Serrano-Mora LE, Zambrano-Zaragoza ML, Mendoza-Muñoz N, Leyva-Gómez G, Urbán-Morlán Z, Quintanar-Guerrero D. Preparation of Co-Processed Excipients for Controlled-Release of Drugs Assembled with Solid Lipid Nanoparticles and Direct Compression Materials.
Molecules 2021;
26:2093. [PMID:
33917445 PMCID:
PMC8038754 DOI:
10.3390/molecules26072093]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 03/24/2021] [Accepted: 03/30/2021] [Indexed: 11/16/2022] Open
Abstract
The purpose of the study was to develop a novel, directly compressible, co-processed excipient capable of providing a controlled-release drug system for the pharmaceutical industry. A co-processed powder was formed by adsorption of solid lipid nanoparticles (SLN) as a controlled-release film onto a functional excipient, in this case, dicalcium phosphate dihydrate (DPD), for direct compression (Di-Tab®). The co-processed excipient has advantages: easy to implement; solvent-free; industrial scaling-up; good rheological and compressibility properties; and the capability to form an inert platform. Six different batches of Di-Tab®:SLN weight ratios were prepared (4:0.6, 3:0.6, 2:0.6, 1:0.6, 0.5:0.6, and 0.25:0.6). BCS class III ranitidine hydrochloride was selected as a drug model to evaluate the mixture's controlled-release capabilities. The co-processed excipients were characterized in terms of powder rheology and dissolution rate. The best Di-Tab®:SLN ratio proved to be 2:0.6, as it showed high functionality with good flow and compressibility properties (Carr Index = 16 ± 1, Hausner Index = 1.19 ± 0.04). This ratio could control release for up to 8 h, so it fits the ideal profile calculated based on biopharmaceutical data. The compressed systems obtained using this powder mixture behave as a matrix platform in which Fickian diffusion governs the release. The Higuchi model can explain their behavior.
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