Collabortive Research: Mathematical optimization for targeted macro-molecules delivery to the brain

点击翻译按钮获取中文摘要

Collaborative Research: Mathematical optimization for targeted macro-molecules delivery to the brainRichard PennUniversity of ChicagoCBET-0730043The goal of this research is to study a new computational approach to predict the distribution of infused therapeutic macromolecules in the human brain using advanced medical imaging techniques to measure brain geometry and tissue properties. In particular, the impact of tissue inhomogeneity and anisotropic drug distribution in the three-dimensional human brain will be incorporated. Optimal catheter placement for drug targeting will be computed to reduce toxicity and improve the effectiveness of treatments. Genome maps of receptors can be incorporated into the proposed mathematical model for determining the spatial distribution of the drug activity. This research will be carried out by an interdisciplinary research team composed of two biochemical engineers, a neurosurgeon, and an MRI physicist. Intellectual Merits: The proposed approach of three dimensional transport drug deliveries in the human brain will (i) bring together recent advancements in medical imaging and rigorous mathematical analysis, (ii) create mathematical formulations for the representation of the inhomogeneous and anisotropic properties of the brain, and (iii) account for the effect of infusion catheter placement. Broader Impacts: This research will integrate existing medical imaging technology with new mathematical modeling and scientific computing methods. The progress of creating computational grids of the human brain and symbolic codes for cerebral transport phenomena will be shared via the world-wide web to attract attention to the subject and create a growing scientific community. A large educational impact is expected because of the PI's commitment to high school math and science education via the NSF site for research experiences for teachers (RET), as well as his outreach to minorities and underrepresented groups through undergraduate research (REU) mentorship.