Process Design for Antisolvent Crystallization of Erythromycin

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Process Design for Anti-solvent Crystallization of Erythromycin Ethylsuccinate in Oiling-out System Xiang Li, Qiuxiang Yin, Meijing Zhang, Baohong Hou, Ying Bao, Junbo Gong, Hongxun Hao, Yongli Wang, Jingkang Wang, and Zhao Wang Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.6b00795 • Publication Date (Web): 23 Jun 2016 Downloaded from http://pubs.acs.org on June 29, 2016

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Industrial & Engineering Chemistry Research

Process Design for Anti-solvent Crystallization of Erythromycin Ethylsuccinate in Oiling-out System Xiang Li†, Qiuxiang Yin†, ‡,Meijing Zhang†, ‡, Baohong Hou†, ‡, Ying Bao†, ‡, Junbo Gong†, ‡, Hongxun Hao†, ‡, Yongli Wang†, ‡, Jingkang Wang†, ‡, Zhao Wang†, ‡,* †

School of Chemical Engineering and Technology, State Key Laboratory of Chemical

Engineering, Tianjin University, and ‡Collaborative Innovation Center of Chemical Science and Chemical Engineering, Tianjin 300072, People’s Republic of China *Corresponding author Tel.: 86-22-27405754. Fax: 86-22-27374971. E-mail: [email protected]

ABSTRACT

The crystallization process of erythromycin ethylsuccinate in a tetrahydrofuran– water system was investigated. Results show that oiling out occurs under several conditions; hence, a phase diagram with a liquid–liquid equilibrium area was established experimentally. For improved understanding of oiling-out crystallization, a series of in-situ tools, including FBRM, ATR-FTIR, and PVM, were applied to monitor the oiling-out phenomenon and the subsequent nucleation of erythromycin ethylsuccinate. SEM images were employed to analyze the influence of oiling out on the properties of the final crystals. The nucleation mechanism of erythromycin ethylsuccinate differs significantly depending on the location of the line of operation. The combination of cooling method and anti-solvent crystallization can be achieved with fundamental data of the phase diagram to suppress the oiling out phenomenon and obtain crystal products with high quality. The ternary phase diagram is of great importance in the process design of anti-solvent crystallization for an oiling-out system.

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1. Introduction Anti-solvent crystallization1-4 is widely utilized as an isolation and purification method in industries nowadays because of its low cost and high efficiency. In a crystallization system that utilizes a binary solvent, oiling out

5-8

or liquid–liquid

phase separation, which refers to the appearance of a second liquid, frequently occurs during crystallization development at the plant scale. The oiling out phenomenon was first reported in a protein system9 and was found to be similar to the phase behavior of polycyclic aromatic hydrocarbons system10. Because oil droplets formed before nucleation and traditional methods lack effectively process control on crystallization, consequentially impurity is incorporated into the final products 11. Although the oiling out phenomenon has been utilized to change the characteristics of crystals in a few studies in recent years12-15, the main purpose of crystallization is still purification. Thus, the suitable crystallization process conditions is the key factor for the occurrence of the oiling out phenomenon. The oiling out phenomenon promotes the formation and development of a two-step nucleation mechanism16-18. Oil droplets are considered unstable amorphous phases or pre-crystalline structures according to this view. However, structure determination may provide some insight to the oiling out phenomenon

19, 20

.

Characterization of the oiling out system continues to play important roles in understanding the mechanism of oiling out crystallization. Phase diagrams are essential and helpful in obtaining a comprehensive understanding of oiling out crystallization21-23. Phase diagrams provide a global picture of the oiling out system, based on which suitable operating conditions are identified. Thus, crystallization can occur outside the region of the liquid–liquid equilibrium area. To this aim, correlating the phase equilibrium data with classical thermodynamic models is essential for the design of crystallization processes in oiling out systems. However, only a few studies have applied the thermodynamic model to predict oiling out behavior24-26 and design the crystallization process27-29. Phase diagrams become complicated when a binary solvent is used 30. The binary


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phase diagram has been widely utilized in liquid−liquid phase separation (LLPS) induced by temperature and concentration31-33. However, the oiling out phenomenon cannot be completely suppressed for composition-induced LLPS because of the limited information provided by a binary phase diagram,. Information on the location and shape of the phase boundaries needs to be acquired for anti-solvent crystallization systems. The ternary phase diagram can offer abundant information34-36, including phase boundaries from the thermodynamic view, whereas the binary phase diagram focuses on the kinetic point corresponding to the supersaturation rate generated in the solution. Process analytical technology (PAT) is defined as a system for design, analysis, and control of manufacturing processes through timely measurement of critical quality and performance attributes37, 38. Problems including time delay for analysis and the solution change caused by sampling process can be avoided with real-time monitoring. During the early stage of investigation, detailed and critical information about when and how various process events take place can be acquired with the application of PAT. For example, Wu et al successfully confirmed the onsets of distinct stages39 and nucleation/growth mechanisms40 with real-time information obtained through PAT’s. With an enhanced understanding of mechanism and process, the process design and optimization on formulation parameters and process parameters can be achieved with PAT. Duffy designed the crystallization with a desupersaturation profiles for suppressing oiling out11. Combined with feedback process control strategies, PAT has been used successfully for providing high quality product. The application of concentration feedback control has been demonstrated for anti-solvent crystallization of some pharmaceutical compounds41, 42. Process analytical technologies (PATs) have been employed to monitor the oiling out and crystallization in the past two decades11, 43-45. According to previous studies, an obvious variation of the solute concentration and chord counts can be observed when oil droplets formed and crystal nucleation occurred. Also oil droplets and crystal can be differentiated by morphology with visualized images. In this work, with the useful and reliable information provided by PATs, an improved understanding of



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oiling out crystallization can be acquired. Oiling out and nucleation can be tracked and distinguished by analyzing the chord counts provided by focused beam reflectance measurement (FBRM) and the peak height acquired from Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) probes. Images of crystals and droplets obtained through particle vision measurement (PVM) help divide the entire crystallization process into different steps and identify the nucleation position. This study aims to provide a basic understanding of the oiling out phenomenon in an erythromycin ethylsuccinate (EES) system, then a coupling method was developed to suppress oiling out in the EES system. First, the liquid–liquid equilibrium area was determined experimentally and correlated with the NRTL model. Second, FBRM, ATR-FTIR, and PVM were applied to characterize the oiling out and crystallization processes. After combining the thermodynamic data of the phase diagram and in-situ data, cooling method coupled with anti-solvent method is utilized to eliminate or suppress oiling out in the EES system. 2. Material and methods 2.1. Materials. EES with a mass fraction purity of more than 0.98 was supplied by Xi’an Lijun Co. Ltd. The structure of EES is shown in Figure 1. Tetrahydrofuran (THF) of analytical reagent grade (mass fraction purity >0.995) was used as a solvent without further purification; it obtained from Tianjin Kewei Chemical Reagent Co. Ltd. of China. Distilled-deionized water (conductivities < 0.5 µs cm-1) was prepared in the laboratory and used throughout the study. 2.2. Measurement of the Phase Diagram A 250 ml round-bottomed jacketed glass batch crystallizer was employed to determine the phase boundary of the liquid–liquid equilibrium area. The experimental procedure is as follows. A desired concentration of EES in THF–water binary solvent was added to the crystallizer and agitated with a mechanical stirrer under a steady


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desired temperature. The temperature was controlled by a thermostat bath (Julabo CF41, Germany) with uncertainty of ±0.02 K. The stirring rate was set to 300 rpm. The experiments show that the liquid–liquid equilibrium can be reached after 6 h. Liquid–liquid equilibrium can be maintained for a long time because of the slow volatilization rate of THF under the selected temperature. The average sample concentrations at 6 and 8 h are nearly similar, with an average relative error of less than 1%. Then, the agitation was turned off. The solution separated into two liquids after settling for half an hour. A total of 20 ml of each liquid sample was obtained with an injector with filtration (0.22 µm PVDF filters). The injector utilized for sampling and all PVDF filters were preheated to approximately 5 ℃ above the equilibrium temperature. The liquid samples were evaporated in a vacuum oven at 50 ℃ for 24 h. The amount of the remaining solid after drying was weighed using a balance with accuracy of 0.0001 g. The experiments were repeated three times, and the average value was employed to calculate the solute weight fraction in each phase. The relative standard uncertainty of the solute weight measurement was estimated to be 0.05. At the same time, 8–10 µl of solute-lean phase was analyzed directly by Karl Fisher titration to confirm the water content. For solute-rich phase, 5ml sample was diluted with 45ml methanol (chromatographic grade) in 50ml volumetric flask. After that, 8– 10 µl of solute-rich phase can be analyzed by Karl Fisher titration. The relative standard uncertainty of the water content measurement was estimated to be less than 0.05. The method for solid-liquid equilibrium measurements reported in the literature46 was used in this work. 2.3. Oiling Out Crystallization Oiling out crystallization experiments were performed in a 180 ml glass crystallizer with 10.0187 g EES dissolved in 29.9547 g THF. Both temperature and agitation were controlled by EASY-MAX reactor (Mettler-Toledo Easymax-102). The uncertainty of temperature was ±0.1 K. The agitation speed was maintained at 300 rpm, and the rate of water addition was kept at 700 µl/min under the temperature of 308.15 K. 2.4. Normal Crystallization with lower solute concentration



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Normal crystallization experiments were performed in a 180 ml glass crystallizer with 3.3554 g EES dissolved in 30.1973 g THF. Both temperature and agitation were controlled by EASY-MAX reactor. The uncertainty of temperature was ±0.1 K. The agitation speed was maintained at 300 rpm and the rate of water addition was kept at 500 µl/min under the temperature of 308.15 K. 2.5. Crystallization with combination method Crystallizations with combination method were performed in a 180 ml glass crystallizer with 15.6019 g EES dissolved in 27.7688 g THF. Both temperature and agitation were controlled by EASY-MAX reactor. The uncertainty of temperature was ±0.1 K. The agitation speed was maintained at 300 rpm and the rate of water addition was kept at 250 µl/min. The cooling rates of temperature were maintained at 0.125 ℃ /min. 3. Results and Discussion 3.1 Ternary Phase Diagram for the Oiling-out system A phase diagram provides important thermodynamic data for crystallization and determines the choice of solvents, the final yield, and the methods of supersaturation generation for the process design. The phase diagram applied for crystallization optimization depends on the crystallization method. A temperature–composition binary diagram is commonly utilized for oiling-out systems with cooling method. However, to provide improved understanding of the anti-solvent crystallization process of EES, the ternary phase diagram of EES in THF/water binary solvents needs to be determined experimentally and the results are listed in Table 1. As shown in Figures 2–3, the points denote the experiment results, and the lines are the calculation results. The results aim to identify the phase boundary. The entire phase diagram can be divided into five regions: one undersaturated homogenous liquid area, one liquid– liquid area, one solid–liquid–liquid area in which the phases are in equilibrium with one another, and two solid–liquid areas with a large difference in solute concentration. The liquid–liquid area shifts to the THF-lean part of the phase diagram as temperature


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increases from 303.15 K to 308.15 K. Thus, the occurrence of the oiling-out phenomenon can be facilitated at high temperatures in this work. The homogenous undersaturated solution area and the solubility curve expand to the solute-rich part of the phase diagram because of the temperature effect on dissolution capacity. Minimizing the total Gibbs free energy and solving the activity coefficient equations are two robust methods for the accurate of phase equilibrium. Given that total Gibbs free energy minimization is time consuming, activity coefficient equations were utilized for phase equilibrium calculations in this work. Based on the logarithm of activities, the parameters for the NRTL model47 were estimated through the procedure described by Sørensen et al48. Given that small and large activities should be weighted equally in the least-squares minimization problem, a logarithmic formulation was employed. The parameters were determined by minimizing the errors in liquid–liquid equilibrium regions to accurately describe the ternary phase diagram of EES, THF, and water in the liquid-liquid equilibrium (LLE) region. On the basis of the activity condition, LLE errors (FLLE) were calculated with Eq. (1). Activity coefficient models describe the function relationship between the activity coefficient and solution composition, temperature, and parameter set. Considering that mole fraction compositions and temperature can be determined from experiments, the parameter set was obtained to minimize the LLE error.

LLE = ∑ ∑ −

(1)

where n is the number of tie-lines in the LLE region and m refers to the number of

components. The non-randomness parameter ( = ) was fixed at 0.21 for

each binary pair (-), which are commonly used49-52 for simplifying the computation effectively. NRTL parameters g were determined by minimizing of Eq. (1) through

MATLAB. The superscripts w and o refer to the solute-lean phase and solute-rich

phase, respectively, and exp and cal are experimental and calculated mole fraction values, respectively. The melting properties reported in our previous work46 and NRTL parameters were summarized in Table 2. The root mean square deviation (RMSD) calculated by Eq. 2 was utilized to evaluate the accuracy of the data.



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/

'() $%& ∑ ∑ ∑ # − * rmsd = " 6,

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× 100 (2)

N refers to the total number of data points in Liquid-liquid equilibrium area. Given that the RMSD for this ternary system is less than 0.05, the NRTL model can provide a good correlation with the experimental data. The boundary between the two liquid areas and the solid–liquid–liquid area can be evaluated with estimated NRTL parameters by using the following equations:

w γo o = γw

γo o = γ5 5 =

∆7m 89m

:9 − 1; 9

m

(3) (4)

The melting temperature and enthalpy of EES are represented by Tm and∆

Process Design for Antisolvent Crystallization of Erythromycin

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