## 4 Bionanosystems
### Bionanosystems for RA
#### 4.1.1. Bionanosystems Based on Organic Carriers
ULs prepared by using 0.69% _w/v_ of Phospholipon 90G, 0.078% _w/v_ of cholesterol, 2% _w/v_ of Tween 20 (non-ionic surfactant), 0.5% _w/v_ of oleic acid and water had particle size of 60 \(\pm\) 17.3 nm, polydispersity of 0.32 \(\pm\) 0.1 and zeta potential of -18.03 \(\pm\) 0.35 mV. The confocal laser scanning microscopy, where the co-localization technique using multifluorescent labelled particles was utilized, showed that ULs attached to any part of the skin before releasing the entrapped drug to further penetrate the skin [120]. Solid lipid nanoparticles (SLNs), made of lipids that remain solid at both the temperature of the human body and at room temperature, are another way to encapsulate RA. The composition of these nanoparticles, along with their characteristics, makes the SLNs ideal for carrying/delivering sensitive bioactive compounds. SLNs protect these compounds against chemical degradation and facilitate their application in varied administration routes [121]. RA was successfully encapsulated in SLNs made of witepsol (mixture of mono-, di- and triglycerides from natural origin) and carnauba wax. About 40-60% of RA encapsulated in SLNs was released in simulated gastrointestinal tract conditions, and its antioxidant activity was maintained [122]. Another application of RA-loaded SNLs is in the therapeutic approach for neurodegenerative disorders. Indeed, RA, besides having anti-inflammatory and antioxidant activities, also has a neuroprotective effect. In the therapy of neurodegenerative disorders, solid lipid nanoparticles were used for the nasal administration because this is an efficient root for the delivery of active principle to the central nervous system [123]. For the management of [PERSON]'s disease, a neurodegenerative disease, the RA-loaded SLNs was prepared using glycerol monostearate as lipid, tween 80 and soya lecithin as surfactant and hydrogenated soya phosphatidyl choline as a stabilizer. Optimized RA-loaded SLNs have the mean size of 149.2 \(\pm\) 3.2 nm, zeta potential of \(-\)38.27 mV and entrapment efficiency of 61.9 \(\pm\) 2.2%. Nasal delivery of the developed formulation shows that RA-loaded SLNs formulation following the non-invasive nose-to-brain drug delivery is a promising therapeutic approach for the effective management in [PERSON] disease [124]. Another lipid system used to entrap plant extracts containing RA is the nanostructured lipid carrier (NLC), which has been developed and used as an alternative carrier system to liposomes, emulsions, and solid lipid nanoparticles. Compared to SLNs, NLCs have a higher loading capacity of active ingredients because the liquid lipid in the formulation caused imperfect structures with low crystallization ability than SLNs. Moreover, the firmer inclusion of the active ingredients inside the particle matrix leads to better stability and longer shelf life of entrapped extract [121]. _Ocimum sanctum_ extract containing a high amount of RA was successfully loaded in a NLC made of 5% _w/w_ of cetyl palmitate, 3% _w/w_ of tea seed oil, 2.5% _w/w_ of Plantacare 2000\({}^{\text{\textregistered}}\) (non-ionic surfactant), and 91.5% _w/w_ of distilled water. The NLC has an internal droplet size of 261.0 \(\pm\) 5.3 nm, polydispersity index of 0.216 \(\pm\) 0.042, and Zeta potential of \(-\)45.4 \(\pm\) 2.4 mV. The loaded-RA NLC dissolved in propylene glycol showed a continuous release of RA during 24 h; about 27% of the extract was detected into the skin layers, and no irritation was detected by Hen's Egg Test on the Chrioallantoic Membrane (HET-CAM) [125]. Finally, nanoemulsions containing RA have been developed and tested for different applications. For example, they were used for a new nasally delivered neuroprotective therapy. Here, the association of lipid nanotechnology-based delivery systems with a mucoadhesive biopolymer such as CS improves RA penetration through biological barriers and increases its residence time in the nasal cavity [126].