In early 2018, leaders from the College of Engineering and The Ohio State University Comprehensive Cancer Center began synthesizing cancer-related research activity across the medical and engineering campuses to establish a campus-wide team of experts that together develop solutions and technologies leading to fundamental and clinical discoveries.
The program will serve as a nexus for new training opportunities, high-impact collaborative research, collaborative cross-disciplinary funding as well as technology development and transfer.
Areas of Concentration
Multimodal and Multiscale Imaging and Detection
- Develop advanced microscopy methods for intracellular molecular imaging at sub-nanometer single molecule resolution to real-time tracking at diffraction-limited resolution
- Develop molecular analysis for structure/function studies and drug design
- Develop new methods to identify cell types and circulating tumor cells based on biological, chemical or physical properties
- Develop high throughput methods to confirm biological functions, molecular or cellular interactions or drug screens
- Develop non-invasive imaging for inflammation/immune activation to predict side effects and response
Tissue Engineering, Biomaterials, Biomechanics and Drug Delivery
- Development of innovative cell culture technologies (e.g., bioreactor, 3D culture, clean room technologies) to increase cell and tissue viability to support basic research and clinical trials
- Biofabrication (bioprinting, bioplotting and solid curing) of tissue scaffolds and tissues for organoid and tumor microenvironment modeling
- Develop therapeutic biomaterials for surgery and localized biomedical administration
- Develop nanostructures or nanomaterials for drug delivery and immunotherapy
- Design and development of materials for controlled fluid delivery/fluid dynamics and biosensors to model cancer evolution and metastasis.
- Develop high-throughput systems using engineered models and organoids for compound screening and target validation
- Develop predictive biomechanical models of the natural history of bone related cancers to inform and improve treatment
Machine Learning/Artificial Intelligence
- Develop machine learning and/or artificial intelligence algorithms for multi-omics data analytics (phenotypes, genomic, proteomics, transcriptomics, metabolomics, etc.) as well as imaging and clinical records
- Develop applications to imaging and structural data for biomechanical modeling, understanding and predicting disease progression, and virtual surgical/non-surgical planning
- Develop applications for structure predictions to drug design and development