Abstract:
Efficacy of the brain cancer drugs depends mostly on the type of cancerous tissue that are targeted for therapy and the characteristics of the drug itself. The movement of drug particles within the interstitial healthy tissues and tumor are dependent on the delivery method, nature of the medium, flow of the fluid and the size of the particles. Convection enhanced delivery is one of the emerging techniques in drug delivery to the tumor. However, most studies till now have been carried out using single inlet probe and case specific brain characteristics. In this study a computational model has been developed considering an outlet probe in addition to inlet probe which can enhance solute movement, increase drug recovery, and minimize side effects of the drugs. Agarose gel was selected to mimic the brain and Methylene Blue dye properties were used for defining the base model. The simulation was carried out with COMSOL MULTIPHYSICS which uses a finite element method to provide solutions for a specific model. The model was also simulated for authorized cancer drugs Temozolomide and Avastin. The study ranged from simple matrix model to mixed matrix model that miniatures the real-life scenario. The model with an output probe showed altered concentration profile in the outlet side compared to a single probe scheme. Concentration profile and diffusion pattern were studied for varying molecular mass, probe distance, matrix properties, holes in probe and dosing variations. The study revealed that the impact of molecular size of the particles has significant impact on the concentration of solute inside the matrix. Dosing variation has large impact if changed to a higher value and probe distance can be a key factor for targeted delivery of drugs. In contrast to the single probe model the two probe model provided concentration enhancement in desired regions and showed that convective effect can result in effective drug transport to selected tissues. Furthermore, the studied model can be a good indicator to identify the parameters that impact drug delivery the most and suggest ways to optimize these. The developed computational model is simple yet highly flexible to change any characteristics of the brain as well as the drug. Moreover, the model can incorporate case specific modifications and provide results for critical cases where early diagnosis is required.
