Selecting Excipients Forming Therapeutic Deep Eutectic Systems-A Mechanistic Approach

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.