The Blood Brain Barrier (BBB) is a network of tight-junction brain endothelial cells that restricts pharmaceutical diffusion into the brain and leads to inaccurate dosage. This research focuses on using a novel predictive model to simulate transport for 25 commonly used drugs in brain dysfunctions. Paper emphasizes the integration of Ficks and Einstein-Stokes Laws to derive a parametrized function representing drug diffusivity. The function is constructed on calculated values of j-flux, diffusion coefficient, radius, and polarity; viscosity is a constant to model BBB fluidity. The equation is integrated from t in 0, , the barrier at t =, and yields a measure of moles limited when diffused. We devise a rank formula, denoted H (x), to weight drugs with respect to numerical diffusibility. Inputs employ min-max normalization to ensure the domain occupies 0, 1, standardizing values. Weight scores produced are shown through heatmaps to measure total diffusivity. Results showed Levodopa and Temozolomide scored highest, with weighted scores of 5. 22 and 5. 13 respectively. Conversely, Vancomycin and Paclitaxel attained the lowest. These results are consistent through viscosity modulation, achieving similar rank distributions. This validates the model's accuracy. The model weighs chemical factors to produce predictive permeability scores, avoiding in vitro costs and time. Future adaptations follow inclusion of Markov Chains to model BBB movement.
Nithik Uppara Allabanda (Tue,) studied this question.