Hubrecht Organoid Technology and GlaxoSmithKline will together develop a human relevant Lung and Colon Immuno-Oncology model using Tumor Organoids, to better predict drug effectiveness for small molecule therapies.
The RBD‐CURE project will develop innovative gene therapy approaches for patients with rare bleeding disorders. The unique expertise of Sanquin on bleeding disorders together with the advanced gene therapy strategies developed by SanaGen and the Netherlands Institute for Neurosciences aims to provide a permanent cure for patients with rare bleeding disorders.
Hepatocellular carcinoma is the most frequent liver malignancy and the fourth most common cause of cancer-related death worldwide. There is a clear clinical need for accessible and reliable parameters to identify high-risk populations in order to decrease the high mortality rates of hepatocellular carcinoma.
To help in the battle against COVID-19, a novel compact CT scanner will be developed to rapidly screen for disease patterns and monitor disease progression. This is done by developing a new type of compact mobile CT scanner, equipped with artificial intelligence software to detect disease patterns accurately.
The cancer grade, provided by pathologists, is the most important predictor of patient outcome, but suffers from inter- and intra-pathologist variability, reducing its usefulness for individual patients. An expert-level AI system will be provided to support pathologist and help reduce this variability and make their diagnostic practice more accurate and efficient.
COVID-19 is taking a huge toll among healthcare workers worldwide: researchers are warning that the coronavirus pandemic could inflict posttraumatic stress disorder on an unprecedented global scale. Here, the aim is to implement a novel treatment strategy – that yields long-term cure within a single treatment-session – for traumatised healthcare workers during COVID-19.
A successful societal uptake of digital eye health requires a robust and safe telemonitoring platform that addresses the needs of its users. Patients request a simple tool that works intuitively with little external instructions. Doctors need a dataflow fully integrated in the electronic health record, and both need to develop trust in the validity and safety of remote monitoring. These requirements are addressed in this project.
Photon attenuation correction methods for PET-MRI are currently developed using CT transmission images obtained prior to the PET-MRI scan. Their accuracy is limited by differences due to patient movement. A transmission scan mechanism will be integrated into the PET-MRI system, capable of acquiring transmission images simultaneously during the PET-MRI scan.
The application of simultaneous MRI-PET in the planning of (radio)therapy is currently hampered by the concessions done in the design of current MRI-PET scanners. In this project, a prototype MRI-PET system was designed and built which delivers improved PET sensitivity, spatial resolution, and bore diameter without compromising MRI performance.
To improve individual healthcare artificial intelligence will be used for objective quantitation of patient imaging and pathology outcomes. Subsequently these algorithms can be validated and integrated into a tumor dashboard setting to support multidisciplinary clinical decision making.