A Review of Quantifying Drug Diffusion in Human Tissues for Assessing Drug Dispersion in the Body

Understanding the mechanisms and effectiveness of drug diffusion in human tissues is critical for advancing precision medicine and optimizing therapeutic strategies. This thesis presents a comprehensive bibliographic and methodological review of current approaches for evaluating drug diffusion, emphasizing the integration of pharmacokinetics, thermodynamics, and state-of-the-art imaging technologies. Central to this investigation is the role of magnetic resonance imaging (MRI), with a particular focus on diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) sequences, which serve as powerful, non-invasive tools for visualizing drug dispersion, assessing tissue permeability, and monitoring pharmacodynamic interactions in vivo. This work inquiries into the application of mathematical and physical models to describe and predict drug transport phenomena. Models based on Fick’s law of diffusion and Darcy’s law for fluid flow are examined alongside tracer-kinetic models and thermodynamic concepts such as Gibbs free energy. These frameworks provide a theoretical basis for simulating molecular movement across complex biological barriers and heterogeneous tissue environments. Emphasis is placed on the importance of combining empirical data from imaging studies with computational simulations to achieve more accurate and meticulous predictions of drug behavior. Special attention is dedicated to pediatric pharmacotherapy, a field that presents unique challenges due to anatomical and physiological variability, limited availability of patient data, and strict ethical constraints on invasive procedures. The use of non-invasive imaging modalities and computational models becomes especially valuable in this context, offering safer alternatives for assessing drug efficacy and optimizing dosing regimens in vulnerable populations. Furthermore, the thesis explores the clinical and translational potential of emerging technologies, including the use of nanoparticles for targeted delivery and the application of artificial intelligence (AI) for image analysis, parameter estimation, and model personalization. Illustrative case studies and optimized imaging protocols are discussed to demonstrate real-world applications and highlight areas for future development. By integrating multidisciplinary methodologies - from biophysics and pharmacology to medical imaging and computational modeling - this research proposes a comprehensive framework aimed at enhancing the precision, efficacy, and safety of drug administration in both adult and pediatric populations. The findings and recommendations presented herein aim to support the development of more individualized therapeutic strategies and contribute to the evolving landscape of precision medicine.