Pharmacometric analysis is often used to quantify the differences and similarities between formulation prototypes. In the regulatory framework, it plays a significant role in the evaluation of bioequivalence. While non-compartmental analysis provides an unbiased data evaluation, mechanistic compartmental models such as the physiologically-based nanocarrier biopharmaceutics model promise improved sensitivity and resolution for the underlying causes of inequivalence. In the present investigation, both techniques were applied to two nanomaterial-based formulations for intravenous injection, namely, albumin-stabilized rifabutin nanoparticles and rifabutin-loaded PLGA nanoparticles. The antibiotic rifabutin holds great potential for the treatment of severe and acute infections of patients co-infected with human immunodeficiency virus and tuberculosis. The formulations differ significantly in their formulation and material attributes, resulting in an altered biodistribution pattern as confirmed in a biodistribution study in rats. The albumin-stabilized delivery system further undergoes a dose-dependent change in particle size which leads to a small yet significant change in the in vivo performance. A second analysis was conducted comparing the dose fraction-scaled pharmacokinetic profiles of three dose levels of albumin-stabilized rifabutin nanoparticles. The dose strength affects both the nanomaterial-related absorption and biodistribution of the carrier as well as the drug-related distribution and elimination parameters, increasing the background noise and difficulty of detecting inequivalence. Depending on the pharmacokinetic parameter (e.g., AUC, C_max, Cl_obs), the relative (percentage) difference from the average observed using non-compartmental modeling ranged from 85% to 5.2%. A change in the formulation type (PLGA nanoparticles vs. albumin-stabilized rifabutin nanoparticles) resulted in a similar level of inequivalence as compared to a change in the dose strength. A mechanistic compartmental analysis using the physiologically-based nanocarrier biopharmaceutics model led to an average difference of 152.46% between the two formulation prototypes. Albumin-stabilized rifabutin nanoparticles tested at different dose levels led to a 128.30% difference, potentially due to changes in particle size. A comparison of different dose strengths of PLGA nanoparticles, on average, led to a 3.87% difference. This study impressively illustrates the superior sensitivity of mechanistic compartmental analysis when dealing with nanomedicines.

It has been shown via the example of three types of polyacrylamide hydrogels synthesized through the usual radical copolymerization of acrylamide and N,N′-methylene-bisacrylamide, the copolymerization of these monomers in the presence of a chain-transfer agent, and the pseudoliving copolymerization in the presence of a reversible-chain-transfer agent that one of the factors determining the microstructure of crosslinked polymer systems is the molecular-mass distribution of the copolymer forming at the initial step of the process. The closer the M _w/M _n ratio of the copolymer is to unity, the lower the contribution of larger pores in the total number of hydrogel pores.

The objective of this study was to compare the properties of core–shell nanoparticles with a PLGA core and shells composed of different types of polymers, focusing on their structural integrity. The core PLGA nanoparticles were prepared either through a high-pressure homogenization–solvent evaporation technique or nanoprecipitation, using poloxamer 188 (P188), a copolymer of divinyl ether with maleic anhydride (DIVEMA), and human serum albumin (HSA) as the shell-forming polymers. The shells were formed through adsorption, interfacial embedding, or conjugation. For dual fluorescent labeling, the core- and shell-forming polymers were conjugated with Cyanine5, Cyanine3, and rhodamine B. The nanoparticles had negative zeta potentials and sizes ranging from 100 to 250 nm (measured using DLS) depending on the shell structure and preparation technique. The core–shell structure was confirmed using TEM and fluorescence spectroscopy, with the appearance of FRET phenomena due to the donor–acceptor properties of the labels. All of the shells enhanced the cellular uptake of the nanoparticles in Gl261 murine glioma cells. The integrity of the core–shell structures upon their incubation with the cells was evidenced by intracellular colocalization of the fluorescent labels according to the Manders’ colocalization coefficients. This comprehensive approach may be useful for the selection of the optimal preparation method even at the early stages of the core–shell nanoparticle development.

Development of in situ forming implants (ISFI) based on PLGA polymers is one of the most promising approaches to long-acting injectables. Evaluation of the drug release rate from such depot formulations requires methods that most closely simulate in vivo conditions. Gel phantoms mimic the elastic properties of muscle tissue and appear to be a promising replacement for conventional methods using physiologically relevant buffer solutions. Accordingly, the aim of the study was to select the optimal composition for the gel phantom formation and evaluate the effect of the phantom matrix on the release rate of rilpivirin used as a model drug from the PLGA ISFI. According to the results of the study, a 1% agarose gel was the best suited for a tissue phantom preparation and implant formation. It was also shown that the release profile of rilpivirin from the ISFI matrix depended on how the implant was formed (in a gel or freely in buffer). In the case of a phantom, the structure of the implant was less porous and retained its shape for 28 days of incubation at 37 °C. During this period, the ISFI formed in an agarose gel released considerably less rilpivirin compared to the ISFI formed without gel (11% vs 80%).