Conventional administration of drugs is limited by poor water solubility, low permeability, and mediocre targeting. Safe and effective delivery of drugs and therapeutic agents remains a challenge, especially for complex therapies, such as cancer treatment, pain management, heart failure medication, among several others. Thus, delivery systems designed to improve the pharmacokinetics of loaded molecules, and allowing controlled release and target specific delivery, have received considerable attention in recent years. The last two decades have seen a growing interest among scientists and the pharmaceutical industry in mesoporous silica nanoparticles (MSNs) as drug delivery systems (DDS). This interest is due to the unique physicochemical properties, including high loading capacity, excellent biocompatibility, and easy functionalization. In this review, we discuss the current state of the art related to the preparation of drug-loaded MSNs and their analysis, focusing on the newest advancements, and highlighting the advantages and disadvantages of different methods. Finally, we provide a concise outlook for the remaining challenges in the field.

A complementary approach that combines NMR measurements, analysis of X-ray and neutron powder diffraction data and advanced quantum mechanical calculations was employed to study the α-polymorph of L-polylactide. Such a strategy, which is known as NMR crystallography, to the best of our knowledge, is used here for the first time for the fine refinement of the crystal structure of a synthetic polymer. The GIPAW method was used to compute the NMR shielding parameters for the different models, which included the α-PLLA structure obtained by 2-dimensional wide-angle X-ray diffraction (WAXD) at −150 °C (model M1) and at 25 °C (model M2), neutron diffraction (WAND) measurements (model M3) and the fully optimized geometry of the PLLA chains in the unit cell with defined size (model M4). The influence of changes in the chain conformation on the ¹³C σ_ii NMR shielding parameters is shown. The correlation between the σ_ii and δ_ii values for the M1–M4 models revealed that the M4 model provided the best fit. Moreover, a comparison of the experimental ¹³C NMR spectra with the spectra calculated using the M1–M4 models strongly supports the data for the M4 model. The GIPAW method, via verification using NMR measurements, was shown to be capable of the fine refinement of the crystal structures of polymers when coarse X-ray diffraction data for powdered samples are available.