Convective Drug Transport in the Spinal Cord

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DESCRIPTION (provided by applicant): With the development of promising therapeutic agents for chronic pain, spinal injury, and other neurodegenerative diseases, local drug delivery methods are increasingly being considered as a solution to overcoming transport barriers encountered by macromolecular, slow-diffusing drugs. Intelligent design of regional therapy will require new tools to evaluate drug transport issues specific to nervous tissue physiology. Recently, the PI has presented a method for predicting the local tissue distribution of an injected macromolecule in the spinal cord. Medical image-based computational models are created to determine interstitial (extracellular) fluid flow and convective and diffusive transport in white and gray matter regions. Further research is warranted to develop this approach for intraneural infusion and convective transport at nerve entry into the spinal cord. The PI plans to implement a novel application of diffusion weighted imaging (DWI) technology which will use the effective water diffusion tensor to predict preferential interstitial transport directions along white matter tracts. Computational fluid dynamic (CFD) models will integrate DWI data with porous media transport analysis to create 3D models of direct nerve infusion into spinal cord tissue targeted as an alternative, less invasive delivery site. Concurrently, a pressure sensor system will be developed to measure interstitial fluid pressure gradients and characterize hydraulic conductivity. The relationship between transport properties and infusion mechanics will be validated and further improved by fitting predicted distributions to macromolecular tracer data obtained in rat spinal cord studies. Successful physiologically-based drug delivery models can be used for feasibility studies and improved drug protocols. Ultimately, image-based drug transport modeling provides the first step toward computer-aided chemical surgery and patient-specific therapeutic treatment. This will enable customized medical care for patients that inherently factors in physiological differences due to age, gender, and/or disease progression.