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Nanostructured lipid carriers (NLC) are biocompatible and biodegradable nanoscale systems with extensive application for controlled drug release. However, the development of optimal nanosystems along with a reproducible manufacturing process is still challenging. In this study, a two-step experimental design was performed and databases were successfully modelled using Artificial Intelligence techniques as an innovative method to get optimal, reproducible and stable NLC. The initial approach, including a wide range of values for the different variables, was followed by a second set of experiments with variable values in a narrower range, more suited to the characteristics of the system. NLC loaded with rifabutin, a hydrophobic drug model, were produced by hot homogenization and fully characterized in terms of particle size, size distribution, zeta potential, encapsulation efficiency and drug loading. The use of Artificial Intelligence tools has allowed to elucidate the key parameters that modulate each formulation property. Stable nanoparticles with low sizes and polydispersions, negative zeta potentials and high drug loadings were obtained when the proportion of lipid components, drug, surfactants and stirring speed were optimized by FormRules ® and INForm ® . The successful application of Artificial Intelligence tools on NLC formulation optimization constitutes a pioneer approach in the field of lipid nanoparticles., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Lyophilization is often employed to transform nanoparticle suspensions to stable solid forms. This work proposed Neurofuzzy Logic (NFL) to better understand the lyophilization process of Nanostructured Lipid Carriers' (NLCs) dispersions and the carbohydrate cryoprotectants' (CPs) performance in these processes. NLCs were produced by hot homogenization, frozen at different speeds, and lyophilized using several CPs at variable concentrations. NLCs were characterized, and results were expressed as increase in particle size (Δ size), polydispersity (Δ PdI), and zeta potential (Δ ZP) of lyophilized powders (LP) regarding initial dispersions. CPs were classified according to their molecular weights (MW), and the osmolarities (Π) of CPs solutions were also determined. Databases obtained were finally modelled through FormRules® (Intelligensys Ltd., Kirkwall, Scotland, UK), an NFL software. NFL models revealed that CPs' MW determines the optimal freezing conditions and CPs' proportions. The knowledge generated allowed the establishment of a traffic light system intended to successfully select and apply sugars for nanoparticles lyophilization. [ABSTRACT FROM AUTHOR]

Oral anti-mycobacterial treatment of Crohn's disease (CD) is limited by the low aqueous solubility of drugs, along with the altered gut conditions of patients, making uncommon their clinical use. Hence, the aim of the present work is focused on the in vitro evaluation of rifabutin (RFB)-loaded Nanostructured lipid carriers (NLC), in order to solve limitations associated to this therapeutic approach. RFB-loaded NLC were prepared by hot homogenization and characterized in terms of size, polydispersity, surface charge, morphology, thermal stability, and drug payload and release. Permeability across Caco-2 cell monolayers and cytotoxicity and uptake in human macrophages was also determined. NLC obtained were nano-sized, monodisperse, negatively charged, and spheroidal-shaped, showing a suitable drug payload and thermal stability. Furthermore, the permeability profile, macrophage uptake and selective intracellular release of RFB-loaded NLC, guarantee an effective drug dose administration to cells. Outcomes suggest that rifabutin-loaded NLC constitute a promising strategy to improve oral anti-mycobacterial therapy in Crohn's disease. [ABSTRACT FROM AUTHOR]