Solubility Advantage of Amorphous Ketoprofen. Thermodynamic and Kinetic Aspects by Molecular Dynamics and Free Energy Approaches

"Stabilization" of Amorphous Ketoprofen in Thin Films

It has been shown that depositing ketoprofen as thin films on glass substrates has a stabilizing effect on the amorphous state of ketoprofen. Polyethylene glycol (M = 6000 g/mol) was mixed with ketoprofen in a wide range of concentrations. Amorphous thin films were prepared by spin coating and subjected to storage conditions with different levels of relative humidity. The films were characterized by specular X-ray diffraction and atomic force microscopy to assess their stability in dry to wet atmospheres. In a dry atmosphere, the amorphous films remained stable for up to 4 months, although ketoprofen possesses a glass transition temperature of -6 °C. However, when subjected to a humid atmosphere (over 50% relative humidity), ketoprofen tends to crystallize in the amorphous films. At low solution concentrations (i.e., low film thickness and low ketoprofen loading) and high humidity, only nanometer-size crystals could be detected. Increasing the polymer mass ratio may favor or prevent crystallization of ketoprofen in the amorphous films depending on its own crystallization behavior in those films.

Modeling the Structure of Ketoprofen-Poly(vinylpyrrolidone) Amorphous Solid Dispersions with Empirical Potential Structure Refinements of X-ray Scattering Data

The metastability of amorphous formulations poses barriers to their safe and widespread commercialization. The propensity of amorphous solid dispersions (ASDs) to crystallize is directly linked to their molecular structure. Amorphous structures are inherently complex and thus difficult to fully characterize by experiments, which makes structural simulations an attractive route for investigating which structural characteristics correlate with ASD stability. In this study, we use empirical potential structure refinement (EPSR) to create molecular models of ketoprofen-poly(vinylpyrrolidone) (KTP/PVP) ASDs with 0-75 wt % drug loading. The EPSR technique uses X-ray total scattering measurements as constraints, yielding models that are consistent with the X-ray data. We perform several simulations to assess the sensitivity of the EPSR approach to input parameters such as intramolecular bond rotations, PVP molecule length, and PVP tacticity. Even at low drug loading (25 wt %), ∼40% of KTP molecules participate in KTP-KTP hydrogen bonding. The extent of KTP-PVP hydrogen bonding does not decrease significantly at higher drug loadings. However, the models' relative uncertainties are too large to conclude whether ASDs' lower stabilities at high drug loadings are due to changes in drug-excipient hydrogen bonding or a decrease in steric hindrance of KTP molecules. This study illustrates how EPSR, combined with total scattering measurements, can be a powerful tool for investigating structural characteristics in amorphous formulations and developing ASDs with improved stability.

Regularized Bennett and Zwanzig free energy estimators

We consider the problem of free energy estimation from the general perspective of regularization and Bayes estimation theory. We try to take advantage of an assumed a priori knowledge of the free energy. We reformulate the original Bennett acceptance ratio method, in this perspective, devise a numerical algorithm to solve it, and give a closed formula to estimate the confidence in the prior. Finally, we test the derived estimators by applying them to a toy model.

Improved Solubility and Dissolution Rate of Ketoprofen by the Formation of Multicomponent Crystals with Tromethamine

This study aims to improve the dissolution rate of ketoprofen by preparing multicomponent crystals with tromethamine. The multicomponent crystals (equimolar ratio) of ketoprofen and tromethamine were prepared by the solvent co-evaporation method. The solid-state properties of the resulting powder were characterized by powder X-ray diffraction, DSC thermal analysis, FT–IR spectroscopy, solubility, and in vitro dissolution rate. The crystal structure of the multicomponent crystal was determined by single-crystal X-ray diffraction analysis. The results showed that the powder X-ray diffraction pattern of the ketoprofen–tromethamine binary system was different from that of the starting materials. This difference indicates the formation of a new crystalline phase between ketoprofen and tromethamine (equimolar ratio). The DSC thermogram of the ketoprofen–tromethamine binary system exhibited a single and sharp endothermic peak at 128.67 °C, attributed to the melting point of a multicomponent crystal of ketoprofen–tromethamine. A single-crystal X-ray analysis revealed that ketoprofen–tromethamine formed a layered structure, salt-type multicomponent crystal. The solubility and dissolution rate of the multicomponent crystal were notably enhanced compared to the intact ketoprofen. The ketoprofen–tromethamine binary system forms salt-type multicomponent crystals, which can significantly increase the solubility and dissolution rate.

Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy

Computational capabilities are rapidly increasing, primarily because of the availability of GPU-based architectures. This creates unprecedented simulative possibilities for the systematic and robust computation of thermodynamic observables, including the free energy of a drug binding to a target. In contrast to calculations of relative binding free energy, which are nowadays widely exploited for drug discovery, we here push the boundary of computing the binding free energy and the potential of mean force. We introduce a novel protocol that leverages enhanced sampling, machine learning, and ad hoc algorithms to limit human intervention, computing time, and free parameters in free energy calculations. We first validate the method on a host-guest system, and then we apply the protocol to glycogen synthase kinase 3 beta, a protein kinase of pharmacological interest. Overall, we obtain a good correlation with experimental values in relative and absolute terms. While we focus on protein-ligand binding, the strategy is of broad applicability to any complex event that can be described with a path collective variable. We systematically discuss key details that influence the final result. The parameters and simulation settings are available at PLUMED-NEST to allow full reproducibility.