β-caryophyllene cationic nanoemulsion for intranasal delivery and treatment of epilepsy: development and in vivo evaluation of anticonvulsant activity
Source abstract
Abstract
Intranasal delivery systems have been proposed as alternative routes for drug delivery to the brain, primarily for treating diseases that affect the central nervous system. β-Caryophyllene (BCP) is a naturally occurring agonist of CB2 cannabinoid receptors and has anticonvulsant potential but limited oral bioavailability. Thus, considering that developing a cationic nanoemulsion containing BCP (BCP-NE) may be useful in intranasal (i.n.) delivery, this study aimed to develop and characterise BCP-NE and its putative anticonvulsant effect via the i.n. route in rats using the pentylenetetrazole (PTZ)-induced seizure model. BCP-NE was prepared by spontaneous emulsification. The oil phase consisted of BCP (40 mg mL−1), lecithin (20 mg), oleylamine (0.5 mM) and an aqueous phase of water and glycerin. Physicochemical and morphological characterisation and the content and encapsulation efficiency of BCP were determined in the BCP-NE. Physical stability was evaluated at room temperature, refrigeration and oven. The anticonvulsant potential of BCP-NE was evaluated in vivo. The BCP-NE showed a droplet size of 244.03 ± 15.67 nm with a polydispersity index of 0.18 ± 0.04 and a zeta potential of 41.1 ± 1.57 mV. The BCP trapping efficiency was 98% at a BPC content of 40 mg mL−1. The NE-BCP presented stable conditions evaluated in one month. Importantly, in vivo analysis demonstrated that i.n. administration of BCP-NE delayed the onset of tonic-clonic seizures. Altogether, these results demonstrate that BCP-NE administered via the i.n. pathway has anticonvulsant potential, indicating that the developed system offers favourable intranasal delivery of BCP. Graphical abstract
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Drug Delivery Systems · Drug Solubulity and Delivery Systems · Drug Transport and Resistance Mechanisms
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (55)
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