Optimizing Lipid Nanoparticles: advanced carriers for active compounds and enhancers for sensing technologies

Lipidic delivery systems have emerged as enhancers of drug solubility and bioavailability as they offer advantages such as site-specific action and prolonged drug release. Due to their ability to structure and facilitate the administration of active compounds in pharmaceuticals, foods, and personal care products, the development of lipid-based systems has garnered significant interest. Over time, various lipidic nanostructures have been developed based on the intrinsic chemical properties of lipid molecules, however, traditional synthetic approaches to produce dispersed systems with appropriate dimensions, good encapsulation efficiency and low polydispersity often face scalability challenges. To address this issue, it is essential to incorporate studies on these nanosystems' physical and chemical properties into the design and synthetical process. As a result, Quality by Design approach is widely used, enabling precise control over the key characteristics of dispersed lipidic nanostructures by systematical analysis and optimization of the variables that are influencing their final properties. Beyond drug delivery, some lipidic nanostructures could serve as signal enhancers for piezoelectric biosensors, to both improve the limit of detection of crucial compounds and demonstrate how surface roughness and increased surface area are key factors in the development of specific and reliable mass-sensitive devices. In this work, an investigation of solid lipid nanoparticles as carriers of different drugs, their optimization, functionalization with polymers, and their applications as detecting elements for QCM sensors is proposed. Chronic kidney disease is a condition characterized by a gradual loss of kidney function over time, and the cost of dialysis therapies remains prohibitive for many, especially in low-income countries where healthcare resources are scarce. In such settings, the life expectancy of treated patients is still increased, but the effort to sustain hemodialysis therapy and the prohibitive nature of the conditions negatively influence the mental health and lifestyle of patients. There have been many efforts to innovate and improve dialysis, with a focus on developing less invasive techniques and portable devices that can purify dialysates from contaminants withdrawn from bloodstream. Here is also presented a Raman-based Partial Least Squares regression model that allows urea quantification without any further derivatization in spent and recycled dialysates.