Dynamic agglomeration profiling during the drying phase in an agitated filter dyer: Parametric investigation and regime map studies

Elaboration and Characterization of Natural Deep Eutectic Solvents (NADESs): Application in the Extraction of Phenolic Compounds from pitaya

In this paper, natural deep eutectic solvents (NADESs) with lactic acid, glycine, ammonium acetate, sodium acetate, and choline chloride were prepared with and without the addition of water. NADES formation was evaluated using FTIR and Raman, where hydrogen bonds were identified between the hydroxyl group of lactic acid and the amino and carboxyl groups of glycine. Acetate and ammonium ions were also identified as forming bonds with lactic acid. The addition of water did not cause changes in the vibrational modes of the FTIR and Raman spectra but contributed to a reduction in NADES viscosity and density. Viscosity ranged from 0.335 to 0.017 Pa s^-1, and density ranged from 1.159 to 0.785 g mL^-1. The best results for the extraction of phenolic compounds from pitaya (dragon fruit) were achieved with an organic solvent (450. 41 mg 100 g^-1 dry bases-db) in comparison to NADESs lactic acid:glycine (193.18 mg 100 g^-1 db) and lactic acid:ammonium acetate (186.08 mg 100 g^-1 db). The antioxidant activity of the extracts obtained with the NADESs was not statistically different from that of the extract obtained with organic solvents.

Breakage Assessment of Lath-Like Crystals in a Novel Laboratory-Scale Agitated Filter Bed Dryer

Agitated filter bed dryer is often the equipment of choice in the pharmaceutical industry for the isolation of potent active pharmaceutical ingredients (API) from the mother liquor and subsequent drying through intermittent agitation. The use of an impeller to promote homogeneous drying could lead to undesirable size reduction of the crystal product due to shear deformation induced by the impeller blades during agitation, potentially causing off-specification product and further downstream processing issues. An evaluation of the breakage propensity of crystals during the initial development stage is therefore critical. A new versatile scale-down agitated filter bed dryer (AFBD) has been developed for this purpose. Carbamazepine dihydrate crystals that are prone to breakage have been used as model particles. The extent of particle breakage as a function of impeller rotational speed, size of clearance between the impeller and containing walls and base, and solvent content has been evaluated. A transition of breakage behaviour is observed, where carbamazepine dihydrate crystals undergo fragmentation first along the crystallographic plane [00l]. As the crystals become smaller and more equant, the breakage pattern switches to chipping. Unbound solvent content has a strong influence on the breakage, as particles break more readily at high solvent contents. The laboratory-scale instrument developed here provides a tool for comparative assessment of the propensity of particle attrition under agitated filter bed drying conditions.

A Novel Computational Approach Coupled with Machine Learning to Predict the Extent of Agglomeration in Particulate Processes

Solid particle agglomeration is a prevalent phenomenon in various processes across the chemical, food, and pharmaceutical industries. In pharmaceutical manufacturing, agglomeration is both desired in unit operations like wet granulation and undesired in unit operations such as agitated filter drying of highly potent active pharmaceutical ingredients (API). Agglomeration needs to be controlled for optimal physical properties of the API powder. Even after decades of work in the field, there is still very limited understanding of how to quantify, predict, and control the extent of agglomeration, owing to the complex interaction between the solvent and the solid particles and stochasticity imparted by mixing. Furthermore, a large size of industrial scale particulate process systems makes it computationally intractable. To overcome these challenges, we present a novel theory and computational methodology to predict the agglomeration extent by coupling the experimental measurements of agglomeration risk zone or "sticky zone" with discrete element method. The proposed model shows good agreement with experiments. Further, a machine learning model was built to predict agglomeration extent as a function of input variables, such as material properties and processing conditions, in order to build a digital twin of the unit operation. While the focus of the present study is the agglomeration of particles during industrial drying processes, the proposed methodology can be readily applied to numerous other particulate processes where agglomeration is either desired or undesired.

A Novel Integrated Workflow for Isolation Solvent Selection Using Prediction and Modeling

A predictive tool was developed to aid process design and to rationally select optimal solvents for isolation of active pharmaceutical ingredients. The objective was to minimize the experimental work required to design a purification process by (i) starting from a rationally selected crystallization solvent based on maximizing yield and minimizing solvent consumption (with the constraint of maintaining a suspension density which allows crystal suspension); (ii) for the crystallization solvent identified from step 1, a list of potential isolation solvents (selected based on a series of constraints) is ranked, based on thermodynamic consideration of yield and predicted purity using a mass balance model; and (iii) the most promising of the predicted combinations is verified experimentally, and the process conditions are adjusted to maximize impurity removal and maximize yield, taking into account mass transport and kinetic considerations. Here, we present a solvent selection workflow based on logical solvent ranking supported by solubility predictions, coupled with digital tools to transfer material property information between operations to predict the optimal purification strategy. This approach addresses isolation, preserving the particle attributes generated during crystallization, taking account of the risks of product precipitation and particle dissolution during washing, and the selection of solvents, which are favorable for drying.

Understanding API Static Drying with Hot Gas Flow: Design and Test of a Drying Rig Prototype and Drying Modeling Development

Developing a continuous isolation process to produce a pure, dry, free-flowing active pharmaceutical ingredient (API) is the final barrier to the implementation of continuous end-to-end pharmaceutical manufacturing. Recent work has led to the development of continuous filtration and washing prototypes for pharmaceutical process development and small-scale manufacture. Here, we address the challenge of static drying of a solvent-wet crystalline API in a fixed bed to facilitate the design of a continuous filter dryer for pharmaceutical development, without excessive particle breakage or the formation of interparticle bridges leading to lump formation. We demonstrate the feasibility of drying small batches on a time scale suitable for continuous manufacturing, complemented by the development of a drying model that provides a design tool for process development. We also evaluate the impact of alternative washing and drying approaches on particle agglomeration. We conclude that our approach yields effective technology, with a performance that is amenable to predictive modeling.

Developing a Batch Isolation Procedure and Running It in an Automated Semicontinuous Unit: AWL CFD25 Case Study

A key challenge during the transition from laboratory/small batch to continuous manufacturing is the development of a process strategy that can easily be adopted for a larger batch/continuous process. Industrial practice is to develop the isolation strategy for a new drug/process in batch using the design of experiment (DoE) approach to determine the best isolation conditions and then transfer the isolation parameters selected to a large batch equipment/continuous isolation process. This stage requires a series of extra investigations to evaluate the effect of different equipment geometry or even the adaptation of the parameters selected to a different isolation mechanism (e.g., from dead end to cross flow filtration) with a consequent increase of R&D cost and time along with an increase in material consumption. The CFD25 is an isolation device used in the first instance to develop an isolation strategy in batch (optimization mode) using a screening DoE approach and to then verify the transferability of the strategy to a semicontinuous process (production mode). A d-optimal screening DoE was used to determine the effect of varying the input slurry. Properties such as solid loading, particle size distribution, and crystallization solvent were investigated to determine their impact on the filtration and washing performance and the characteristics of the dry isolated product. A series of crystallization (ethanol, isopropanol, and 3-methylbutan-1-ol) and wash solvents (n-heptane, isopropyl acetate and n-dodcane) were used for the process. To mimic a real isolation process, paracetamol-related impurities, acetanilide and metacetamol, were dissolved in the mother liquor. The selected batch isolation strategy was used for the semicontinuous isolation run. Throughput and filtration parameters, such as cake resistance and flow rate, cake residual liquid content and composition, cake purity, particle–particle aggregation, and extent and strength of agglomerates, were measured to evaluate the consistency of the isolated product produced during a continuous experiment and compared with the isolated product properties obtained during the batch process development. Overall, the CFD25 is a versatile tool which allows both new chemical entity process development in batch and the production of the active pharmaceutical ingredient in semicontinuous mode using the same process parameters without changing equipment. The isolated product properties gained during the semicontinuous run are overall comparable between samples. The residual solvent content and composition differs between some samples due to filter plate blockage. In general, the mean properties obtained during semicontinuous running are comparable with the product properties simulated using the DoE.