There are many promising treatments for neurological disorders. The work in this dissertation is aimed at addressing some of the issues associated with delivery of drugs to the brain. A major focus of this work is the study of transport phenomena of therapeutic agents through neural tissues. First, we carry out a theoretical analysis to investigate the fluid mechanics in the perivascular space (PVS). Our calculations indicate that peristaltic motion of the blood vessel walls can facilitate fluid and solute transport in the PVS. We then consider the impact of ultrasound exposure on neural drug delivery. We find that under certain conditions two acoustic waves can coexist and one of them has an extremely large penetration depth. We make a third analysis on the retro-convection-enhanced drug delivery (R-CED). The model is used to predict the pressure distribution, the fluid flow pattern, and the drug concentration profile in R-CED. The effectiveness of R-CED to achieve a large treatment volume is called into question. We make a fourth analysis to describe nanoparticle transport in the brain. We explicitly take the hydrodynamic interactions between the nanoparticles, the carrying fluid, and the brain tissue into account. We devote the fifth analysis to the solid mechanics involved in cerebral microhemorrhage. The steady-state and the time-dependent behaviors of the displacement vectors are examined. Then, we describe the design and fabrication of a microfluidic probe with a capacitive pressure sensor integrated at its tip. Such a device should be able to monitor the tip pressure in convection-enhanced drug delivery (CED) and serve as an indicator of the onset of serious backflow problems or other failures. Finally, we present the fabrication and characterization of a micromachined dissolved oxygen sensor based on solid polymer electrolyte. The small size of the whole device and the simplicity of the fabrication process make these devices promising for medical uses. Single devices are shown to have decent performances in terms of long term stability, reliability, hysteresis, linearity, and sensitivity. Variations among different devices are characterized and correlated and methods for reducing such variations are proposed.