Translating photodynamic therapy research into practice with high efficacy should follow characterization and optimization steps in an integrated process. In this way, integration of molecular-based simulations with in vitro and in vivo studies to produce more accurate models with higher prediction precision is inevitable. This study reports on the development a two-phase approach to design and synthesize, and characterize novel hybrid nano-photosensitizers to target breast cancer using molecular docking, microfluidic-based testing and animal studies. In the first phase, using pkCSM artificial intelligence tool and molecular docking, pharmacokinetic weaknesses of photoprotoporphyrin and its retention potential within albumin protein were identified. Biohybrid photosensitive nanoplatform were then synthesized using opto-microfluidics and characterized. In addition, an in-vivo method was used to qualitatively evaluate the opto-biological stability of the final optimized biohybrid nanoplatform. At the second phase, variables of photodynamic treatment were firstly optimized using design of experiment method for the optimized biohybrid photosensitive nanoplatform. Then, on-chip photodynamic studies were carried out in static and dynamic conditions. Results revealed that optimized biohybrid photosensitive nanoplatform as a nano-photosensitizer induced significant death of triple negative human cancer cells in static and dynamic cell cultures under optimized irradiation conditions. Consequently, the presented multiphase study that combined in-silico simulations with microfluidic-based synthesis and characterizations of nano-photosensitizers provided a more convergent model for development of efficacious cancer treatment for photodynamic therapy applications.

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