Effect of Copolymer Properties on the Phase Behavior of Ibuprofen-PLA/PLGA Mixtures

COSMOPharm: Drug-Polymer Compatibility of Pharmaceutical Amorphous Solid Dispersions from COSMO-SAC

The quantum mechanics-aided COSMO-SAC activity coefficient model is applied and systematically examined for predicting the thermodynamic compatibility of drugs and polymers. The drug-polymer compatibility is a key aspect in the rational selection of optimal polymeric carriers for pharmaceutical amorphous solid dispersions (ASD) that enhance drug bioavailability. The drug-polymer compatibility is evaluated in terms of both solubility and miscibility, calculated using standard thermodynamic equilibrium relations based on the activity coefficients predicted by COSMO-SAC. As inherent to COSMO-SAC, our approach relies only on quantum-mechanically derived σ-profiles of the considered molecular species and involves no parameter fitting to experimental data. All σ-profiles used were determined in this work, with those of the polymers being derived from their shorter oligomers by replicating the properties of their central monomer unit(s). Quantitatively, COSMO-SAC achieved an overall average absolute deviation of 13% in weight fraction drug solubility predictions compared to experimental data. Qualitatively, COSMO-SAC correctly categorized different polymer types in terms of their compatibility with drugs and provided meaningful estimations of the amorphous-amorphous phase separation. Furthermore, we analyzed the sensitivity of the COSMO-SAC results for ASD to different model configurations and σ-profiles of polymers. In general, while the free volume and dispersion terms exerted a limited effect on predictions, the structures of oligomers used to produce σ-profiles of polymers appeared to be more important, especially in the case of strongly interacting polymers. Explanations for these observations are provided. COSMO-SAC proved to be an efficient method for compatibility prediction and polymer screening in ASD, particularly in terms of its performance-cost ratio, as it relies only on first-principles calculations for the considered molecular species. The open-source nature of both COSMO-SAC and the Python-based tool COSMOPharm, developed in this work for predicting the API-polymer thermodynamic compatibility, invites interested readers to explore and utilize this method for further research or assistance in the design of pharmaceutical formulations.

Towards rational design of API-poly(D, L-lactide-co-glycolide) based micro- and nanoparticles: The role of API-polymer compatibility prediction

Due to their unique properties, such as controlled drug release and improved bioavailability, polymeric microparticles and nanoparticles (MPs and NPs) have gained considerable interest in the pharmaceutical industry. Nevertheless, the high costs associated with biodegradable polymers and the active pharmaceutical ingredients (APIs) used for treating serious diseases, coupled with the vast number of API-polymer combinations, make the search for effective API-polymer MPs and NPs a costly and time-consuming process. In this work, the correlation between the compatibility of selected model APIs (i.e., ibuprofen, naproxen, paracetamol, and indomethacin) with poly(lactide-co-glycolide) (PLGA) derived from respective binary phase diagrams and characteristics of prepared MPs and NPs, such as the drug loading and solid-state properties, was investigated to probe the possibility of implementing the modeling of API-polymer thermodynamic and kinetic phase behavior as part of rational design of drug delivery systems based on MPs and NPs. API-PLGA-based MPs and NPs were formulated using an emulsion-solvent evaporation technique and were characterized for morphology, mean size, zeta potential, drug loading, and encapsulation efficiency. The solid-state properties of the encapsulated APIs were assessed using differential scanning calorimetry and X-ray powder diffraction. The evaluated compatibility was poor for all considered API-PLGA pairs, which is in alignment with the experimental results showing low drug loading in terms of amorphous API content. At the same time, drug loading of the studied APIs in terms of amorphous content was found to follow the same trend as their solubility in PLGA, indicating a clear correlation between API solubility in PLGA and achievable drug loading. These findings suggest that API-polymer phase behavior modeling and compatibility screening can be employed as an effective preformulation tool to estimate optimum initial API concentration for MP and NP preparation or, from a broader perspective, to tune or select polymeric carriers offering desired drug loading.

Amorphous solid dispersions: Stability mechanism, design strategy and key production technique of hot melt extrusion

Solid dispersion (SD) system has been used as an effective formulation strategy to increase in vitro and in vivo performances of poorly water-soluble drugs, such as solubility/dissolution, stability and bioavailability. This review provides a comprehensive SD classification and identifies the most popular amorphous solid dispersions (ASDs). Meanwhile, this review further puts forward the systematic design strategy of satisfactory ASDs in terms of drug properties, carrier selection, preparation methods and stabilization mechanisms. In addition, hot melt extrusion (HME) as the continuous manufacturing technique is described including the principle and structure of HME instrument, key process parameters and production application, in order to guide the scale-up of ASDs and develop more ASD products to the market in pharmaceutical industry.

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug-Polymer Compatibility Screening?

The bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs) can be improved via the formulation of an amorphous solid dispersion (ASD), where the API is incorporated into a suitable polymeric carrier. Optimal carriers that exhibit good compatibility (i.e., solubility and miscibility) with given APIs are typically identified through experimental means, which are routinely labor- and cost-inefficient. Therefore, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state, a popular thermodynamic model in pharmaceutical applications, is examined in terms of its performance regarding the computational pure prediction of API-polymer compatibility based on activity coefficients (API fusion properties were taken from experiments) without any binary interaction parameters fitted to API-polymer experimental data (that is, kij = 0 in all cases). This kind of prediction does not need any experimental binary information and has been underreported in the literature so far, as the routine modeling strategy used in the majority of the existing PC-SAFT applications to ASDs comprised the use of nonzero kij values. The predictive performance of PC-SAFT was systematically and thoroughly evaluated against reliable experimental data for almost 40 API-polymer combinations. We also examined the effect of different sets of PC-SAFT parameters for APIs on compatibility predictions. Quantitatively, the total average error calculated over all systems was approximately 50% in the weight fraction solubility of APIs in polymers, regardless of the specific API parametrization. The magnitude of the error for individual systems was found to vary significantly from one system to another. Interestingly, the poorest results were obtained for systems with self-associating polymers such as poly(vinyl alcohol). Such polymers can form intramolecular hydrogen bonds, which are not accounted for in the PC-SAFT variant routinely applied to ASDs (i.e., that used in this work). However, the qualitative ranking of polymers with respect to their compatibility with a given API was reasonably predicted in many cases. It was also predicted correctly that some polymers always have better compatibility with the APIs than others. Finally, possible future routes to improve the cost-performance ratio of PC-SAFT in terms of parametrization are discussed.