Discovery Fund supports innovative cancer and neurodegenerative disease projects

October 12, 2026

Two research proposals from chemistry faculty members have been selected to receive grants from the Department of Chemistry's Discovery Fund, which was established in 2018 to provide funding for innovative research in chemistry and is generously supported by a gift from chemistry alumni Ving Lee (PhD, ‘75, Rinehart) and May Lee (PhD, ‘76, Rinehart). This marks the eighth consecutive year that the fund has supported chemistry research projects in the initial discovery phase.

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Head shot of professor Jeff Chan on a white background

Jeff Chan will pursue cancer detection through simple screening methods

For many cancers, treatment is most effective when disease is detected early, yet diagnosis often occurs only after tumors have progressed or become symptomatic.

What if a simple blood or urine test could identify cancer in its earliest stage? That’s the goal of researchers in the lab of Prof. Jeff Chan. They will begin work to establish a fundamentally different approach to cancer detection where the tumor signals its presence in the body through simple screening methods that are used as early warning systems for a variety of diseases. 

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Head shot of Liviu Mirica

Liviu Mirica seeks to improve neurodegenerative disease imaging

Scientists and medical professionals studying and treating neurodegenerative diseases such as Alzheimer’s and Parkinson’s rely on neuroimaging agents that enter the brain, bind to disease-related proteins, and generate signals detectable by PET or MRI scans. 

Liviu Mirica’s project will develop a customizable imaging platform that more effectively targets these diseased proteins and produces stronger signals for PET, MRI, and other imaging techniques. Current neuroimaging agents combine brain penetration, target recognition, and signal generation in a single molecule, creating trade-offs in performance. Improving one property often compromises another. Mirica’s approach uses a two-step system that separates protein targeting from signal delivery, reducing these trade-offs.