Harvard Undergraduate OpenBio Laboratory

Personalizing Pharmacological Treatments for Chronic Myeloid Leukemia

A hybrid quantum-classical computing stack for personalized cancer treatment optimization

Quantum ComputingQAOAAlphaFold2Drug DiscoveryMachine Learning
View Source Code on GitHub

Program Certificate

Harvard OpenBio Student Research Institute

Completed the Harvard Undergraduate OpenBio Laboratory Student Research Institute program, conducting original research on personalizing pharmacological treatments for Chronic Myeloid Leukemia using a hybrid quantum-classical computing approach.

Summer 2025

Research Poster

Research poster: Personalizing pharmacological treatments for Chronic Myeloid Leukemia (CML) with a hybrid quantum-classical computing stack

Research Paper

Important Note: Project In Progress

This project is not complete, and the data shown in the figures above is incorrect due to a bug. The binding site of the ligands was mistakenly set to the geometric center of the protein, and as such the mentioned and intended use of the pipeline cannot be relied upon.

However, the binding affinities can be reconsidered as indicators of adverse reactions due to substrate ambiguity, which are potential key indicators of adverse effects such as cardio-toxicity.

This project is in progress.