Journal of Flow Chemistry最新文献

A straightforward “one-column” continuous flow method of Grignard generation and reaction was successfully developed. The diverse mixtures of aryl- or alkyl- halides and electrophiles were flowed through an activited magnesium packed-bed column, delivering a series of ketones, secondary alcohols, tertiary alcohols, esters, amides, and sulfinamides immediately in moderate to good yields. By combining Grignard generation and reaction into one step and avoiding the separate preparation and storage of Grignard reagents, this practical and efficient protocol dramatically enhanced the safety of operation and provided a convenient access for Grignard reactions, compared with traditional batch process. The continuous flow synthesis of Grignard generation and reaction is carried out in a magnesium packed-bed column successfully.The target product is provided in moderate to good yields within 6.0 min. This protocol with preferable controllability, good selectivity, and safety extremely simplified operational procedure.

For reliable supervision in multiphase processes, the droplet size represents a critical quality attribute and needs to be monitored. A promising approach is the use of smart image flow sensors since optical measurement is the most commonly used technique for droplet size distribution determination. For this, two different AI-based object detection methods, Mask RCNN and YOLOv4, are compared regarding their accuracy and their applicability to an emulsification flow process. Iterative optimization steps, including data diversification and adaption of training parameters, enable the models to achieve robust detection performance across varying image qualities and compositions. YOLOv4 shows better detection performances and more accurate results which leads to a wider application window than Mask RCNN in determining droplet sizes in emulsification processes. The final droplet detection model YOLOv4 with Hough Circle (HC) for feature extraction determines reliable droplet sizes across diverse datasets of liquid-liquid flow systems (disperse phase content 1–15 vol.-%, droplet size range 5–150 μm). Evaluating the adjustment of Confidence Scores (CS) ensures statistical representation of even smaller droplets. The droplet detection performance of the final YOLOv4 model is compared with a manual image processing method to validate the model in general as well as its accuracy and reliability. Since YOLOv4 in combination with Hough Circle (HC) shows an accurate and robust detection and size determination, it is applicable for online monitoring and characterization of various liquid-liquid flow processes.

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Experimental investigations into acoustic cavitation and ultrasound-assited emulsification process between highly viscous liquids were systematically conducted in a laboratory-built ultrasonic microreactor. Under ultrasound irradiation, four cavitation modes were observed simultaneously in soybean oil, including volume, shape, transient collapse and cavitation clouds. Influenced by the intense oscillation of cavitation bubbles, emulsification between viscous liquids was initiated through a dispersion and migration mode. The effects of varying parameters, such as input power, residence time, channel size, HLB value, surfactant concentration and volume ratio between aqueous and oil phase, on the size and polydispersity of prepared emulsion were investigated using water-soybean oil two-phase system as a model. The emulsion size was reduced to 75.60 nm through optimization of experimental parameters. Based on these findings, the ultrasonic microreactor was successfully employed in the preparation of Vitamin E-enriched nano-emulsions. A fine emulsion with low average size (47.69 nm) and good storage stability (60 days) was prepared within 2 min, further indicating the potential application of ultrasonic microreactor in the beverage and pharmaceutical industries.

The separation of silybin A (SilA) and B (SilB) diastereomers in optically pure compounds is challenging due to their very similar physical and chemical properties. However, such separation is crucial for evaluating the biological activity of the diasteroisomers SilA and SilB, which show very different performance in pharmacological applications like treating prostate cancer, liver diseases, and Alzheimer’s disease. The most common isolation method is based on high-performance liquid chromatography, but it is slow and has a yield in pure SilB of hundreds of milligrams per day. An alternative chemo-enzymatic separation method, utilizing an immobilized lipase CALB catalyst to stereoselectively acetylate silybin B (1b), offers advantages in terms of higher productivity, selectivity, and scalability, particularly when applied in flow reactors. This study delves into the kinetics of Sil acetylation catalyzed by Novozym 435 in a continuous flow milli-reactor, investigated at various temperatures, volumetric flow rates, and Sil initial concentrations. It is noteworthy that, at the current state of the art, there is a lack of kinetic studies on this reaction, emphasizing the novelty and significance of this work. The kinetic and fluid dynamic parameters were estimated using a non-linear regression analysis of experimental data. The examined reaction showed a null apparent activation energy, explaining the temperature insensitivity of the final acetylated silybin B (1b) concentration. Furthermore, the decrease in steady-state concentrations of the acetylated products with increasing volumetric flow rates indicated that the reaction was occurring in a kinetic regime. Interestingly, a maximum starting Sil concentration was identified, above which there was no favorable impact on conversion.

In the continuous struggle for improvements in laboratory processes, flow synthesis has been widely used for being safer, more reproducible, as for improving yields and scalability. Therefore, flow ozonolysis has become a turning point as flow reactors provides a much safer work environment and reactions can now be produced at industrial scales. In this review we would discuss several reactors used in flow ozonolysis and its importance for the safety of the ozonolysis process.

Organic azides are widely used in organic synthesis. Continuous flow processing can be used to bypass their isolation, and can therefore be useful in mitigating the hazards associated with these potentially toxic and explosive reagents. Nonaflyl azide has been reported as an effective, bench-stable, and relatively safe diazo transfer reagent that can be useful in the preparation of azides from amines and so avoid the use of alkyl halides. Here we demonstrate the synthesis and purification of nonaflyl azide in continuous flow with isolation of the neat, pure reagent by membrane filtration. The neat reagent was used in the preparation of organic azides from primary amines, and then applied to the synthesis of triazoles. A variety of triazoles, including the antiseizure drug Rufinamide, were prepared from primary amines and alkynes via the CuAAC click reaction in a semi-batch parallel array without isolation of alkyl azide intermediates. A telescoped two-stage continuous flow process was also designed and demonstrated to form triazoles via the same CuAAC reaction, which avoids the handling of the intermediate reactive azides.

In this paper, we demonstrate the use of machine learning to optimize the continuous flow process of a crucial intermediate in the production of Nemonoxacin. Our focus is to achieve the good yield and enantioselectivity in the construction of chiral methyl group utilize the initial 29 experimental datasets and consider six important variables. Employing Single-Objective Bayesian optimization (SOBO), we achieved an impressive predicted yield of up to 89.7%, which is consistent with the experimental results, with a yield of 89.5%. Additionally, A Multi-Objective Bayesian Optimization (MOBO) algorithm, namely qNEHVI, to strike a balance between yield and enantioselectivity in the continuous flow system is applied. The algorithm’s prediction, with a yield of 81.8% and enantioselectivity of 97.85%, was experimentally validated, yielding 83.8% and 97.2%, respectively. This study effectively demonstrates that Bayesian optimization is a powerful tool for optimizing the continuous process in the production of active pharmaceutical ingredients (APIs).

Abstract

Pharmaceutical industry is challenged by the rising development costs, strict regulatory and environmental requirements all while racing to deliver complex molecules to market. The need to be the first-in-class brings about shorter lifetime to the launched products in favor of better functioning followers. In addition, a shift from large volume blockbusters towards small volume production of complex molecules presents a unique opportunity to challenge the status quo in pharmaceutical manufacturing. Traditional batch manufacturing, while foundational, presents hurdles in scaling and efficiency, particularly for demanding reactions. Continuous manufacturing has emerged as a promising alternative, delivering better control and uniformity of operating conditions, mirroring the efficiencies found in small-scale batch reactors. However, continuous manufacturing is not universally applicable. As a solution, a combination of the two into hybrid manufacturing processes, appears to fill this gap effectively. While the concept of hybrid manufacturing is not new, the current perspective adds an additional angle to the integration of both technologies. Authors propose to sustain the continuity of the operation for batch mode processes by decreasing the reactor size and increasing the level of automation. Furthermore, modular fabrication of smaller-footprint technological platforms is expected to synergize other advancements in the field, such as digitalization, automation, and standardization. As a result, a leap towards the implementation of advanced manufacturing to drive sustainability in pharmaceutical industry is more tangible than ever.

The Pinnick oxidation, due to its tolerance for sensitive functional groups, is widely used in the process of oxidizing α,β-unsaturated aldehydes to corresponding carboxylic acids. The reaction reagents typically include sodium chlorite, buffer salts, and a scavenger. However, the controllability of Pinnick oxidation in the batch reaction process is poor due to the inherent limitations of the reactor’s performance. This leads to potential safety risks and necessitates the reaction to proceed slowly under conditions of low temperature and low concentration. In this work, we introduced a new continuous micro-reaction process to intensify the Pinnick oxidation. The water-soluble crotonic acid was selected as a typical object of study. Through the study of reaction parameters and the construction of a micro-reaction system, efficient continuous process was achieved under high-temperature and high-pressure conditions for the first time. Compared to the batch process, the reaction benefited from the superheated condition resulting in a significant acceleration of the reaction rate, efficient gas–liquid interphase mass transfer allowing for effective utilization of the generated chlorine dioxide, and the inherent safety of the microreactor enabling an increase in reaction concentration. In addition, the buffer salts used in the Pinnick oxidation has been successfully replaced by hydrochloric acid and applied to the continuous flow. This work shows the tremendous potential of microreactors in utilizing harsh reaction conditions to achieve process intensification.

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Emulsification processes are often found in the process industry and their evaluation is crucial for product quality and safety. Numerous methods exist to analyze critical quality attributes (CQA) such as the droplet sizes and droplet size distribution (DSD) of an emulsification process. During the emulsification process, the optical process accessibility may be limited due to high disperse phase content of liquid-liquid systems. To overcome this challenge, a modular, optical measurement flow cell is presented to widen the application window of optical methods in emulsification processes. In this contribution, the channel geometry is subject of optimization to modify the flow characteristics and produce high optical quality. In terms of rapid prototyping, an iterative optimization procedure via SLA-3D printing was used to increase operability. The results demonstrated that the flow cell resulting from the optimization procedure provides a broad observation window for droplet detection.

Graphical abstract