ECCOMAS 2024

A Computational Framework for Mechanically Controlled Brain Drug Delivery

  • Yuan, Tian (Imperial College London)
  • Pecco, Nicolo (Vita-Salute San Raffaele University)
  • Zhan, Wenbo (University of Aberdeen)
  • Jamal, Asad (Imperial College London)
  • Riva, Marco (Humanitas University)
  • Falini, Andrea (Vita-Salute San Raffaele University)
  • Rodriguez y Baena, Ferdinando (Imperial College London)
  • Castellano, Antonella (Vita-Salute San Raffaele University)
  • Dini, Daniele (Imperial College London)

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Brain tumour, especially Glioblastomas, has been a health challenge worldwide. Developing effective treatments has been one of the major concerns [1]. While pharmacotherapy is a common treatment for various brain tumours, delivering drugs into the brain is difficult due to the selective permeability of the Blood-Brain Barrier (BBB), a protective barrier that prevents harmful substances, together with most of the drug molecules, from entering the brain. Despite new techniques have been developed to penetrate the BBB, such as Convection-Enhanced Delivery (CED) method, which implants catheters in the brain to deliver the drugs directly into the target area by applying pressure gradient, few desired results have been achieved in clinical trials [2]. The failures include undesired and uneven drug distribution, backflow of drugs, and tissue damage. As a mechanically triggered and controlled drug delivery technique, these problems in CED ultimately come from the current poor understanding of the mechanical and hydraulic interactions between drugs and the brain. The anisotropic and heterogeneous microchannels of the brain, formed by the extremely soft and easily deformable neuron, make the mass transport within the brain extremely complex, unsteady, and hard to predict [3]. To fill this gap, we have established a new multiscale and multiphysics mathematical framework underpinned by experiments to provide accurate predictions for drug delivery process in the brain. By achieving this goal, we have successfully: (i) gained a deeper understanding of the drug-brain interactions across the neuron, tissue, and organ scales, and mathematically described them [4,5,6]; (ii) built upscale techniques to correlate the drug-neuron interactions to drug transport properties of the brain [7]; (iii) established a multiscale framework to predict the drug delivery process in the brain [8]; (iv) validated the models by experiments at different scales and validated the whole framework by in vivo drug delivery experiments with sheep.