Experimental investigations of the batch seeded crystallization of paracetamol in 2-propanol were carried out at 200, 300, and 375 rpm agitation rates, using a large seed size (355–500 μm) and a low level of initial supersaturation (S 0 = 1.2) in a laboratory scale reactor. Such experiments are normally conducted for the indirect measurement of crystal growth, contingent on the assumption of negligible nucleation, agglomeration, and breakage. In the present work a copious increase in crystals nuclei was noted shortly following seed addition. The formation of substantial numbers of new nuclei was substantiated through focused beam reflectance measurement, laser diffraction, and scanning electron microscopy. Secondary nucleation was proposed as the origin of the new crystals, and a secondary nucleation threshold was determined, with relative supersaturation between 1.09 and 1.11. Below this limit, crystal growth only was apparent. A study was undertaken to investigate the origin of secondary nucleation. Crystal nuclei breeding, as a mechanism of secondary nucleation, has being theorized for many years; however, it is only very recently that definitive molecular dynamics simulations have provided mechanistic insight as to its action. The mechanically driven attrition and breakage mechanism of secondary nucleation remains prominent in the literature. Stirred vessel experiments were conducted using paracetamol seed crystals suspended in a nonsolvent indicated. Despite 3 h of continuous agitation, no significant change in particle number or size was detected. Only after a threshold of 4 h were significant crystal fatigue and fragmentation evident. Shadowgraphy investigations of crystal jet wall impingement revealed the squeeze film as a key protective element in preventing crystal attrition and breakage. A low temperature (283.15 K) crystallization was conducted which indicated a significant temperature dependency, entirely inconsistent with the attrition and breakage mechanism of secondary nucleation. It was shown through the use of smaller seed crystals (125–250 μm), a high agitation rate, and elevated solution temperature that the rate of secondary nucleation could be enhanced thereby creating the potential for confounding rapid secondary nucleation with growth. The current work elucidates the potential impact of cluster breeding in laboratory scale crystallizations and furthermore provides additional experimental support for the crystal breeding mechanism of secondary nucleation.

A new formulation of the recent stochastic approach for the description of the particle‐size distribution (PSD) time evolution in antisolvent crystal‐growth processes is presented. In this new approach, the crystals size is modeled as a random variable driven by a Gompertz growth term and the corresponding Fokker‐Planck equation is carried out. This proposed formulation, allows an analytical solution to describe the time evolution of the PSD as a function of the model parameters. The analytical solution is obtained by exploiting the typical properties of linear partial differential equations with linear coefficients, and using the analogy with Kalman filter, in terms of the first two stochastic moments: mean and variance of the PSD. Furthermore, an alternative way for the parameters estimation based on the maximum likelihood estimation is also introduced. Validations against experimental data are provided for the NaCl‐water‐ethanol antisolvent crystallization system. © 2012 American Institute of Chemical Engineers AIChE J, 2012

A stochastic formulation for the description of antisolvent mediated crystal growth processes is discussed. In the proposed approach, the crystal size growth dynamics is driven by a deterministic growth factor coupled to a stochastic component. The evolution in time of the particle size distribution (PSD) is then described in terms of a Fokker-Planck equation. In this work, we investigate and assess comparatively the performance of the FPE approach to model the crystal size distribution based on different expressions for the stochastic component. In particular, we investigate the one-dimensional Fokker-Planck equation with a nonlinear diffusion coefficient to represent the crystal growth process. Validations against experimental data are presented for the NaCl water ethanol antisolvent crystallization system. It is shown that the stochastic model better suited to describe the experiments is given by the Geometric Brownian Motion (GBM), which gives an excellent agreement, with the experiments for a wide range of process conditions (i.e., antisolvent feed rate)

ABSTRACT:Crystallization of Active Pharmaceutical Ingredients (APIs) has traditionally been carried out using the batch or semi-batch manufacturing processes, techniques which remain prevalent to this day. Continuous processing affords significant production advantages including enhanced reproducibility of results, optimal control of process conditions, shorter downtime and the elimination of scale-up problems.The Plug Flow Crystallizer (PFC) is one of the most widely employed forms of continuous crystallizer. PFCs are usually selected for processes with fast kinetics and short residence times. One key limitation of PFCs, which has partially constrained their adoption in industry, is that normally they do not allow for equilibrium conditions to be achieved; this is in effect a consequence of the short residence times. Thus, the resultant yield from PFCs is generally less than that of the equivalent batch process. 2Recycling the mother liquor back through the PFC is one approach which can potentially be used in order to mitigate against this drawback, allowing for an amelioration in the continuous process yield.In the present work, the effects of introducing a recycle stream and adjusting critical recycling parameters, namely recycling ratio and axial extraction position, on an idealized PFC are examined. Particular attention is focused on the resultant volume average size of particles d 4,3 , and the process yield η. The influence of residence time on the maximum and minimum yield and size of crystals achievable is investigated. In addition, the effect of recycle parameters on the Particle Size Distribution (PSD) is ascertained, at specified values of yield.The proposed continuous PFC, as conceptualized and modelled with recycle, facilitates practical application in an industrial setting, allowing for augmented continuous process yields, whilst furthermore facilitating PSD control.

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.