Pressurized-synthetic methodology for solubility determination at elevated temperatures with application to paracetamol in pure solvents

This paper describes a new nonintrusive method for the determination of high-temperature solubility data. Accurate high-temperature solubility data is vital to many industrial manufacturing processes such as cooling crystallization with direct implications for yield, throughput, and solvent usage. However, the provision of such data is notably absent from published literature for many active pharmaceutical ingredients. Pressurized-synthetic methodology is presented as a new technique for determining high-temperature solubility data. Paracetamol (acetaminophen) is used as a reference active pharmaceutical ingredient to validate the methodology. Solubility data determined using the pressurized-synthetic approach is reported for several pure solvents across a significantly extended temperature range. In the case of methanol, solubility data is obtained up to 354.15 K, above the atmospheric boiling point of the solvent, 337.65 K, and far in excess of the temperature range for which data exists in the literature, 268.15-303.15 K. The data obtained using the pressurized-synthetic method is validated against an extended gravimetric data set at temperatures up to the atmospheric boiling point for each solvent. Sensitivity studies were conducted to determine the influence of factors such as temperature gradient on the ultimate solubility determination. A temperature-based standard deviation of 0.1 K was established for paracetamol in 2-propanol at 303.15 K, comparing favorably with the temperature-based equivalent standard deviation of 0.2 K for the gravimetric approach. Binary interaction parameters for the pressurized-synthetic solubility data are derived and estimated for four different activity coefficient models, namely Margules, Van-Laar, Wilson, and non-random two-liquid (NRTL), along with the empirical solubility equation of Apelblat. For each solvent, the quality of fit of each of the activity coefficient models is analyzed. The NRTL model was found to best fit the experimental data for methanol, ethanol, 2-propanol, and acetone with mean square errors of 5.73 × 10^-5, 3.00 × 10^-4, 1.70 × 10^-4, and 7.35 × 10^-5, respectively. The pressurized-synthetic approach provides a nonintrusive, validated, and readily automated approach for the provision of valuable high-temperature solubility data that can be readily extended to binary and ternary systems.