCR-based cancer mutation profiling workflow for diagnostics.

• Assessed the anti-tumor efficacy of the XPO1 inhibitor Selinexor in testicular germ cell models, as part of a preclinical oncology project aimed at identifying novel therapeutic strategies.
• Contributed to the design and execution of cell culture assays, supporting the development and optimization of drug testing protocols in collaboration with pathology researchers.

Focus: Translational Immuno-Oncology.

Thesis title: Validation of AI-designed pMHC mini-binders against cancer surface markers.

Thesis title: Komplementation von mgd1- und dgd1-Arabidopsis-Mutanten mit homologen Sequenzen von Bakterien