Mahadevabharath R. Somayaji

Computational methods for predicting drug transport in anisotropic and heterogeneous brain tissue

Effective drug delivery for many neurodegenerative diseases or tumors of the central nervous system is challenging. Targeted invasive delivery of large macromolecules such as trophic factors to desired locations inside the brain is difficult due to anisotropy and heterogeneity of the brain tissue. Despite much experimental research, prediction of bio-transport phenomena inside the brain remains unreliable. This article proposes a rigorous computational approach for accurately predicting the fate of infused therapeutic agents inside the brain. Geometric and physiological properties of anisotropic and heterogeneous brain tissue affecting drug transport are accounted for by in-vivo diffusion tensor magnetic resonance imaging data. The three-dimensional brain anatomy is reconstructed accurately from subject-specific medical images. Tissue anisotropy and heterogeneity are quantified with the help of diffusion tensor imaging (DTI). Rigorous first principles physical transport phenomena are applied to predict the fate of a high molecular weight trophic factor infused into the midbrain. Computer prediction of drug distribution in humans accounting for heterogeneous and anisotropic brain tissue properties have not been adequately researched in open literature before.

Systematic design of drug delivery therapies

This paper presents an engineering approach for optimal drug delivery to the human brain. The hierarchical design procedure addresses three major challenges: (i) physiologically consistent geometric models of the brain anatomy, (ii) discovery of unknown transport and metabolic reaction rates of therapeutic drugs by problem inversion, and (iii) a rigorous method for determining optimal parameters for delivering therapeutic agents to desired target anatomy in the brain. The proposed interdisciplinary approach integrates medical imaging and diagnosis with systems biology and engineering optimization in order to better quantify transport and reaction phenomena in the brain in vivo. It will enhance the knowledge gained from clinical data by combining advanced imaging techniques with large scale optimization of distributed systems. The new procedure will allow physicians and scientists to design and optimize invasive drug delivery techniques systematically based on in vivo drug distribution data and rigorous first principles models.

Rigorous Mathematical Modeling Techniques for Optimal Delivery of Macromolecules to the Brain

Several treatment modalities for neurodegenerative diseases or tumors of the central nervous system involve invasive delivery of large molecular weight drugs to the brain. Despite the ample record of experimental studies, accurate drug targeting for the human brain remains a challenge. This paper proposes a systematic design method of administering drugs to specific locations in the human brain based on first principles transport in porous media. The proposed mathematical framework predicts achievable treatment volumes in target regions as a function of brain anatomy and infusion catheter position. A systematic procedure to determine the optimal infusion and catheter design parameters that maximize the penetration depth and volumes of distribution will be discussed. The computer simulations are validated with agarose gel phantom experiments and rat data. The rigorous computational approach will allow physicians and scientists to better plan the administration of therapeutic drugs to the central nervous system.