Analytical Tools Integrated in Continuous-Flow Reactors: Which One for What?

Ultrasound-Assisted Microcontinuous Process Facilitates the Selective Deuteration of Steroid Hormones

Constructing deuterated molecules efficiently and practically has been a long-standing challenge. Deuterated steroid hormones are essential for medical research and drug metabolism studies and are thus in high demand; mild and selective methods for the deuteration of steroid hormones have remained unexplored. Herein, we demonstrate a practical and efficient approach to synthesize 12 deuterated steroid hormones with up to 98% selectivity and 99% d-incorporation under an ultrasound-assisted microcontinuous process. Optical rotation experiments confirm that steroid hormones configurations are preserved during the H/D exchange reaction. Our protocol enables rapid, inexpensive, and sustainable gram-scale synthesis, facilitated by the reuse of deuterated solvents via molecular distillation technology. Applying synthetic deuterated steroid hormones as mass spectrometry standards, six steroid hormones in metabolites are accurately analyzed from Frozen Human Plasma-1950 sample. Overall, this work has successfully demonstrated the application of ultrasound assisted microcontinuous processing in enhancing H/D exchange reactions.

Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning

The discovery of the optimal conditions for chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically, the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and through the design of experiments where reaction variables are modified one at a time to find the optimal conditions for a specific reaction outcome. Recently, a paradigm change in chemical reaction optimization has been enabled by advances in lab automation and the introduction of machine learning algorithms. Therein, multiple reaction variables can be synchronously optimized to obtain the optimal reaction conditions, requiring a shorter experimentation time and minimal human intervention. Herein, we review the currently used state-of-the-art high-throughput automated chemical reaction platforms and machine learning algorithms that drive the optimization of chemical reactions, highlighting the limitations and future opportunities of this new field of research.

Simultaneous reaction- and analytical model building using dynamic flow experiments to accelerate process development

In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active pharmaceutical ingredients (APIs) has led to a paradigm shift towards data-rich process development. Conventional methodologies encompass prolonged timelines for the development of both a reaction model and analytical models. The development of both methods are often separated into different departments and can require an iterative optimization process. Addressing this issue, we introduce an innovative dual modeling approach, combining the development of a Process Analytical Technology (PAT) strategy with reaction optimization. This integrated approach is exemplified in diverse amidation reactions and the synthesis of the API benznidazole. The platform, characterized by a high degree of automation and minimal operator involvement, achieves PAT calibration through a "standard addition" approach. Dynamic experiments are executed to screen a broad process space and gather data for fitting kinetic parameters. Employing an open-source software program facilitates rapid kinetic parameter fitting and additional in silico optimization within minutes. This highly automated workflow not only expedites the understanding and optimization of chemical processes, but also holds significant promise for time and resource savings within the pharmaceutical industry.

Quantitative Online Monitoring of an Immobilized Enzymatic Network by Ion Mobility-Mass Spectrometry

The forward design of in vitro enzymatic reaction networks (ERNs) requires a detailed analysis of network kinetics and potentially hidden interactions between the substrates and enzymes. Although flow chemistry allows for a systematic exploration of how the networks adapt to continuously changing conditions, the analysis of the reaction products is often a bottleneck. Here, we report on the interface between a continuous stirred-tank reactor, in which an immobilized enzymatic network made of 12 enzymes is compartmentalized, and an ion mobility-mass spectrometer. Feeding uniformly 13C-labeled inputs to the enzymatic network generates all isotopically labeled reaction intermediates and products, which are individually detected by ion mobility-mass spectrometry (IMS-MS) based on their mass-to-charge ratios and inverse ion mobilities. The metabolic flux can be continuously and quantitatively monitored by diluting the ERN output with nonlabeled standards of known concentrations. The real-time quantitative data obtained by IMS-MS are then harnessed to train a model of network kinetics, which proves sufficiently predictive to control the ERN output after a single optimally designed experiment. The high resolution of the time-course data provided by this approach is an important stepping stone to design and control sizable and intricate ERNs.

A Slug Flow Platform with Multiple Process Analytics Facilitates Flexible Reaction Optimization

Flow processing offers many opportunities to optimize reactions in a rapid and automated manner, yet often requires relatively large quantities of input materials. To combat this, the use of a flexible slug flow reactor, equipped with two analytical instruments, for low-volume optimization experiments are reported. A Buchwald-Hartwig amination toward the drug olanzapine, with 6 independent optimizable variables, is optimized using three different automated approaches: self-optimization, design of experiments, and kinetic modeling. These approaches are complementary and provide differing information on the reaction: pareto optimal operating points, response surface models, and mechanistic models, respectively. The results are achieved using <10% of the material that would be required for standard flow operation. Finally, a chemometric model is built utilizing automated data handling and three subsequent validation experiments demonstrate good agreement between the slug flow reactor and a standard (larger scale) flow reactor.

Multiphasic Continuous-Flow Reactors for Handling Gaseous Reagents in Organic Synthesis: Enhancing Efficiency and Safety in Chemical Processes

The use of reactive gaseous reagents for the production of active pharmaceutical ingredients (APIs) remains a scientific challenge due to safety and efficiency limitations. The implementation of continuous-flow reactors has resulted in rapid development of gas-handling technology because of several advantages such as increased interfacial area, improved mass- and heat transfer, and seamless scale-up. This technology enables shorter and more atom-economic synthesis routes for the production of pharmaceutical compounds. Herein, we provide an overview of literature from 2016 onwards in the development of gas-handling continuous-flow technology as well as the use of gases in functionalization of APIs.

Quid Pro Flow

How do you get into flow? We trained in flow chemistry during postdoctoral research and are now applying it in new areas: materials chemistry, crystallization, and supramolecular synthesis. Typically, when researchers think of "flow", they are considering predominantly liquid-based organic synthesis; application to other disciplines comes with its own challenges. In this Perspective, we highlight why we use and champion flow technologies in our fields, summarize some of the questions we encounter when discussing entry into flow research, and suggest steps to make the transition into the field, emphasizing that communication and collaboration between disciplines is key.

Will the next generation of chemical plants be in miniaturized flow reactors?

For decades, a production paradigm based on centralized, stepwise, large scale processes has dominated the chemical industry horizon. While effective to meet an ever increasing demand for high value-added chemicals, the so-called macroscopic batch reactors are also associated with inherent weaknesses and threats; some of the most obvious ones were tragically illustrated over the past decades with major industrial disasters and impactful disruptions of advanced chemical supplies. The COVID pandemic has further emphasized that a change in paradigm was necessary to sustain chemical production with an increased safety, reliable supply chains and adaptable productivities. More than a decade of research and technology development has led to alternative and effective chemical processes relying on miniaturised flow reactors (a.k.a. micro and mesofluidic reactors). Such miniaturised reactors bear the potential to solve safety concerns and to improve the reliability of chemical supply chains. Will they initiate a new paradigm for a more localized, safe and reliable chemical production?

In-line Multidimensional NMR Monitoring of Photochemical Flow Reactions

This work demonstrates the in-line monitoring of a flow photochemical reaction using 1D and ultrafast 2D NMR methods at high magnetic field. The reaction mixture exiting the flow reactor is flown through the NMR spectrometer and directly analyzed. In the case of simple substrates, suitable information can be obtained through 1D ¹ H spectra, but for molecules of higher complexity the use of 2D experiments is key to address signal overlaps and assignment issues. Here we show the usefulness of ultrafast 2D COSY experiments acquired in 70 s or less, for the in-line monitoring of photochemical reactions, and the possibility to obtain reliable quantitative information. This is a powerful framework to, for example, efficiently screen reaction conditions.

Non-fouling flow reactors for nanomaterial synthesis

This review provides a holistic description of flow reactor fouling for wet-chemical nanomaterial syntheses. Fouling origins and consequences are discussed together with the variety of flow reactors for its prevention.

Heterogeneous metallaphotoredox catalysis in a continuous-flow packed-bed reactor

Metallaphotoredox catalysis is a powerful and versatile synthetic platform that enables cross-couplings under mild conditions without the need for noble metals. Its growing adoption in drug discovery has translated into an increased interest in sustainable and scalable reaction conditions. Here, we report a continuous-flow approach to metallaphotoredox catalysis using a heterogeneous catalyst that combines the function of a photo- and a nickel catalyst in a single material. The catalyst is embedded in a packed-bed reactor to combine reaction and (catalyst) separation in one step. The use of a packed bed simplifies the translation of optimized batch reaction conditions to continuous flow, as the only components present in the reaction mixture are the substrate and a base. The metallaphotoredox cross-coupling of sulfinates with aryl halides was used as a model system. The catalyst was shown to be stable, with a very low decrease of the yield (≈1% per day) during a continuous experiment over seven days, and to be effective for C–O arylations when carboxylic acids are used as nucleophile instead of sulfinates.