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Insight into nucleation kinetics and other nucleation parameters can be obtained from probability distributions of induction time measurements in combination with the classical nucleation theory. In this work, induction times of crystallization were recorded using a robust and automated methodology involving a focused beam reflectance measurement probe. This methodology is easily interchangeable between different crystallizers which allowed us to investigate the effects of scale-up on the kinetics of crystal nucleation of paracetamol from 2-propanol in four different crystallizers, ranging from small magnetically stirred 10 mL solutions to overhead-stirred solutions of 680 mL. The nucleation rate was an order of magnitude faster in the magnetically stirred crystallizer as compared to the crystallizers involving overhead stirring. The thermodynamic part of the nucleation rate expression did not significantly change the nucleation rate, whereas the kinetic nucleation parameter was found to be the rate-determining process when the crystallization process was scaled-up. In particular, the shear rate was rationalized to be the part of the kinetic parameter that changes most significantly when the crystallization process was scaled-up. The effect of shear rate on the nucleation kinetics decreases with increasing volume and plateaus when the volume becomes too large. In this work, the nucleation mechanism was also investigated using the chiral sodium chlorate system. These experiments showed that the single nucleus mechanism is the underlying nucleation mechanism in all four tested crystallization setups when supersaturation remains the same. When the supersaturation was changed continuously through cooling, crystallization was driven by a multinucleus mechanism. The automated and robust method used to measure induction times can easily be extended to other crystallizers, enabling the measurement of induction times beyond small crystallizer volumes.

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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.

The striking ability of impurities to significantly influence crystallization processes is a topic of paramount interest in the pharmaceutical industry. Despite being present in small quantities, impurities tend to considerably change a crystallization process as well as the final crystalline product. In the present work, the effect of two markedly different impurities 4-nitrophenol and 4′-chloroacetanilide on the solubility, nucleation, and crystallization of paracetamol is described. In the first part of this work, the fundamentals are outlined and show that, although each impurity led to a small increase in solubility of paracetamol, their effect as a nucleation inhibitor was much more pronounced. Induction time experiments were used in conjunction with the classical nucleation theory to show that the impurities did not affect the solid−liquid interfacial energy but instead significantly reduced the kinetic factor, overall resulting in reduced nucleation rates. Intriguingly, both impurities influenced the solubility and nucleation of paracetamol in a similar fashion despite their significant differences in terms of molecular structure, solubility, and ability to incorporate into the crystal structure of paracetamol. In the second part of this work, the incorporation of 4′-chloroacetanilide into the solid phase of paracetamol was investigated. The presence of 4′-chloroacetanilide in the solid phase of paracetamol significantly increased the compressibility of paracetamol, resulting in improved processability properties of paracetamol. The compressibility efficiency of paracetamol could be controlled using the amount of incorporated 4′-chloroacetanilide. Therefore, an experimental design space was developed and utilized to select the most important process parameters for impurity incorporation. Intriguingly, the number of carbon atoms in the aliphatic chain of the alcohol solvent strongly correlated to the impurity incorporation efficiency. As a result, it was feasible to accurately control the compressibility and the amount of 4′-chloroacetanilide in the solid phase of paracetamol by simply choosing the required alcohol as the solvent for crystallization. Thus, the present work comprehensively shows how different impurities impact the key crystallization mechanisms and properties of a pharmaceutical product. Rational process control over the incorporation of impurities and additives allows for advanced manufacturing of products with tailored specifications.

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α-Thio-β-chloroacrylamides are of considerable synthetic utility due to their versatile reactivity profile enabling a diverse range of useful transformations. Availability of accurate and extensive solubility data and models is a prerequisite for advanced process optimization of such valuable pure synthetic intermediate compounds, in particular facilitating their isolation with a high degree of efficiency and control. As an illustrative example the solubility of one such derivative, N-(4methylphenyl-Z-3-chloro-2-(phenylthio)propenamide (Z-1), is described in the present work. Solubility data is reported in 12 pure solvents specifically selected for their potential utility in synthesis and isolation at scale. Solubility data are determined using the gravimetric method across a range of temperatures T= (278.15 to 318.15) K under pressure of 0.1 MPa. On a molar basis, the solubility of Z-1 at temperature T = 298.15 K was observed to follow the order: tetrahydrofuran > 1,2-dichloroethane > 2-methyltetrahydrofuran > butanone > acetone > ethyl acetate > methyl acetate > toluene > tert-butyl methyl ether > acetonitrile > 2-propanol > 2-methyl-2-butanol. The experimental solubility data were correlated by the modified Apelblat, Margules, Van-Laar, Wilson, and nonrandom two-liquid (NRTL) models. The NRTL model was found to result in the lowest error for 8 of the 12 solvents tested. In the case of acetonitrile, the Wilson model had a slightly lower mean square error of 3.52 × 10 −4 while for methyl acetate and 1,2-dichloroethane the Van-Laar model had the smallest mean square error of 1.47 × 10 −3 and 3.54 × 10 −4 , respectively. The provision of solubility data and models for such a prized and versatile compound will assist with further development of continuous isolation strategies.