COMPREHENSION OF PHYSICAL FUNDAMENTALS OF PHOTODYNAMIC THERAPY: STUDY ABOUT DIFFUSION OF ALA AND DISTRIBUTION OF PPIX

Photodynamic therapy (PDT) is a minimally invasive approach combining light, oxygen, and a photosensitizer (PS) to treat non-melanoma skin neoplasms, such as basal cell carcinoma (BCC). Currently, Amaral Carvalho Hospital in Jaú applies a standardized PDT protocol consolidated by decades of research. Using methyl aminolevulinate (MAL), ester of δ-aminolevulinic acid (ALA), with a drug-light interval (DLI) of 3 hours to generate optimal protoporphyrin IX (PpIX) accumulation, this protocol yields complete response rates of 85–90% in superficial lesions. Patient differences in lesion thickness, tissue optical properties, and drug penetration cause PpIX accumulation to vary, making a fixed DLI suboptimal. Consequently, this project develops a mathematical model of ALA or MAL kinetics following topical administration, optimizing the DLI based on specific tumor characteristics. Enabling personalized PDT, the proposed model will improve therapeutic outcomes and reduce pain during illumination by preventing unnecessarily long incubation times. The initial phase of this research requires a detailed understanding of the physical and biological phenomena underlying PDT. Once the therapeutic stages and their epithelial tissue effects are consolidated, a mathematical model is developed to describe transdermal ALA diffusion, intracellular PpIX production, and clearance mechanisms. The model is formulated as a system of differential equations with spatial dependence, representing molecular penetration depth, and temporal dependence, describing the dynamics from ALA/MAL topical application. Presently, several models based on literature have been analyzed and integrated into a unified model based on Fick's diffusion laws, general model equations, Michaelis–Menten kinetics, enzymatic transformation of ALA into PpIX, and clearance mechanisms, such as biotransformation into heme or cellular efflux. Although the theory behind these procedures is robust and provides a solid basis for computational modeling, the high variability among patients and clinical lesions makes it challenging to develop a unified model. Addressing this complexity requires rigorous attention to the characteristics that bridge the fields of physics, pharmacochemistry, and cellular biology. The proposed model represents an important step toward predictive PDT dosimetry and personalized treatment planning. Future work will focus on parameter estimation using clinical data and experimental validation of the model.

This work was supported by Conselho Nac. Des. Cient. Tecnologico (CNPq 184410/2025-8).