Hydroxypropyl Cellulose for Drug Precipitation Inhibition: From the Potential of Molecular Interactions to Performance Considering Microrheology

A study of hydrophobic domain formation of polymeric drug precipitation inhibitors in aqueous solution

Despite the widespread use of polymers as precipitation inhibitors in supersaturating drug formulations, the current understanding of their mechanisms of action is still incomplete. Specifically, the role of hydrophobic drug interactions with polymers by considering possible supramolecular conformations in aqueous dispersion is an interesting topic. Accordingly, this study investigated the tendency of polymers to create hydrophobic domains, where lipophilic compounds may nest to support drug solubilisation and supersaturation. Fluorescence spectroscopy with the environment-sensitive probe pyrene was compared with atomistic molecular dynamics simulations of the model drug fenofibrate (FENO). Subsequently, kinetic drug supersaturation and thermodynamic solubility experiments were conducted. As a result, the different polymers showed hydrophobic domain formation to a varying degree and the molecular simulations supported interpretation of fluorescence spectroscopy data. Molecular insights were gained into the conformational structure of how the polymers interacted with FENO in solution phase, which apart from nucleation and crystal growth effects, determined drug concentrations in solution. Notable was that even at the lowest polymer concentration of 0.01 %, w/v, there were polymer-specific solubilisation effects of FENO observed and the resulting reduction in apparent drug supersaturation provided relevant knowledge both from a mechanistic and practical perspective.

Physiological Buffer Effects in Drug Supersaturation - A Mechanistic Study of Hydroxypropyl Cellulose as Precipitation Inhibitor

Phosphate buffer is predominantly used instead of the more physiological bicarbonate buffer, as the latter requires a technical solution of adequate gas mixing. Recent pioneering work on how bicarbonate buffer affected drug supersaturation revealed interesting effects that call for more mechanistic understanding. Therefore, this study used hydroxypropyl cellulose as a model precipitation inhibitor and real-time desupersaturation testing was conducted with the drugs bifonazole, ezetimibe, tolfenamic acid and triclabendazole. Specific buffer effects for the different compounds were noted and overall, statistical significance was found for the precipitation induction time (p = 0.0088). Interestingly, molecular dynamics simulation revealed a conformational effect of the polymer in the presence of the different buffer types. Subsequent molecular docking trials suggested a stronger interaction energy of drug and polymer in the presence of phosphate compared to bicarbonate buffer (p =0.0010). In conclusion, a better mechanistic understanding of how different buffers affect drug-polymer interactions regarding drug supersaturation was achieved. Further mechanisms may account for the overall buffer effects and additional research on drug supersaturation is certainly needed, but it can already be concluded that bicarbonate buffering should be used more often for in vitro testing in drug development.

Supersaturation and phase behavior during dissolution of amorphous solid dispersions

Amorphous solid dispersion (ASD) is a promising strategy to enhance solubility and bioavailability of poorly water-soluble drugs. Due to higher free energy of ASD, supersaturated drug solution could be generated during dissolution. When amorphous solubility of a drug is exceeded, drug-rich nanodroplets could form and act as a reservoir to maintain the maximum free drug concentration in solution, facilitating the absorption of the drug in vivo. Dissolution behavior of ASD has received increasing interests. This review will focus on the recent advances in ASD dissolution, including the generation and maintenance of supersaturated drug solution in absence or presence of liquid-liquid phase separation. Mechanism of drug release from ASD including polymer-controlled dissolution and drug-controlled dissolution will be introduced. Formation of amorphous drug-rich nanodroplets during dissolution and the underlying mechanism will be discussed. Phase separation morphology of hydrated ASD plays a critical role in dissolution behavior of ASD, which will be highlighted. Supersaturated drug solution shows poor physical stability and tends to crystallize. The effect of polymer and surfactant on supersaturated drug solution will be demonstrated and some unexpected results will be shown. Physicochemical properties of drug and polymer could impact ASD dissolution and some of them even show opposite effect on dissolution and physical stability of ASD in solid state, respectively. This review will contribute to a better understanding of ASD dissolution and facilitate a rational design of ASD formulation.

Purely Predicting the Pharmaceutical Solubility: What to Expect from PC-SAFT and COSMO-RS?

A pair of popular thermodynamic models for pharmaceutical applications, namely, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state and the conductor-like screening model for real solvents (COSMO-RS) are thoroughly benchmarked for their performance in predicting the solubility of active pharmaceutical ingredients (APIs) in pure solvents. The ultimate goal is to provide an illustration of what to expect from these progressive frameworks when applied to the thermodynamic solubility of APIs based on activity coefficients in a purely predictive regime without specific experimental solubility data (the fusion properties of pure APIs were taken from experiments). While this kind of prediction represents the typical modus operandi of the first-principles-aided COSMO-RS, PC-SAFT is a relatively highly parametrized model that relies on experimental data, against which its pure-substance and binary interaction parameters (k_ij) are fitted. Therefore, to make this benchmark as fair as possible, we omitted any binary parameters of PC-SAFT (i.e., k_ij = 0 in all cases) and preferred pure-substance parameter sets for APIs not trained to experimental solubility data. This computational approach, together with a detailed assessment of the obtained solubility predictions against a large experimental data set, revealed that COSMO-RS convincingly outperformed PC-SAFT both qualitatively (i.e., COSMO-RS was better in solvent ranking) and quantitatively, even though the former is independent of both substance- and mixture-specific experimental data. Regarding quantitative comparison, COSMO-RS outperformed PC-SAFT for 9 of the 10 APIs and for 63% of the API-solvent systems, with root-mean-square deviations of the predicted data from the entire experimental data set being 0.82 and 1.44 log units, respectively. The results were further analyzed to expand the picture of the performance of both models with respect to the individual APIs and solvents. Interestingly, in many cases, both models were found to qualitatively incorrectly predict the direction of deviations from ideality. Furthermore, we examined how the solubility predictions from both models are sensitive to different API parametrizations.