In the Integrative Pancreatic Cancer Research (iPanCare) Lab, we aim to advance understanding of pancreatic cancer, with a particular emphasis on precision prevention, diagnostics and medicine. Our work focuses on developing strategies for personalized prevention, individualized risk prediction, early detection, and tailored therapeutic and prognostic tools for pancreatic cancer.
The lab employs integrative approaches of classical epidemiology, genetic and molecular epidemiology, and machine learning algorithms to dissect this lethal disease by leveraging large population-based cohorts, national registries, biobanks, and electronic healthcare records and clinical images. Through innovatively applying diverse data sources with advanced analytical methodologies, we identify key factors contributing to the development and metastasis of pancreatic cancer, and tools for early cancer detection.
Our research findings will provide new knowledge of pancreatic cancer for further scientific research and facilitate the development of personalized screening programs, individualized treatments, and surveillance strategies. Our research holds significant potential for improving earlier diagnosis and survival of pancreatic cancer.
Group Members:
Ana Camila Vásquez (master student)
Ellen Amper (bachelor student)
Minghao Chen (master student)
Naiqi Zhang (postdoc)
Soroush Ghodratipoor (master student)
Zheng Su (postdoc)