The majority of all newly identified active pharmaceutical ingredients (APIs) have a low solubility in water (partly smaller than marble). In order to enhance their solubility and bioavailability, the formulation of these APIs, as part of therapeutic deep eutectic systems (THEDES), has been recently shown to be a promising approach. By choosing the right excipient, the melting point of the API/excipient mixture can be lowered below body temperature or even room temperature, resulting in a liquid formulation. To date, because of a lack of mechanistic understanding of how THEDES are formed, the identification of suitable excipients for a given API is almost exclusively based on heuristic decisions and trial-and-error-based approaches. This is both very time-consuming and expensive. The purpose of this work is to reduce the experimental effort to identify suitable excipients for a given API solely based on the melting properties (melting temperature and melting enthalpy) of the API and excipient and accounting for intermolecular interactions via a predictive thermodynamic model [in this case, UNIFAC(Do)]. Lidocaine, ibuprofen, and phenylacetic acid were considered as model APIs, whereas thymol, vanillin, lauric acid, para-toluic acid, benzoic acid, and cinnamic acid were considered as model excipients. The formation of THEDES from these components was predicted and confirmed using differential scanning calorimetry. The results indicate that the experimental effort for the identification of suitable API/excipient combinations can be drastically reduced by thermodynamic modeling, leading to more efficient and tailor-made formulations in the future.
In formulation development, amorphous solid dispersions (ASD) are considered to improve the bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs). However, the crystallization of APIs often limits long-term stability and thus the shelf life of ASDs. It has already been shown earlier that the long-term stability of ASDs strongly depends on the storage conditions (relative humidity, temperature), the manufacturing methods, and the resulting particle sizes. In this work, ASDs composed of the model APIs Griseofulvin (GRI) or Itraconazole (ITR) and the polymers poly (vinylpyrrolidone-co-vinyl acetate) (PVPVA) or Soluplus® were manufactured via spray drying and hot-melt extrusion. Each API/polymer combination was manufactured using the two manufacturing methods with at least two different API loads and two particle-size distributions. It was a priori known that these ASDs were metastable and would crystallize over time, even in the dry stage. The amount of water absorbed by the ASD from humid air (40 °C/75% relative humidity), the solubility of the API in the ASD at humid conditions, and the resulting glass-transition temperature were predicted using the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) and the Gordon–Taylor approach, respectively. The onset of crystallization was determined via periodic powder X-ray diffraction (PXRD) measurements. It was shown that simple heuristics such as “larger particles always crystallize later than smaller particles” are correct within one manufacturing method but cannot be transferred from one manufacturing method to another. Moreover, amorphous phase separation in the ASDs was shown to also influence their crystallization kinetics. Counterintuitively, phase separation accelerated the crystallization time, which could be explained by the glass-transition temperatures of the evolving phases.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.