industrial crystallization - developments in research and technology

0263–8762/04/$30.00+0.00 # 2004 Institution of Chemical Engineers Trans IChemE, Part A, December 2004 Chemical Engineering Research and Design, 82(A12): 1567–1570

INDUSTRIAL CRYSTALLIZATION Developments in Research and Technology J. ULRICH and M. J. JONES Martin-Luther-Universita¨t Halle-Wittenberg, Institut fu¨r Verfahrenstechnik/TVT, Fachbereich Ingenieurwissenschaften, Halle (Saale), Germany

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n this review paper developments in industrial crystallization are discussed with emphasis on recent highlights in the field. One of the most important past developments can be found in the introduction of the population balance concept. This will be discussed together with more recent developments and topics currently of great interest such as molecular modelling, polymorphism and polymorph prediction at the fundamental scientific level as well as melt crystallization equipment, eutectic freezing crystallization and crystallization control by means of on-line techniques at the applied, industrial level. Potential future directions for industrial crystallization are discussed with reference to past and present developments. The future of industrial crystallization is envisaged to lie in areas such as nano-particle production by means of crystallization and protein crystallization, in addition to some of those mentioned above. Keywords: industrial crystallization; molecular modelling; polymorphs/pseudopolymorphs; crystallizer control; precipitation.

INTRODUCTION Industrial crystallization as a thermal unit operation is still a technology with many poorly understood aspects. Over the past 30 years, large strides have been taken away from crystallization as an ‘art’ and towards putting industrial crystallization onto a firm scientific basis. One of the highlights among the many important developments was the introduction of the population balance concept into industrial crystallization by Randolph and Larson (1971). However, there remain many open questions both in crystallizer design and in crystallization kinetics. Today, a number of new tools are available such as molecular simulation programs or measuring devices which not only encourage new trends in research but also provide the basis for faster progress in the field. Of course new challenges constantly arise from new industrial needs. On the other hand there is a noticeable trend away from the classical engineering research of the past and towards research at the molecular or interfacial level (including computerbased molecular modelling of crystals and the prediction of polymorphs and pseudopolymorphs) or research on complicated substances such as drugs or proteins on one side and sensor development for the on-line control of crystallizers or precipitation processes on the other. Software for computer simulations of crystallization processes is by far more developed when compared to the  Correspondence to: Professor J. Ulrich, Department of Chemical Engineering, Martin-Luther-Universita¨t Halle-Wittenberg, D-06099 Halle (Saale), Germany. E-mail: [email protected]

available sensors, despite the obvious and urgent need for progress in the measurement of accurate and reliable process data. To control crystal growth at a constant and optimum level requires constant information regarding the position of the process with respect to both the supersaturation of the system and the metastable zone width under the pertinent process conditions. The optimum growth conditions are those that maximise the product yield while producing high quality crystals. This means producing the required crystal size distribution as well as the desired purity of crystals or crystal agglomerates. The metastable zone width depends upon various process parameters such as temperature, rate of attainment of supersaturation (i.e. cooling or evaporation rate), presence or absence of (seed) crystals and, most importantly, the composition of the solution (e.g. impurity enrichment in batch processes or concentration fluctuations in the feed stream of a continuous process can have a significant influence on the width of the metastable zone). THE PAST Up until the end of the 1980s, the development of engineering tools to improve the design and operation of large scale, continuously operating crystallization processes was one of the key areas in research and development of industrial crystallization. The introduction of the population balance concept into industrial crystallization was one of the more important developments (Randolph and Larson, 1971). The introduction of growth rate dispersion (White and Wright, 1971;

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Ulrich, 1989) and its incorporation into the population balance concept was another major step forward. In parallel with these developments Toyokura and coworkers introduced the ‘design chart’ (Aoyama et al., 1989; Luo et al., 1989), aiming in the same direction. One of the improvements in the description of the kinetics of industrial crystallization which was introduced into the abovementioned concepts is the effectiveness factor developed by Garside and Tavare (Garside, 1971; Garside and Tavare, 1981). Computer simulations for crystallization processes have been, and still are, improving in precision and quality with increasing computer power; however, almost all of them lack from verification and their accuracy is therefore an unknown quantity. The data from running plants necessary for comparison with simulations are generally not available and in most cases have simply never been measured! The progress in simulation tools is mainly due to the relatively advanced state of the available hard- and software. In contrast, developments in sensor technology required for on-line and in-line measurements of the physical and process properties in industrial plants are somewhat lacking and existing techniques are not necessarily of the required quality with regard to parameters such as sensitivity, robustness and cost. The main physical/process parameters that need to be measured on- or in-line are of course supersaturation, width of metastable zone as well as crystal size distribution and crystal shape. There is a clear need to have the ability to measure process parameters that may influence crystal size and shape such as impurity content. However, the influence of other chemical species on crystal growth is poorly understood, in particular when considering the effect of impurity concentration. In recent years, there has been a large increase in the number of books on industrial crystallization (Arkenbout, 1995; Hofmann, 2004; Hurle, 1994; Jones, 2002; Mersmann, 2001; Mullin, 2000; Myerson, 2002; Myerson, 1999; Nyvlt et al., 1995; Nyvlt and Ulrich, 1995; So¨hnel and Garside, 1992; Ulrich and Glade, 2003; van der Eerden and Bruinsma, 1995). THE PRESENT Current computing technology allows molecular simulations of crystalline materials to be carried out with relative ease. Ideas originating in the 1950s (Hartman and Perdock, 1955; Hartman and Bennema, 1980) and many others (Berkovitch-Yellin, 1985, for example) have been transferred into computer codes that have been applied to predict morphologies of crystalline solids with varying degrees of success. In recent years, the idea of tailor made additives (Black, et al., 1986; Wang, et al., 1985) has generated considerable interest. Additives present an option for product design, specifically by controlling and directing crystal shape. Although the concept has been demonstrated in practice (Davey et al., 1991), theoretical models able to account for the effect of additives on crystal shape are still somewhat lacking. Although modifications to the abovementioned models have been proposed (for example, surface docking and ‘build-in’ of additives Nieho¨rster, 1997; Mattos, 1999) and successfully applied, there are still cases where these models fail. The reasons why these

models are not able to predict the crystal morphology are still unclear and require further investigation. In any case, none of these models properly treat concentration effects and the modelled additive concentrations are usually governed by the number of molecules in the crystal unit cell that can be replaced by an additive (build-in) or by the size of the slice used for surface docking and are therefore unrealistically large. Considering this the more surprising it is that these models are successful in those cases where they predict the morphology correctly! In part, this limitation is due to available computing hardware in the academic community. At present, with the currently available computer codes, large model systems containing many molecules need to be defined in order to approach smaller additive concentrations. Large models, however, are memory intensive and result in arduous, time-consuming calculations on single processor computers. It is worth noting, that additive influence is not the only problem that has yet to be solved satisfactorily. Other problems are encountered in the modelling of solvent crystallization (where solvent effects may be viewed as the extreme case of an ‘additive’) as well as in the prediction of polymorphs and the conditions under which a given polymorph crystallizes. Prediction of polymorphs has received some academic attention in recent years (Rovira, 2001) as well as through the development of proprietary software (Cerius2 Polymorph Module, Accelrys Inc.) though there is still much scope for development. Nucleation is a further area where attempts to model the nucleation process are few and far between (see, for example, Koishi, et al., 2003; Mucha and Jungwirth, 1993). Much of this interest in crystallization stems from the field of pharmaceuticals polymorphs and pseudopolymorphs, which represents a major driving force in industrial crystallization research today. This is clearly evidenced by the number of papers in the proceedings of the last two International Symposia on Industrial Crystallization in Cambridge 1999 (Garside, 1999) and Sorrento 2002 (Chianese, 2002) which show a strongly increasing trend in that particular area. In the field of pharmaceuticals it is essential to characterize a given active ingredient as thoroughly as possible in order to understand if and under which circumstances the drug substance exhibits polymorphism, so as to avoid the production of the ‘wrong’ polymorph. Polymorphs generally exhibit different solubilities and rates of dissolution and as a consequence have different bioavailability. In extreme cases, employing the wrong polymorph can lead to either inefficacy or overdosing of the active ingredient. One well known example is the case of Ritonavir, an anti-retroviral drug manufactured by Abbott Laboratories. Only one crystal form was ever identified (Chemburkar et al., 2000) in the drug development process. Furthermore, it was assumed that polymorphism was immaterial to the product, since the drug was formulated as a semi-solid or liquid oral dosage form due to its lack of bioavailability in the solid state. However, two years into production, a new, more stable, solid form began to emerge in the shape of crystalline material precipitating in the original formulation. This new form was found to have significantly less favourable dissolution characteristics compared to the original polymorph. It was later established (Bauer et al., 2001) that the new polymorph only nucleates under

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INDUSTRIAL CRYSTALLIZATION conditions of high supersaturation and when seeded. Since this observation suggests that the stable form should never have been observed, further seeding experiments were carried out with structurally similar degradation products observed in the manufacturing process. These experiments demonstrated, that the related compounds can lead to the nucleation of the stable form of the drug, presumably via a templating mechanism. One consequence of the unexpected production of the new, undesired, polymorph was a prolonged investigation of the causes of and solutions to this problem, costing the company a significant amount of money. This example highlights the vagaries of polymorphism. Despite thorough polymorph screening, it cannot be guaranteed that the results obtained cover all possibilities. In addition, polymorphism can lead to complications in terms of intellectual property rights and incomplete knowledge of polymorphism in a new drug entity leaves the opportunity for competitors to secure patent rights on alternative polymorphs and hence alternative formulations of the drug, with disastrous consequences for the originating company. Further to this, a noticeable number of papers dealing with precipitation exist. Important features of these publications are the control of processes as well as the control of crystal modification and of the sizes of crystals produced. The production of nano-materials (again: the idea of product design) is one of the new aims here. The development of the abovementioned sensors for the control of crystallization processes is one of the most important research topics currently emerging, as witnessed by the many papers being published (see the abovementioned Symposia). Furthermore, sensors are also of interest for precipitation processes and for the control of the polymorph that should be produced. Great strides have been taken improving in-line and on-line control of crystallizers. Examples can be found in the development of techniques for measuring supersaturation using either near infra-red spectroscopy (Dunuwila et al., 1994) and ultrasoundbased techniques (Omar and Ulrich, 1997). Both methods have the potential to lead to a better understanding of batch crystallization processes resulting in better crystal, and therefore product, quality than that available from most current processes. A proper understanding of crystallization processes would allow, amongst others, better control of growth rates—ideally, the ability to keep growth rates constant—control of nucleation and the reduction of liquid inclusions in crystals. There are of course many other interesting developments which have, however, a reduced scope when compared to the topics discussed so far, but will nonetheless have a significant impact on developments in the area of crystallization. It is worth mentioning a few, such as the development of eutectic freezing technology (Drummond et al., 2002), fractionation of oils and fats (Lu¨deke et al., 2003), the separation of chiral substances (Grandeury et al., 2003) or supercritical crystallization to produce fine particles without solid liquid separation problems (Wubbolts, 2000).

THE FUTURE Further development of the topics already mentioned and where presently activity is noticeable in the industrial

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crystallization research community can be expected. In particular the following areas should be mentioned: . . . . .

molecular modeling; polymorph predicting; nano-particle production; sensor development; speciality process development.

It stands to reason to expect that recent developments in computer hardware such as massively parallel computers using inexpensive, off-the-shelf components will facilitate further developments in the modelling of crystallization processes. In those cases where many independent calculations are required, distributed computing is clearly suited to reduce the real-time requirements for computations. Prime candidates for developments in this direction, in the absence of more elegant models, are habit modelling in the presence of realistic additive concentrations employing large model systems as well as modelling of nucleation. Polymorph prediction, too, could conceivably benefit from massively parallel computing, where clustering approaches necessitate the investigation of large numbers of configurations. New topics are bound to emerge. With growing knowledge and growing demand for highly specialized products the challenges to industrial crystallization are increasing rather than diminishing. One example for the many new challenges we are facing should be mentioned: separation of crystalline substances with their origin in bioprocesses. Bioprocesses result in complex solutions with variable component concentrations. Nonetheless, bioproducts are expected to have the same or even better quality (as measured by their purity, for example) as those manufactured in traditional and very well defined chemical processes. Here, proteins are worth special consideration. Proteins are used for a range of purposes such as therapeutics/ pharmaceuticals, medical sensors and in more profane applications such as household detergents. In the long term, the growing understanding of the human genome and of the functioning of the human body is likely to draw with it further developments in protein therapy and therefore the need to manufacture a large range of proteins on an industrial scale. Although protein crystals have been grown for over 150 years, much of the interest in crystallizing proteins has focussed firmly on generating good quality single crystals for structure determination. McPherson (1999) provides a detailed overview of current state-ofthe-art. Only few protein systems have been characterised exhaustively in terms of solubility, crystal growth and nucleation kinetics (Cacioppo and Pusey, 1991; Judge, 1996). From the literature it is clear that those researchers concerned with growth of single crystals of proteins tend to work with materials that have been meticulously purified by other means and studiously avoid conditions typically found in fermentation broths, namely poorly defined content and variable concentration of species present. The knowledge accumulated in those fundamental studies available is therefore perhaps no more than a good starting point for further investigations and potentially of limited applicability to industrial applications.

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There is still much worthwhile research to be carried out and we welcome new people to the field with—hopefully— many new and innovative ideas.

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The manuscript was received 11 June 2004 and accepted for publication after revision 5 November 2004.

Trans IChemE, Part A, Chemical Engineering Research and Design, 2004, 82(A12): 1567–1570