1 year
Duration
Multimodal Siamese Network for Parkinson's Disease Diagnosis and Computational Drug Discovery
A conceptual exploration of balance, movement, and minimal layout through experimental design.
Computational Pharmacology
Industry
Date
Problem Statement
Methods
Working on this computational pharmacology project was incredibly meaningful because it allowed me to apply artificial intelligence to a real-world healthcare challenge like Parkinson’s disease. I learned how to integrate complex data—such as MRIs and biomarkers—into a multimodal Siamese network to improve diagnostic accuracy. Furthermore, by using tools like Chimera X and DiffSBDD to analyze the IL-6 protein, I gained hands-on experience in the computational drug discovery pipeline and successfully designed promising drug candidates.
Experience
Working on this computational pharmacology project allowed me to apply artificial intelligence to a real-world healthcare challenge like Parkinson’s disease. I learned how to integrate complex data, such as MRIs and biomarkers, into a multimodal Siamese network to improve diagnostic accuracy. Furthermore, by using tools like Chimera X and DiffSBDD to analyze the IL-6 protein, I gained hands-on experience in the computational drug discovery pipeline and successfully designed promising drug candidates.
