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Ebtisam A Aldaais
Imam Abdulrahamn Bin Faisal University, Saudi Arabia
Scientific Tracks Abstracts: J Clin Trials
In nano-medicine, designing therapeutic nanoparticles has undergone an enormous development in the last few decades. These therapeutic designs focus on developing several features to illuminate inflammations, protect the drug, and enhance the targeted delivery. While the choice of materials affects the efficiency of the design, pondering the intermolecular interactions in a system that is composed of a nanoparticle and cell at a biological environment is vital to stabilize the design and improve targeting. Such a system is usually subject to steric, Van der Waals, and electrostatic interaction, and in the case of magnetic nanoparticles, to electromagnetic interactions. Thus, developing a theory that can predict and/or interpret the nanoparticle behavior at altered biological and design parameters is sufficient. The biological parameters include temperature, salt concentration, pH, and an external electromagnetic field, while the choice of polymers, their functional groups, and density are considered as design parameters. The theory defines the molecular reorganization that can form microgel or micelle, prevent drug leakage, extend mono or dual-ligands toward the targeted cell. Using the theory to stimulate the system and predict the molecular reorganization and correspondingly the nanoparticles behavior should illuminate material and time loss. Then, combining the theory with several experimental data can lead to a new machine learning technique to post the arena of designing smart therapeutic nanoparticles.