Jean-Christophe Gimel

Fate of paclitaxel lipid nanocapsules in intestinal mucus in view of their oral delivery.

The bioavailability of paclitaxel (Ptx) has previously been improved via its encapsulation in lipid nanocapsules (LNCs). In this work, the interactions between LNCs and intestinal mucus are studied because they are viewed as an important barrier to successful oral delivery. The rheological properties of different batches of pig intestinal mucus were studied under different conditions (the effect of hydration and the presence of LNCs). Fluorescence resonance energy transfer (FRET) was used to study the stability of LNCs in mucus at 37°C for at least 3 hours. Diffusion through 223, 446, and 893 μm mucus layers of 8.4, 16.8, and 42 μg/mL Ptx formulated as Taxol® (Bristol-Myers Squibb, Rueil-Malmaison, France) or encapsulated in LNCs (Ptx-LNCs) were investigated. The effect of the size of the LNCs on their diffusion was also investigated (range, 25–110 nm in diameter). Mucus behaves as a non-Newtonian gel with rheofluidifying properties and a flow threshold. The viscous (G″) and elastic (G′) moduli and flow threshold of the two mucus batches varied with water content, but G′ remained below G″. LNCs had no effect on mucus viscosity and flow threshold. The FRET efficiency remained at 78% after 3 hours. Because the destruction of the LNCs would lead to a FRET efficiency below 25%, these results suggest only a slight modification of LNCs after their contact with mucus. The diffusion of Taxol® and Ptx-LNCs in mucus decreases if the mucus layer is thicker. Interestingly, the apparent permeability across mucus is higher for Ptx-LNCs than for Taxol® for drug concentrations of 16.8 and 42 μg/mL Ptx (P<0.05). The diffusion of Ptx-LNCs through mucus is not size-dependent. This study shows that LNCs are stable in mucus, do not change mucus rheological properties, and improve Ptx diffusion at low concentrations, thus making these systems good candidates for Ptx oral delivery. The study of the physicochemical interaction between the LNC surface and its diffusion in mucus is now envisioned.

How to design the surface of peptide-loaded nanoparticles for efficient oral bioavailability? ☆

The oral administration of proteins is a current challenge to be faced in the field of therapeutics. There is currently much interest in nanocarriers since they can enhance oral bioavailability. For lack of a clear definition, the key characteristics of nanoparticles have been highlighted. Specific surface area is one of these characteristics and represents a huge source of energy that can be used to control the biological fate of the carrier. The review discusses nanocarrier stability, mucus interaction and absorption through the intestinal epithelium. The protein corona, which has raised interest over the last decade, is also discussed. The universal ideal surface is a myth and over-coated carriers are not a solution either. Besides, common excipients can be useful on several targets. The suitable design should rather take into account the composition, structure and behavior of unmodified nanomaterials.

Nanoscale texture development of C-S-H gel: A computational model for nucleation and growth

The development of C-S-H (Calcium-Silicate-Hydrate) gels during cement hydration is often investigated by nucleation and growth models which fit reasonably well with the calorimetric measurements but predict hydration degrees which grossly exceed the experimental values. Here, a computational model is presented which explicitly considers the intrinsic nanoparticulate nature of C-S-H gel. Based on a nucleation and growth algorithm the model reproduces the experimental calorimetric and hydration degree measurements without invoking to any diffusion mechanism. The model also suggests that the peak in the calorimetric curves can be ascribed to the percolation point of the hydrates themselves within the interstitial pore volume.

Lipid nanocapsules maintain full integrity after crossing a human intestinal epithelium model

&NA; Lipid nanocapsules (LNCs) have demonstrated great potential for the oral delivery of drugs having very limited oral bioavailability (BCS class II, III and IV molecules). It has been shown previously that orally‐administered LNCs can permeate through mucus, increase drug absorption by the epithelial tissue, and finally, increase drug bioavailability. However, even if transport mechanisms through mucus and the intestinal barrier have already been clarified, the preservation of particle integrity is still not known. The aim of the present work is to study in vitro the fate of LNCs after their transportation across an intestinal epithelium model (Caco‐2 cell model). For this, two complementary techniques were employed: Förster Resonance Energy Transfer (FRET) and Nanoparticle Tracking Analysis (NTA). Results showed, after 2 h, the presence of nanoparticles in the basolateral side of the cell layer and a measurable FRET signal. This provides very good evidence for the transcellular intact crossing of the nanocarriers. &NA; Graphical abstract Figure. No caption available.

Spontaneous nano-emulsification: Process optimization and modeling for the prediction of the nanoemulsion’s size and polydispersity

The aim of the present study was to optimize the size and polydispersity of a lipid nanoemulsion as a function of the oil (Labrafac® WL1349), surfactant (Kolliphor® HS 15) and cosurfactant (Span® 80) phase composition and temperature. The nanoemulsions were prepared using a low-energy self-emulsification method. The Z-average diameter and the polydispersity index (PDI) were modeled with mixture experiments. Nanoemulsions from 20nm to 120nm with PDI<0.2 were obtained at the three different tested temperatures (30°C, 50°C and 90°C). The nanoemulsion size was able to be controlled with the oil, surfactant and cosurfactant concentrations. Interestingly, the smallest PDIs were obtained at 30°C, and the cosurfactant concentration was able to be adjusted to optimize the formulation and to obtain nanoemulsions in the 20-120nm range with a PDI smaller than 0.14. These nanoemulsions have shown a good stability at 4°C in storage conditions and at 37°C in diluted conditions.

Effect of Nano Seeds in C-S-H Gel Formation: Simulation Study from the Colloidal Point of View

The addition of external nanoparticles, mainly nano silica during the hydration of cement is a field of investigation in high performance cements. The added particles act as seeds and initiate early nucleation and subsequent growth of C-S-H gel. Nucleation is triggered very early, before enough clinker grains are dissolved or in other words, before the super saturation condition is attained. Hence, depending on the amount of added seed, the morphology and the mechanical properties of the product differ. Experimental studies in this area are less favored due to economic reasons and simulation studies are rare in the literature. An earlier work by some of the authors introduced a Monte Carlo model which dealt with the kinetics of the hydration process at early ages. The colloidal model incorporated random nucleation in the bulk, followed by an Avramian style layer by layer growth of 5nm sized C-S-H particles. The model was based on a Random Sequential Addition scheme and enabled a satisfactory rationalization of the early growth of C-S-H gel. In the present study, the authors extend this model for the addition of extra seeds and for different water to cement ratios.

A multi-scale approach for percolation transition and its application to cement setting

Shortly after mixing cement grains with water, a cementitious fluid paste is formed that immediately transforms into a solid form by a phenomenon known as setting. Setting actually corresponds to the percolation of emergent network structures consisting of dissolving cement grains glued together by nanoscale hydration products, mainly calcium-silicate-hydrates. As happens in many percolation phenomena problems, the theoretical identification of the percolation threshold (i.e. the cement setting) is still challenging, since the length scale where percolation becomes apparent (typically the length of the cement grains, microns) is many times larger than the nanoscale hydrates forming the growing spanning network. Up to now, the long-lasting gap of knowledge on the establishment of a seamless handshake between both scales has been an unsurmountable obstacle for the development of a predictive theory of setting. Herein we present a true multi-scale model which concurrently provides information at the scale of cement grains (microns) and at the scale of the nano-hydrates that emerge during cement hydration. A key feature of the model is the recognition of cement setting as an off-lattice bond percolation process between cement grains. Inasmuch as this is so, the macroscopic probability of forming bonds between cement grains can be statistically analysed in smaller local observation windows containing fewer cement grains, where the nucleation and growth of the nano-hydrates can be explicitly described using a kinetic Monte Carlo Nucleation and Growth model. The most striking result of the model is the finding that only a few links (~12%) between cement grains are needed to reach setting. This directly unveils the importance of explicitly including nano-texture on the description of setting and explains why so low amount of nano-hydrates is needed for forming a spanning network. From the simulations, it becomes evident that this low amount is least affected by processing variables like the water-to-cement ratio and the presence of large quantities of nonreactive fillers. These counter-intuitive predictions were verified by ex-professo experiments that we have carried out to check the validity of our model.

NMR diffusometry data sampling optimization for mixture analysis

HighlightsOptimization of acquisition parameters for NMR diffusometry mixture analysis.Optimal signal decay sampling prediction tool adapted to mixture composition.Validation on unimer/micelle or liposomal drug mixtures. ABSTRACT NMR diffusometry is a powerful but challenging method to analyze complex mixture. Each component diffuses differently, from the faster small species to the slower large species, corresponding to different signal attenuation. However, the method is highly sensitive to the quality of the acquired data and the performance of the processing used to resolve multiexponential signals influences. Adapting the signal decay sampling to the mixture composition is one way to improve the precision of the measure. In this work, we propose a prediction tool, based on the calculation of the Cramér‐Rao lower bound to minimize the variance of diffusion coefficient estimation in order to determine the optimal number of diffusion gradient steps, the best diffusion gradient sampling (among linear, exponential, quadratic and sigmoidal ones) and the optimal maximum diffusion factor. The tool was validated experimentally on a unimer/micelle solution of sodium dodecyl sulfate and on Caelyx®, a commercial liposomal preparation containing a mixture of pegylated‐liposomes and sucrose.