Rostyslav Marunych

Photodynamic therapy (PDT) is a minimally invasive therapeutic approach based on the light-induced activation of a photosensitizer in the presence of molecular oxygen, resulting in the generation of reactive oxygen species, including singlet oxygen. Despite local selectivity and low systemic toxicity, reproducibility of PDT is restricted by non-uniform accumulation of the photosensitizer, aggregation and insufficient solubility of compounds, variability in the optical properties of tissues, hypoxia, oxygen consumption, photobleaching, and the lack of a universal measure of photodynamic dose. Artificial intelligence (AI), including machine learning and deep learning, graph neural networks, generative models, Bayesian optimization, and physics-informed neural networks, can integrate molecular, spectral, imaging, dosimetric, omics, and clinical data into decision-support systems. In this review, a closed AI–PDT cycle is considered, which includes the in silico design of photosensitizers, optimization of nanoformulations and delivery, personalized light exposure planning, real-time monitoring of photobleaching and oxygenation, and prediction of efficacy, toxicity, immune response, and long-term outcomes. Particular attention is given to data quality, external validation, interpretability, uncertainty assessment, and clinical readiness. This review emphasizes that the greatest potential of AI in PDT lies in its integration with mechanistic models of photochemistry, light transport, and oxygen dynamics, enabling the transition from empirical treatment protocols toward adaptive, reproducible, and personalized photomedicine. Unlike reviews focused on individual AI applications, this work considers the entire AI–PDT workflow as an interconnected system linking molecular design, drug delivery, dosimetry, treatment monitoring, and outcome prediction, while maintaining clinician oversight and the need for experimental and clinical validation.

Protoporphyrin IX (PpIX) occupies a unique nexus in photodynamic therapy (PDT) by bridging the endogenous metabolism of heme biosynthesis with highly efficient, light-induced cytotoxicity. Administered via its precursor 5-aminolevulinic acid (5-ALA) or its derivatives, intracellularly generated PpIX undergoes intersystem crossing upon irradiation to predominantly initiate Type II photochemistry. This process yields singlet oxygen and ancillary reactive oxygen species (ROS) characterized by a strict, nanometer-scale radius of molecular attack. Consequently, the spatiotemporal kinetics of PDT are dictated by the precise subcellular compartmentalization of PpIX within the mitochondria, mitochondrial-associated membranes (MAMs), endoplasmic reticulum, lysosomes, and plasma membrane. Beyond inducing direct biomolecular damage, PpIX-PDT operates as a localized selector of complex signaling networks, orchestrating organelle communication, redox-mediated pathways, and cell fate adaptations. This comprehensive review systematically delineates the metabolic parameters governing intracellular PpIX accumulation, the biophysical mechanisms driving its excitation, and the subsequent cascade from primary oxidative stress to downstream signaling responses. Crucially, we present a novel, integrated framework that seamlessly connects upstream transporter kinetics and metabolic flux directly to downstream immunogenic and therapeutic outcomes. Ultimately, these multifaceted properties establish 5-ALA-mediated PpIX-PDT as a powerful theranostic platform, advancing pathway-oriented and personalized strategies to optimize modern anticancer interventions.

This review analyzes how Zinc(II) coordination alters the electronic configuration of porphyrin-based photosensitizers to optimize reactive oxygen species (ROS) generation and subcellular targeting in photodynamic therapy (PDT). By focusing on the structural design principles that govern excited-state behavior, the work moves beyond clinical descriptions to provide a mechanistic understanding of how engineered metalloporphyrins can achieve precise tumor destruction. When these engineered metal porphyrins are exposed to specific wavelengths of light, they transfer energy to create ROS, such as singlet oxygen, which directly damages and kills tumor tissue. The review evaluates structural modifications that drive selective accumulation within critical subcellular organelles, notably the mitochondria, to maximize cytotoxic efficiency. By analyzing the impact of the tumor microenvironment on hypoxia, the work outlines strategies for maintaining efficacy in oxygen-deprived zones and highlights how the biocompatible, redox-inactive nature of Zinc(II) minimizes systemic toxicity, providing a blueprint for the design of targeted, translation-ready photosensitizers.

Photodynamic therapy (PDT) represents a promising non-antibiotic strategy for addressing bacterial and fungal infections, particularly in the context of increasing antimicrobial resistance and biofilm-associated disease. PDT is based on the light-induced activation of photosensitizers, leading to the generation of reactive oxygen species (ROS), including singlet oxygen (¹O₂), which induce oxidative damage to multiple microbial targets. Unlike conventional antimicrobial drugs that often act through specific molecular pathways, antimicrobial PDT produces simultaneous damage to membranes, proteins, nucleic acids, and extracellular biofilm components, thereby reducing the probability of resistance development. This review critically analyzes the cellular, biochemical, and biophysical determinants that govern PDT selectivity toward bacterial and fungal cells in comparison with mammalian host tissues. Particular attention is given to photosensitizer localization, membrane interactions, photobleaching, oxygen dependence, light penetration, and the balance between Type I and Type II photochemical mechanisms. The review provides a comparative overview of major molecular photosensitizer classes, including phenothiazines, porphyrins, chlorins, phthalocyanines, xanthene dyes, natural polyphenols, endogenous compounds, and advanced targeted photosensitizers. In addition, this review distinguishes molecular photosensitizers from nanotechnology-based platforms and delivery systems. Nanoparticles, polymeric carriers, hydrogels, and light-activated coatings are discussed not only as photosensitizer delivery tools, but also as systems that modulate aggregation, improve localization, enhance biofilm penetration, and enable surface-confined ROS generation. ROS are capable of causing phototoxic effects wherever they are located. Unless selectively accumulated by target organisms, there can be systemic phototoxicity. Overall, PDT should be regarded as a modular antimicrobial platform in which photosensitizer chemistry, formulation, light delivery, oxygen availability, and infection biology must be co-optimized. Although further studies are required to address clinical translation, regulatory complexity, material safety, and standardized treatment protocols, PDT offers a scientifically robust and clinically relevant approach that may complement conventional antibacterial and antifungal therapies, especially in localized, biofilm-associated, and device-related infections.

Glioblastoma (GBM) remains one of the most aggressive malignancies, characterized by profound heterogeneity and a dismal prognosis. While genomic and transcriptomic profiling have provided structural insights, they often fail to capture the dynamic interactions within the tumor microenvironment (TME). Secretome analysis—the study of proteins actively secreted by tumor cells—offers a functional readout of these interactions and a reservoir for potential biomarkers. In this review, we critically evaluate the role of MALDI-TOF Mass Spectrometry as a strategic tool for GBM secretome profiling. While Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) remains the gold standard for deep protein discovery, we argue that MALDI-TOF’s speed, cost-effectiveness, and high-throughput capabilities position it as an ideal platform for clinical screening and “spectral phenotyping.” We discuss the technical hurdles, such as ion suppression and the “leakome” (intracellular contamination), and highlight how integrating MALDI with Extracellular Vesicle (EV) enrichment and Artificial Intelligence (AI) can bridge the gap between in vitro discovery and clinical application.

Magnetic resonance techniques have evolved beyond conventional proton-based imaging, enabling access to a broader range of nuclei that provide complementary structural, functional, and molecular information. This review presents a comprehensive overview of multinuclear NMR and MRI in solid and soft materials as well as in biomedical applications, with particular emphasis on ¹H, ¹³C, ³¹P, ²³Na, and ¹⁹F nuclei. Proton-based methods remain the foundation of magnetic resonance due to their high sensitivity and widespread applicability, offering insights into molecular mobility, hydration, and microstructural heterogeneity. In contrast, heteronuclear approaches enable more specific characterization of chemical structure (¹³C), phosphorus-containing functional groups and membranes (³¹P), ionic homeostasis and transport (²³Na), and exogenous tracers with negligible biological background (¹⁹F). Together, these techniques extend magnetic resonance from primarily anatomical imaging toward functional, metabolic, and molecular-level analysis. The review further discusses key hardware aspects, including magnetic field strength and radiofrequency coil design, highlighting the trade-offs between low- and high-field systems and the growing importance of multinuclear coil architectures. For example, because ¹H, ²³Na, ³¹P, and ¹⁹F resonate at different Larmor frequencies, multinuclear experiments require dedicated or multi-tuned RF coils that balance sensitivity, field homogeneity, and decoupling between channels. Mechanisms of contrast generation are examined in detail, distinguishing between endogenous sources—such as water, ions, and metabolites—and exogenous contrast agents, including gadolinium-, manganese-, and fluorine-based compounds, as well as targeted and theranostic platforms. A comparative framework of endogenous and exogenous signals is presented, emphasizing their complementary roles in balancing safety, specificity, and sensitivity. Finally, the opportunities and challenges of multinuclear magnetic resonance are critically evaluated, including limitations in sensitivity, signal-to-noise ratio, data interpretation in heterogeneous systems, and technical complexity. Emerging directions such as ultrahigh-field imaging, advanced RF technologies, hyperpolarization, and artificial intelligence-assisted reconstruction are discussed as key drivers for future development. Overall, multinuclear NMR and MRI represent a powerful and expanding toolbox for probing complex material and biological systems, with the potential to significantly enhance diagnostic capabilities and deepen our understanding of structure–function relationships across multiple scales.