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NEOPANC-01 is a window of opportunity study looking to assess gene expression in patients with resectable pancreatic cancer. It aims to evaluate the utility of whole transcriptome RNA sequencing as a potential biomarker for future window-of-opportunity trials that will assess existing and/or new treatments for pancreatic cancer. An understanding of the variability in the transcriptomic signature between biopsies will also inform power calculations for future studies. Lastly, the data generated will be available for use as historical controls for future studies. 2 sets of biopsy samples will be taken throughout the trial. Firstly during an endoscopic ultrasound procedure and then again, up to 6 weeks later, during the patients surgery to remove the cancer. Once all patients have been recruited, the mRNA from the samples will be sequenced and analysed. Further samples will also be taken at the same time points for storage into a biobank and for use in future research. This is a single site study opening at the Churchill Hospital looking to recruit 10 patients over 18 months.
Our Projects
PHI has work that spans the worlds of climate change and health equity. Explore some of the themes of our work below, and find project pages, links and publications within them.
Amelia Doran
Amelia is a Science Communicator, and joined the PHI Lab in September 2023. She has a background in Biochemistry and research experience in science communication, and now leads on the various parts of PHI’s outputs.
Real-World Data and Federated Analytics
One key feature of our research is using data collected from the world around us. This could be de-identified patient records, weather station measurements or satellite imagery. This real-world international evidence uses federated analytics to safely and securely combine individual person-level data into valuable learning.
AI for Planetary Health
Artificial Intelligence is one of the biggest areas of development and innovation today. In our research, we are applying AI technology to tackle one of the greatest challenges facing healthcare systems across the globe: the impact of the environment and climate change.
COVID-19 Pandemic Response
Medical statistics was a key part of the response to the COVID-19 pandemic. Like many teams, we applied our experience with data analysis, real-world evidence and international collaboration to help healthcare systems around the world respond to the health crisis, and learn from it.
Machine Learning and Medical Statistics
Our lab applies machine learning in medical statistics, allowing us to identify patterns and insights in large amounts of health data. This can lead to improved diagnoses, treatments, and overall healthcare outcomes.
Fair and Safe Medical AI
As artificial intelligence continues to grow in its power and applications, we are harnessing its power to improve healthcare, making it fair and safe for all.
Sara Khalid
Sara is an Associate Professor of Health Informatics and Biomedical Data Science within the Centre for Statistics in Medicine. She trained in electrical and biomedical engineering prior to founding the PHI Lab, which studies data science and artificial intelligence for planetary health.
Improving Malaria Prediction Models
Using satellite data, including vegetation levels, nighttime lights, rainfall and temperature, connected to malaria levels in South Asia to improve malaria prediction models.
How Hot Temperatures change Physical Activity
Using de-identified data from fitness trackers connected with localised weather data to study the impact of extreme temperatures on sleep and activity.
Measuring the Humanitarian Impact of Flooding
Using satellite data to track the humanitarian impacts of flooding, particularly on schools, hospitals and roads.
Meet the Team
Meet the faces behind the PHI Team! We'll be adding interviews as we go, so check back to hear more about other team members!