A Mechanistic Model for Predicting the Physical Stability of Amorphous Solid Dispersions

Analysis of stabilization mechanisms in β-lactoglobulin-based amorphous solid dispersions by experimental and computational approaches

Our previous work shows that β-lactoglobulin-stabilized amorphous solid dispersion (ASD) loaded with 70 % indomethacin remains stable for more than 12 months. The stability is probably due to hydrogen bond networks spread throughout the ASD, facilitated by the indomethacin which has both hydrogen donors and acceptors. To investigate the stabilization mechanisms further, here we tested five other drug molecules, including two without any hydrogen bond donors. A combination of experimental techniques (differential scanning calorimetry, X-ray power diffraction) and molecular dynamics simulations was used to find the maximum drug loadings for ASDs with furosemide, griseofulvin, ibuprofen, ketoconazole and rifaximin. This approach revealed the underlying stabilization factors and the capacity of computer simulations to predict ASD stability. We searched the ASD models for crystalline patterns, and analyzed diffusivity of the drug molecules and hydrogen bond formation. ASDs loaded with rifaximin and ketoconazole remained stable for at least 12 months, even at 90 % drug loading, whereas stable drug loadings for furosemide, griseofulvin and ibuprofen were at a maximum of 70, 50 and 40 %, respectively. Steric confinement and hydrogen bonding to the proteins were the most important stabilization mechanisms at low drug loadings (≤ 40 %). Inter-drug hydrogen bond networks (including those with induced donors), ionic interactions, and a high Tg of the drug molecule were additional factors stabilizing the ASDs at drug loading greater than 40 %.

The shelf life of ASDs: 2. Predicting the shelf life at storage conditions

Amorphous solid dispersions (ASDs) are a widely used formulation technology for poorly water-soluble active pharmaceutical ingredients (API). Depending on the API-polymer combination and API load in the ASD, the amorphous API might be thermodynamically metastable and crystallize over time. The crystallization onset is one critical factor that can define the shelf life of the ASD. Thus, for ASD formulations, long-term stability against crystallization of the API is of particular interest. This work presents a method for predicting the long-term physical stability of ASDs (crystallization onset time). The new approach combines the Johnson-Mehl-Avrami-Kolmogorov (JMAK) equation with classical nucleation theory. The shelf life predicted using the new approach depends on supersaturation (determined with PC-SAFT), viscosity (determined with WLF equation or Arrhenius equation) and two specific model parameters k' and B. The latter were fitted to a few fast crystallization-kinetics measurements above the glass transition of the ASD. An additional crystallization-kinetics measurement below the glass-transition temperature of the ASD was used to determine the Arrhenius parameters. Once all parameters are determined for a given API/polymer combination and manufacturing method, they are valid for any API load, temperature, and RH. The proposed approach allows predicting the shelf life (crystallization onset) of a potential ASD in early stage of development within a few days. It was successfully verified for ASDs stored at 25 °C and 10% RH or 60% RH.

Continuous Manufacturing and Molecular Modeling of Pharmaceutical Amorphous Solid Dispersions

Amorphous solid dispersions enhance solubility and oral bioavailability of poorly water-soluble drugs. The escalating number of drugs with poor aqueous solubility, poor dissolution, and poor oral bioavailability is an unresolved problem that requires adequate interventions. This review article highlights recent solubility and bioavailability enhancement advances using amorphous solid dispersions (ASDs). The review also highlights the mechanism of enhanced dissolution and the challenges faced by ASD-based products, such as stability and scale-up. The role of process analytical technology (PAT) supporting continuous manufacturing is highlighted. Accurately predicting interactions between the drug and polymeric carrier requires long experimental screening methods, and this is a space where computational tools hold significant potential. Recent advancements in data science, computational tools, and easy access to high-end computation power are set to accelerate ASD-based research. Hence, particular emphasis has been given to molecular modeling techniques that can address some of the unsolved questions related to ASDs. With the advancement in PAT tools and artificial intelligence, there is an increasing interest in the continuous manufacturing of pharmaceuticals. ASDs are a suitable option for continuous manufacturing, as production of a drug product from an ASD by direct compression is a reality, where the addition of multiple excipients is easy to avoid. Significant attention is necessary for ongoing clinical studies based on ASDs, which is paving the way for the approval of many new ASDs and their introduction into the market.

A Hot-Melt Extrusion Risk Assessment Classification System for Amorphous Solid Dispersion Formulation Development

Several literature publications have described the potential application of active pharmaceutical ingredient (API)–polymer phase diagrams to identify appropriate temperature ranges for processing amorphous solid dispersion (ASD) formulations via the hot-melt extrusion (HME) technique. However, systematic investigations and reliable applications of the phase diagram as a risk assessment tool for HME are non-existent. Accordingly, within AbbVie, an HME risk classification system (HCS) based on API–polymer phase diagrams has been developed as a material-sparing tool for the early risk assessment of especially high melting temperature APIs, which are typically considered unsuitable for HME. The essence of the HCS is to provide an API risk categorization framework for the development of ASDs via the HME process. The proposed classification system is based on the recognition that the manufacture of crystal-free ASD using the HME process fundamentally depends on the ability of the melt temperature to reach the API’s thermodynamic solubility temperature or above. Furthermore, we explored the API–polymer phase diagram as a simple tool for process design space selection pertaining to API or polymer thermal degradation regions and glass transition temperature-related dissolution kinetics limitations. Application of the HCS was demonstrated via HME experiments with two high melting temperature APIs, sulfamerazine and telmisartan, with the polymers Copovidone and Soluplus. Analysis of the resulting ASDs in terms of the residual crystallinity and degradation showed excellent agreement with the preassigned HCS class. Within AbbVie, the HCS concept has been successfully applied to more than 60 different APIs over the last 8 years as a robust validated risk assessment and quality-by-design (QbD) tool for the development of HME ASDs.

Quality-by-design in hot melt extrusion based amorphous solid dispersions: An industrial perspective on product development

An industrially feasible approach to overcome the solubility and bioavailability limitations of poorly soluble active pharmaceutical ingredients is the development of amorphous solid dispersions (ASDs) using hot-melt extrusion (HME) technique. The application of Quality by Design (QbD) had a profound impact on the development of HME-based ASDs. The formulation and process optimization of ASDs manufactured via HME techniques require an understanding of critical quality attributes, critical material attributes, critical process parameters, risk assessment tools, and experimental designs. The knowledge gained from each of these QbD elements helps ensure the consistency of product quality. The selection and implementation of appropriate Design of Experiments (DoE) methodology to screen and optimize the formulation and process variables remain a major challenge. This review provides a comprehensive overview on QbD concepts in HME-based ASDs with an emphasis on DoE methodologies. Further, the information provided in this review can assist researchers in selecting a suitable design with optimal experimental conditions. Specifically, this review has focused on the prediction of drug-polymer miscibility, the elements and sequence of QbD, and various screening and optimization designs, to provide insights into the formulation and process variables that are encountered routinely in the production of HME-based ASDs.