Welcome to the Butch/Wang Joint Research Group in the Department of Biomedical Engineering at Nanjing University.
Tackling cancer's greatest challenges through data-driven research, innovative engineering, and translational science.
Highlights:
2025.06.25 - Advanced Functional Materials - Rapid Personalized Therapeutic Cancer Vaccines
We've published breakthrough research in Advanced Functional Materials that could transform how we prevent cancer from coming back after surgery. Our team developed a personalized cancer vaccine that can be produced in just 72 hours using the patient's own tumor cells—a dramatic improvement over current cell therapies that take 6-8 weeks.
2025.04.07 - Analytical Chemistry - Image Processing links Fluorescence to Cancer Pathology for Clearer Intrasurgical Tumor Boundaries
We've published new results in Analytical Chemistry demonstrating that by stratifying fluorescence signal by standard deviations above background, we demonstrated that SNR thresholds correlate strongly with cancer probability. The approach was validated first in xenograft models and then successfully translated to clinical samples through our collaboration with China Medical University, achieving millimeter scale diagnosis with 87.5% accuracy with no false negatives.
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2025.06.10 - Congratulations to our Graduating Students!
Today, I am happy to announce the graduation of four of our students.
Days like today are the real culmination of all the effort in our laboratories. Doing science, and creating new knowledge is an incredible fulfilling pursuit. But even more than that, training new scientists, and (I hope) instilling them with the same curiosity that motivates me to do the hard scientific work is even more so. This year is my largest group of graduates so far, and I am quite proud of all they have accomplished during their time in our group.
Congratulations to our graduates. We wish you all the best in your next steps. 2025.01.06 - Our collaboration with IceKredit finished 3rd of 505 teams in Baidu's Second Global AI Drug R&D Algorithm Competition
This year we have again obtained a third-prize finish in Baidu and Tsinghua University's "Global AI Drug Discovery Competition". This year's challenge focused on predicting quantum chemical properties of sesquiterpene molecules—a significant step up in complexity from traditional drug discovery problems. The challenge specifically targeted one of the field's most pressing issues: model generalization to features and properties outside the training data set.
Our multiscale deep learning approach proved well-suited to this challenge, leveraging both local geometric features and longer-range molecular fingerprints to improve accuracy in predicting the activity of unknown compounds. This methodology demonstrates the versatility of our computational frameworks across different scales of molecular modeling problems. The consistent performance across consecutive years validates our team's approach to developing robust, generalizable AI models for pharmaceutical applications. |
