Session Chair(s):
- Heather Emady, Arizona State University
Poster Participants
- Marcellus G. F. de Moraes, Georgia Institute of Technology (Abstract)
- Sara Ricchetti, Houston Methodist Research Institute (Abstract)
- Tianxiang Gao, Arizona State University (Abstract)
- Spandana Vajrala, Arizona State University (Abstract)
Session Description:
The poster reception features a mix of poster presentations from both industry and academia. As attendees mingle between posters, light refreshments will be served.
The objective of this session is to promote sharing of experiences and knowledge on specific topics as well as give participants a great opportunity to network with other particle science and technology professionals for developing the next-generation of processes.
The Poster Session will formally take place from 2:45pm - 4:45pm, followed by open networking. Posters will be available for viewing throughout the full reception.
Not finished networking? All FPST attendees will be invited to attend the Happy Hour, taking place at the Spring Meeting and GCPS in the convention center.
Abstracts
Spatially-oriented control in batch crystallization processes using population balance modeling
Marcellus G. F. de Moraes*1, Martha A. Grover2, Argimiro Resende Secchi1, Maurício B. de Souza1 Jr., Paulo L. C. Lage1; 1 Federal University of Rio de Janeiro, Brazil,2 Georgia Institute of Technology, United States
Crystallization is an important separation and purification process with relevant applications in the food, pharmaceutical, fine chemical and fertilizing industries. In these processes, modeling and process control for crystallization are focused on crystal size distribution (CSD) and shape of the crystals in order to make it possible to achieve the desired quality and purity of the product of interest. The control of crystal size and shape is of considerable importance for industrial crystallization processes, as crystal morphology has great influence on downstream steps and also from the point of view of product specification criteria. The consideration of crystal shape in modeling of crystallization processes is also important due to its impact on product effectiveness, such as the bioavailability and tablet stability in pharmaceuticals. Control of the crystallization process is can be facilitated with online measurements, which provide information to be used in the modeling of the process. However, if online measurements are not available, the strongly nonlinear dynamics of these processes makes difficult to establish relations between some inputs (e.g. temperature) and the final desirable characteristics of the crystal product. In this context, image analysis has been shown to be a suitable technique to monitoring the process [1].
In our present work, a population balance model-based scheme for controlling the size and shape of crystals is presented. The modeling was performed using a two-dimensional population balance (2D-PBM) in terms of the two characteristic dimensions of the crystals, describing the evolution of crystal size and shape distributions along the batch time. To identify the nucleation, growth and dissolution kinetics parameters using the 2D-PBM approach along the length and width directions, QICPIC-LIXELL’s high speed dynamic image analysis equipment was used for the online measurement of the CSD, shape parameters and aspect ratio distribution of crystals during the experiments. In this way, the developed model allowed for the prediction of the crystal size and shape distributions during growth-dissolution cycles.
The developed framework was employed to obtain optimal temperature policies for controlling the crystal size and shape distributions that meet target criteria for size, morphology and productivity using the dynamic image analysis along the runs. Based on the concept of using measurements along batch crystallization processes as a trajectory in a phase space [2], a trajectory-endpoint control problem is presented with an oriented control scheme that is applied to the shape of the crystals. The scheme was used to control the batch cooling crystallization of potassium dihydrogen phosphate. The results demonstrate the application of the control policies for temperature to produce crystals of the desired average shape and size in different batch times. Thus, using the first principle modeling coupled to the developed trajectory tracking control, the proposed framework has the potential to be applied to industrial crystallization processes for shape control and to be extended to polymorph control investigations.
References:
[1] Eisenschmidt, H.; Bajcinca, N.; Sundmacher, K. (2016) Optimal Control of Crystal Shapes in Batch Crystallization Experiments by Growth-Dissolution Cycles. Crystal Growth & Design, v. 16, p. 3297-2803.
[2] Griffin, D. J., Grover, M. A., Kawajiri, Y., Rousseau, R. W. (2015) Mass-count plots for crystal size control. Chemical Engineering Science, v. 137, p. 338-351.
Designer Polymeric Nanoparticles to Help Heart Failure
Sara Ricchetti,*1 Marc L Sprouse,1 Rossana Terracciano,1 Daryl G Schulz2 Brian Bruckner,3,5 Steve Igo,3 Alessandro Grattoni,1,4,5 Carly Filgueira1,6
- Department of Nanomedicine, Houston Methodist Research Institute, Houston, TX 77030
- Pre-clinical Catheterization Core Lab, Houston Methodist Research Institute, Houston, TX 77030
- Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, TX 77030
- Department of Surgery, Houston Methodist Research Institute, Houston, TX 77030
- Department of Radiation Oncology, Houston Methodist Research Institute, Houston, TX 77030
- Department of Cardiovascular Surgery, Houston Methodist Research Institute, Houston, TX 77030
We report the synthesis and encapsulation of polymeric poly(d,l-lactide-co-glycolide) nanoparticles (PLGA-NPs) encapsulated with prostaglandins to aid in heart repair. PLGA-NPs allow us to stabilize our drug of interest, prevent systemic distribution, avoid adverse off-target side effects and sustain drug release. PLGA is biocompatible and biodegradable, and has demonstrated its safety and efficacy in humans for a number of medical device applications. In modifying the molecular weight of the PLGA polymer and the size of the particles we can also tailor and optimize the rate of prostaglandin release. Technologies used to characterize these drug loaded particles include optical and electron microscopies, zeta potential, and dynamic light scattering. Ultra performance liquid chromatography coupled with a Photodiode Array Detector (UPLC-PDA) was used to quantify the amount of prostaglandin loaded inside the particles as well as drug loss during synthesis. Accumulation of these drug-loaded PLGA-NPs in the pericardium may provide a novel means for delivery of a safe drug with both regenerative and protective benefits.
Granule Formation, Structure and Content Uniformity from Single Drop Impact on Heterogeneous Powder Beds
Tianxiang Gao* and Heather N. Emady, School for Engineering of Matter, Transport and Energy, Arizona State University
Wet granulation, which involves the interaction between particles and liquid, is a common industrial particle process. However, most of the research in this area has focused on the equipment setup and process parameters, while particle design involving the properties of the granular product is less studied. Within wet granulation, single drop granulation is the ideal case to control the granular product, since one liquid drop forms one granule. In this work, single drop granule formation on a static powder bed of pharmaceutical mixtures was studied to investigate the effects of hydrophobicity and primary particle size distribution on granule formation mechanisms, granule morphology, internal structure and the content homogeneity of active pharmaceutical ingredient (API). Binary mixtures consisting of microcrystalline cellulose (MCC) and acetaminophen (APAP) with two different particle sizes (coarse and fine) were prepared. Single drop granulation was performed on four combinations of MCC and APAP based on their particle sizes, to distinguish the effects of particle size and powder hydrophobicity. Besides the formation mechanisms and granule morphology, the powder bed packing structure was characterized by X-ray micro-CT and the API content uniformity was measured by UV-vis spectrometry. The effects of particle size and hydrophobicity of the raw powders on the granule formation mechanisms and granule properties were studied. It is believed that the primary particle size of the powder bed is more significant than the hydrophobicity in affecting the formation mechanism and granule internal structure, while both factors contribute to the content uniformity.
Predicting the Flow of Various Sizes and Moisture Contents of Glass Beads
Spandana Vajrala* and Heather Emady, School for Engineering of Matter, Transport and Energy, Arizona State University
Whether it is pneumatic conveying, die filling in a tablet press, or storage in hoppers, powders will be subjected to some level of stress consolidation during their handling, affecting the flow of these materials. Flow issues are likely to occur over a wide range of particle-scale parameters like particle size, particle size distribution (PSD), particle shape and moisture level. For effective product development and process design, it is important to study the flowability of granular materials and develop scale-up equations which can be used on an industrial scale. The present work investigated the effects of particle sizes between 5 – 600 microns and moisture levels from 0 – 20% on the flowability and shear properties of silica beads using the Freeman FT4 Rheometer. A mathematical model in terms of a flowability descriptor called the flow function (FF) was developed, based on the material’s yield point. The yield point for various particle size distributions and moisture levels was evaluated using a shear cell test. The FF for dry glass beads increased with particle size, following a linear relationship, as expected. On the other hand, the flow function for wet glass beads followed a power law relationship, where FF decreased with increasing moisture content. However, as the moisture level reached 20%, the flow function value escalated again due to supersaturation. The linear and power functions were combined to develop an empirical relation, which can be used to predict the flowability of glass beads, based on the particle size and moisture levels up to 20%.