Science acceleration and accessibility with self-driving labs

In the evolving landscape of scientific research, the complexity of global challenges demands innovative approaches to experimental planning and execution. Self-Driving Laboratories (SDLs) automate experimental tasks in chemical and materials sciences and the design and selection of experiments to optimize research processes and reduce material usage. This perspective explores improving access to SDLs via centralized facilities and distributed networks. We discuss the technical and collaborative challenges in realizing SDLs' potential to enhance human-machine and human-human collaboration, ultimately fostering a more inclusive research community and facilitating previously untenable research projects.

Recent Developments in Automated Reactors for Plasmonic Nanoparticles

Automated reactors are transforming nanomaterial synthesis by enabling precise, multistep control over morphology and reaction pathways. This review discusses recent advancements in robotic batch and continuous-flow platforms, highlighting their role in expanding chemical space exploration and adaptive manufacturing. Despite progress, challenges remain in integrating automation for complex, multistep syntheses due to the intricate interplay of chemical and physical processes. Emerging process analytical technologies and advanced control software are enhancing real-time monitoring, adaptive feedback loops, and self-optimizing synthesis strategies. We categorize these developments, emphasizing their impact on plasmonic nanomaterial fabrication and outlining future directions for autonomous synthesis.

Continuous Flow Synthesis of Nitrofuran Pharmaceuticals Using Acetyl Nitrate

Nitrofurfural is a key building block for the synthesis of antimicrobial nitrofurans as active pharmaceutical ingredients. Its synthesis involves the nitration of furfural, a substrate derived from biobased resources. However, furfural has a delicate heteroaromatic backbone. Typical nitrations involve harsh reaction conditions, which often compromise this structure, resulting in poor reproducibility and low yields. Although acetyl nitrate, a mild nitrating agent, is suitable for this task, major deterrents remain. First, its conventional preparation method involves conditions that are not compatible with furfural. Second, significant safety concerns are associated with the unstable and explosive nature of acetyl nitrate. These critical issues are addressed herein. A safe and robust continuous flow platform featuring in situ generation of acetyl nitrate for the nitration of furfural to nitrofurfural is reported. The high level of integration and automation enables remote process operation by a single operator. Key furfural-based pharmaceutical intermediates were synthesized with favorable metrics and high reproducibility. The efficiency of this flow platform is demonstrated using a selection of best-selling nitrofuran pharmaceuticals (nifuroxazide, nifurtimox, nitrofurantoin, and nitrofural), which were obtained with excellent isolated yields in under five minutes.

Sustainability and Techno-Economic Assessment of Batch and Flow Chemistry in Seven Industrial Pharmaceutical Processes

The synthesis of active pharmaceutical ingredients (APIs) is commonly perceived as more efficient when performed using continuous-flow methods, whereas batch processes are often seen as less favorable due to their limitations in yield, heat and mass transfer, and safety. This perception largely stems from existing studies that focus on green metrics such as the E-factor and yield. However, a comprehensive comparison of batch and flow processes through full techno-economic analyses (TEA) and life-cycle assessments (LCA) remains underexplored, leaving key aspects of their environmental and economic impacts inadequately assessed. This work addresses this gap by presenting a detailed comparison of batch and flow syntheses of seven industrially relevant APIs, including amitriptyline hydrochloride, tamoxifen, zolpidem, rufinamide, artesunate, ibuprofen, and phenibut. Eleven environmental impact categories within the framework of nine planetary boundaries were assessed, and the study also included an evaluation of capital and operating costs for both production methods. The results demonstrated that, on average, continuous-flow processes are significantly more sustainable with improvements in energy efficiency, water consumption, and waste reduction. Flow processes also show a marked reduction in carbon emissions and up to a 97% reduction in energy consumption, highlighting their potential for greener API manufacturing. Despite these advantages, the study identified areas where the continuous-flow technology requires further development. Specifically, manufacturing certain APIs in flow show lower-than-average improvements in operating expenditure and land system changes, the latter being directly correlated with the consumption of organic solvents, that can be comparable to or even higher than in batch. These challenges highlight the need for further optimization of flow processes to fully realize their potential in API production.

Visible Light-Promoted Deracemization of α-Amino Aldehyde by Synergistic Chiral Primary Amine and Hypervalent Iodine Catalysis

α-Amino aldehydes, as versatile chiral synthons, are easily racemized under normal acid or base conditions, seriously limiting their synthetic potentials. We report herein an effective deracemization of α-amino aldehydes by a synergistic chiral primary amine and hypervalent iodine catalysis under visible light. The developed catalytic system allows for the on-demand production of α-Boc- or Cbz-protected amino aldehydes with high enantioselectivity. Mechanistic studies verified a photochemical Z-E isomerization mechanism that drives the deracemization process.

Can Ultrasound Replace Seeding in Flow Reactive Crystallization of an Aromatic Amine?

Continuous crystallization has gained substantial interest due to its high product reproducibility, high labor efficiency, and low capital and production costs. Continuous seeding is preferable and often even required in the application of pharmaceuticals, which presents a bottleneck in continuous crystallization. This work proposes to apply ultrasound for continuous in situ seeding in the continuous reactive crystallization of an aromatic amine. Flow crystallization experiments with both ultrasound and conventionally prepared seeds were conducted. It was found that sonication initiated nucleation and continuously produced crystals in a stable manner. The nucleation rate could be controlled by adjusting the sonication power, highlighting the advantages of the sonicated seed generation strategy. Experiments under different flow conditions demonstrated that a higher flow rate combined with an appropriate sonication power was favorable for robust particle quality, reduced likelihood of clogging, and better reproducibility. Compared with the conventional addition of seed crystals, sonication-induced crystallization achieved higher yields and produced products with a narrow and unimodal size distribution. All sonicated experiments exhibited high robustness, indicating the feasibility and reliability of this method as a replacement for conventional seeding techniques in the continuous reactive crystallization of the studied compound. In summary, using ultrasound for continuous in situ seeding of the aromatic amine offers unique advantages in process robustness and product quality control, providing a promising strategy for continuous crystallization of similar systems.

Chemical Modification of Insulin Using Flow Chemistry

Chemical modification of proteins is of growing importance to generate new molecular probes for chemical biology and for the development of new biopharmaceuticals. For example, two approved, long-acting insulin variants are lipidated at the LysB29 side-chain. Acylations of proteins have so far been performed in batch-mode. Here we describe the use of flow chemistry for site-selective acylation of a small protein, insulin. To the best of our knowledge this is the first report on flow chemistry for chemical modification of insulin. The first step was to develop reaction conditions for acylation of Lys B29 that gave a soluble mixture and thus was compatible with flow chemistry in a microreactor; this included selection of a soluble base. Secondly, the conditions, such as reagent ratios and flow rate were optimized. Third, the use of these conditions for the acylation with a wide range of acids was demonstrated. Finally, Boc-protected insulins were synthesized. Insulin remained stable towards these flow chemistry conditions. This use of flow chemistry for the chemical modification of insulin opens the prospect of producing chemically modified biopharmaceuticals by flow chemistry with fewer byproducts.

Self-Driving Laboratories for Chemistry and Materials Science

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

Automation and machine learning augmented by large language models in a catalysis study

Recent advancements in artificial intelligence and automation are transforming catalyst discovery and design from traditional trial-and-error manual mode into intelligent, high-throughput digital methodologies. This transformation is driven by four key components, including high-throughput information extraction, automated robotic experimentation, real-time feedback for iterative optimization, and interpretable machine learning for generating new knowledge. These innovations have given rise to the development of self-driving labs and significantly accelerated materials research. Over the past two years, the emergence of large language models (LLMs) has added a new dimension to this field, providing unprecedented flexibility in information integration, decision-making, and interacting with human researchers. This review explores how LLMs are reshaping catalyst design, heralding a revolutionary change in the fields.

Advances in aldo-keto reductases immobilization for biocatalytic synthesis of chiral alcohols

Chiral alcohols are essential building blocks of numerous pharmaceuticals and fine chemicals. Aldo-keto reductases (AKRs) constitute a superfamily of oxidoreductases that catalyze the reduction of aldehydes and ketones to their corresponding alcohols using NAD(P)H as a coenzyme. Knowledge about the crucial roles of AKRs immobilization in the biocatalytic synthesis of chiral alcohols is expanding. Herein, we reviewed the characteristics of various AKRs immobilization approaches, the applications of different immobilization materials, and the prospects of continuous flow bioreactor construction by employing these immobilized biocatalysts for synthesizing chiral alcohols. Finally, the opportunities and ongoing challenges for AKR immobilization are discussed and the outlook for this emerging area is analyzed.

Droplet Microfluidic Devices: Working Principles, Fabrication Methods, and Scale-Up Applications

Compared with the conventional emulsification method, droplets generated within microfluidic devices exhibit distinct advantages such as precise control of fluids, exceptional monodispersity, uniform morphology, flexible manipulation, and narrow size distribution. These inherent benefits, including intrinsic safety, excellent heat and mass transfer capabilities, and large surface-to-volume ratio, have led to the widespread applications of droplet-based microfluidics across diverse fields, encompassing chemical engineering, particle synthesis, biological detection, diagnostics, emulsion preparation, and pharmaceuticals. However, despite its promising potential for versatile applications, the practical utilization of this technology in commercial and industrial is extremely limited to the inherently low production rates achievable within a single microchannel. Over the past two decades, droplet-based microfluidics has evolved significantly, considerably transitioning from a proof-of-concept stage to industrialization. And now there is a growing trend towards translating academic research into commercial and industrial applications, primarily driven by the burgeoning demands of various fields. This paper comprehensively reviews recent advancements in droplet-based microfluidics, covering the fundamental working principles and the critical aspect of scale-up integration from working principles to scale-up integration. Based on the existing scale-up strategies, the paper also outlines the future research directions, identifies the potential opportunities, and addresses the typical unsolved challenges.

A robotic system for automated chemical synthesis of therapeutic agents

The development of novel compounds for tissue-specific targeting and imaging is often impeded by a lack of lead compounds and the availability of reliable chemistry. Automated chemical synthesis systems provide a potential solution by enabling reliable, repeated access to large compound libraries for screening. Here we report an integrated solid-phase combinatorial chemistry system created using commercial and customized robots. Our goal is to optimize reaction parameters, such as varying temperature, shaking, microwave irradiation, aspirating and dispensing large-sized solid beads, and handling different washing solvents for separation and purification. This automated system accommodates diverse chemical reactions such as peptide synthesis and conventional coupling reactions. To confirm its functionality and reproducibility, 20 nerve-specific contrast agents for biomedical imaging were systematically and repeatedly synthesized and compared to other nerve-targeted agents using molecular fingerprinting and Uniform Manifold Approximation and Projection, which lays the foundation for creating reliable and reproductive chemical libraries in bioimaging and nanomedicine.

Wall-Immobilized Biocatalyst vs. Packed Bed in Miniaturized Continuous Reactors: Performances and Scale-Up

Sustainable biocatalysis syntheses have gained considerable popularity over the years. However, further optimizations - notably to reduce costs - are required if the methods are to be successfully deployed in a range of areas. As part of this drive, various enzyme immobilization strategies have been studied, alongside process intensification from batch to continuous production. The flow bioreactor portfolio mainly ranges between packed bed reactors and wall-immobilized enzyme miniaturized reactors. Because of their simplicity, packed bed reactors are the most frequently encountered at lab-scale. However, at industrial scale, the growing pressure drop induced by the increase in equipment size hampers their implementation for some applications. Wall-immobilized miniaturized reactors require less pumping power, but a new problem arises due to their reduced enzyme-loading capacity. This review starts with a presentation of the current technology portfolio and a reminder of the metrics to be applied with flow bioreactors. Then, a benchmarking of the most recent relevant works is presented. The scale-up perspectives of the various options are presented in detail, highlighting key features of industrial requirements. One of the main objectives of this review is to clarify the strategies on which future study should center to maximize the performance of wall-immobilized enzyme reactors.

Cascade Sequence of Photooxygenation-Epoxidation for the Flow Synthesis of Epoxy Alcohols

A photooxygenation-epoxidation cascade sequence converting alkenes to epoxy alcohols was developed and evaluated in batch and continuous-flow systems. In the batch system, the undesired interactions between the photooxygenation and epoxidation catalysts resulted in suboptimal yields, whereas the fine control of reaction parameters in the flow system allowed the allyl hydroperoxides produced through photooxygenation of alkenes to be rapidly converted to epoxy alcohols in yields of up to 93%. The developed procedure allows one to avoid an important synthetic bottleneck, works well where traditional batch synthesis fails, and can be scaled up to meet the needs of industrial production, thus presenting a valuable addition to the toolbox of practicing organic chemists.

Deep learning-augmented T-junction droplet generation

Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.

Developing a Modular Continuous Drug Product Manufacturing System with Real Time Quality Assurance for Producing Pharmaceutical Mini-Tablets

The pharmaceutical industry has shown keen interest in developing small-scale modular manufacturing systems for producing medicinal products. These systems offer agile and flexible manufacturing, and are well-suited for use in situations requiring rapid production of drugs such as pandemics and humanitarian disasters. The creation of such systems requires the development of modular facilities for making solid oral drug products. In recent years, however, the development of such facilities has seen limited progress. This study presents a development of a prototype modular system that uses drop on demand (DoD) printing to produce personalized solid oral drug products. The system's operation is demonstrated for manufacturing mini-tablets, a category of pediatric drug products, in continuous and semi-batch modes. In this process, the DoD printer is used to generate molten formulation drops that are solidified into mini-tablets. These dosages are then extracted, washed and dried in a continuous filtration and drying unit which is integrated with the printer. Process monitoring tools are also incorporated in the system to track the critical quality attributes of the product and the critical process parameters of the manufacturing operation in real time. Future areas of innovation are also proposed to improve this prototype unit and to enable the development of advanced drug manufacturing systems based on this platform.

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.

Continuous flow reactions in the preparation of active pharmaceutical ingredients and fine chemicals

Herein, we present an overview of continuous flow chemistry, including photoflow and electroflow technologies in the preparation of active pharmaceutical ingredients (APIs) and fine chemical intermediates. Examples highlighting the benefits and challenges associated with continuous flow processes, mainly involving continuous thermal, photo- and electrochemical transformations, are drawn from the relevant literature, especially our experience and collaborations in this area, with emphasis on the synthesis and prospective scale-up.

Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry

Automation can transform productivity in research activities that use liquid handling, such as organic synthesis, but it has made less impact in materials laboratories, which require sample preparation steps and a range of solid-state characterization techniques. For example, powder X-ray diffraction (PXRD) is a key method in materials and pharmaceutical chemistry, but its end-to-end automation is challenging because it involves solid powder handling and sample processing. Here we present a fully autonomous solid-state workflow for PXRD experiments that can match or even surpass manual data quality, encompassing crystal growth, sample preparation, and automated data capture. The workflow involves 12 steps performed by a team of three multipurpose robots, illustrating the power of flexible, modular automation to integrate complex, multitask laboratories.

An integrated self-optimizing programmable chemical synthesis and reaction engine

Robotic platforms for chemistry are developing rapidly but most systems are not currently able to adapt to changing circumstances in real-time. We present a dynamically programmable system capable of making, optimizing, and discovering new molecules which utilizes seven sensors that continuously monitor the reaction. By developing a dynamic programming language, we demonstrate the 10-fold scale-up of a highly exothermic oxidation reaction, end point detection, as well as detecting critical hardware failures. We also show how the use of in-line spectroscopy such as HPLC, Raman, and NMR can be used for closed-loop optimization of reactions, exemplified using Van Leusen oxazole synthesis, a four-component Ugi condensation and manganese-catalysed epoxidation reactions, as well as two previously unreported reactions, discovered from a selected chemical space, providing up to 50% yield improvement over 25-50 iterations. Finally, we demonstrate an experimental pipeline to explore a trifluoromethylations reaction space, that discovers new molecules.

MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery

We herein describe the development and application of a modular technology platform which incorporates recent advances in plate-based microscale chemistry, automated purification, in situ quantification, and robotic liquid handling to enable rapid access to high-quality chemical matter already formatted for assays. In using microscale chemistry and thus consuming minimal chemical matter, the platform is not only efficient but also follows green chemistry principles. By reorienting existing high-throughput assay technology, the platform can generate a full package of relevant data on each set of compounds in every learning cycle. The multiparameter exploration of chemical and property space is hereby driven by active learning models. The enhanced compound optimization process is generating knowledge for drug discovery projects in a time frame never before possible.

Trends and challenges in microfluidic methods for protein manipulation-A review

Proteins are important molecules involved in an immensely large number of biological processes. Being capable of manipulating proteins is critical for developing reliable and affordable techniques to analyze and/or detect them. Such techniques would enable the production of therapeutic agents for the treatment of diseases or other biotechnological applications (e.g., bioreactors or biocatalysis). Microfluidic technology represents a potential solution to protein manipulation challenges because of the diverse phenomena that can be exploited to achieve micro- and nanoparticle manipulation. In this review, we discuss recent contributions made in the field of protein manipulation in microfluidic systems using different physicochemical principles and techniques, some of which are miniaturized versions of already established macro-scale techniques.

Autonomous chemical research with large language models

Transformer-based large language models are making significant strides in various fields, such as natural language processing1-5, biology6,7, chemistry8-10 and computer programming11,12. Here, we show the development and capabilities of Coscientist, an artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs complex experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation. Coscientist showcases its potential for accelerating research across six diverse tasks, including the successful reaction optimization of palladium-catalysed cross-couplings, while exhibiting advanced capabilities for (semi-)autonomous experimental design and execution. Our findings demonstrate the versatility, efficacy and explainability of artificial intelligence systems like Coscientist in advancing research.

AI-driven robotic chemist for autonomous synthesis of organic molecules

The automation of organic compound synthesis is pivotal for expediting the development of such compounds. In addition, enhancing development efficiency can be achieved by incorporating autonomous functions alongside automation. To achieve this, we developed an autonomous synthesis robot that harnesses the power of artificial intelligence (AI) and robotic technology to establish optimal synthetic recipes. Given a target molecule, our AI initially plans synthetic pathways and defines reaction conditions. It then iteratively refines these plans using feedback from the experimental robot, gradually optimizing the recipe. The system performance was validated by successfully determining synthetic recipes for three organic compounds, yielding that conversion rates that outperform existing references. Notably, this autonomous system is designed around batch reactors, making it accessible and valuable to chemists in standard laboratory settings, thereby streamlining research endeavors.

Revisiting the Paradigm of Reaction Optimization in Flow with a Priori Computational Reaction Intelligence

The use of micro/meso-fluidic reactors has resulted in both new scenarios for chemistry and new requirements for chemists. Through flow chemistry, large-scale reactions can be performed in drastically reduced reactor sizes and reaction times. This obvious advantage comes with the concomitant challenge of re-designing long-established batch processes to fit these new conditions. The reliance on experimental trial-and-error to perform this translation frequently makes flow chemistry unaffordable, thwarting initial aspirations to revolutionize chemistry. By combining computational chemistry and machine learning, we have developed a model that provides predictive power tailored specifically to flow reactions. We show its applications to translate batch to flow, to provide mechanistic insight, to contribute reagent descriptors, and to synthesize a library of novel compounds in excellent yields after executing a single set of conditions.

Evaluation of a compact composite sensor array for concentration monitoring of solutions and suspensions via multivariate analysis

Compact composite probes were identified as a priority to alleviate space constraints in miniaturized unit operations and pharmaceutical manufacturing platforms. Therefore, in this proof of principle study, a compact composite sensor array (CCSA) combining ultraviolet and near infrared features at four different wavelengths (280, 340, 600, 860 nm) in a 380 × 30 mm housing (length x diameter, 7 mm diameter at the probe head), was evaluated for its capabilities to monitor in situ concentration of solutions and suspensions via multivariate analysis using partial least squares (PLS) regression models. Four model active pharmaceutical ingredients (APIs): warfarin sodium isopropanol solvate (WS), lidocaine hydrochloride monohydrate (LID), 6-mercaptopurine monohydrate (6-MP), and acetaminophen (ACM) in their aqueous solution and suspension formulation were used for the assessment. The results demonstrate that PLS models can be applied for the CCSA prototype to measure the API concentrations with similar accuracy (validation samples within the United States Pharmacopeia (USP) limits), compared to univariate CCSA models and multivariate models for an established Raman spectrometer. Specifically, the multivariate CCSA models applied to the suspensions of 6-MP and ACM demonstrate improved accuracy of 63% and 31%, respectively, compared to the univariate CCSA models [1]. On the other hand, the PLS models for the solutions WS and LID showed a reduced accuracy compared to the univariate models [1].

Parallel multi-droplet platform for reaction kinetics and optimization

We present an automated droplet reactor platform possessing parallel reactor channels and a scheduling algorithm that orchestrates all of the parallel hardware operations and ensures droplet integrity as well as overall efficiency. We design and incorporate all of the necessary hardware and software to enable the platform to be used to study both thermal and photochemical reactions. We incorporate a Bayesian optimization algorithm into the control software to enable reaction optimization over both categorical and continuous variables. We demonstrate the capabilities of both the preliminary single-channel and parallelized versions of the platform using a series of model thermal and photochemical reactions. We conduct a series of reaction optimization campaigns and demonstrate rapid acquisition of the data necessary to determine reaction kinetics. The platform is flexible in terms of use case: it can be used either to investigate reaction kinetics or to perform reaction optimization over a wide range of chemical domains.

Rapid Enantiomeric Excess Measurements of Enantioisotopomers by Molecular Rotational Resonance Spectroscopy

Recent work in drug discovery has shown that selectively deuterated small molecules can improve the safety and efficacy for active pharmaceutical ingredients. The advantages derive from changes in metabolism resulting from the kinetic isotope effect when deuterium is substituted for a hydrogen atom at a structural position where rate limiting C-H bond breaking occurs. This application has pushed the development of precision deuteration strategies in synthetic chemistry that can install deuterium atoms with high regioselectivity and with stereocontrol. Copper-catalyzed alkene transfer hydrodeuteration chemistry has recently been shown to have high stereoselectivity for deuteration at the metabolically important benzyl C-H position. In this case, stereocontrol results in the creation of enantioisotopomers-molecules that are chiral solely by virtue of the deuterium substitution-and chiral analysis techniques are needed to assess the reaction selectivity. It was recently shown that chiral tag molecular rotational resonance (MRR) spectroscopy provides a routine way to measure the enantiomeric excess and establish the absolute configuration of enantioisotopomers. High-throughput implementations of chiral tag MRR spectroscopy are needed to support optimization of the chemical synthesis. A measurement methodology for high-throughput chiral analysis is demonstrated in this work. The high-throughput ee measurements are performed using cavity-enhanced MRR spectroscopy, which reduces measurement times and sample consumption by more than an order-of-magnitude compared to the previous enantioisotopomer analysis using a broadband MRR spectrometer. It is also shown that transitions for monitoring the enantiomers can be selected from a broadband rotational spectrum without the need for spectroscopic analysis. The general applicability of chiral tag MRR spectroscopy is illustrated by performing chiral analysis on six enantioisotopomer reaction products using a single molecule as the tag for chiral discrimination.

A field guide to flow chemistry for synthetic organic chemists

Flow chemistry has unlocked a world of possibilities for the synthetic community, but the idea that it is a mysterious "black box" needs to go. In this review, we show that several of the benefits of microreactor technology can be exploited to push the boundaries in organic synthesis and to unleash unique reactivity and selectivity. By "lifting the veil" on some of the governing principles behind the observed trends, we hope that this review will serve as a useful field guide for those interested in diving into flow chemistry.

Techno-economic analysis of dynamic, end-to-end optimal pharmaceutical campaign manufacturing using PharmaPy

Increased interest in the pharmaceutical industry to transition from batch to continuouos manufacturing motivates the use of digital frameworks that allow systematic comparison of candidate process configurations. This paper evaluates the technical and economic feasibility of different end-to-end optimal process configurations, viz. batch, hybrid and continuous, for small-scale manufacturing of an active pharmaceutical ingredient. Production campaigns were analyzed for those configurations containing continuous equipment, where significant start-up effects are expected given the relatively short campaign times considered. Hybrid operating mode was found to be the most attractive process configuration at intermediate and large annual production targets, which stems from combining continuous reactors and semi-batch vaporization equipment. Continuous operation was found to be more costly, due to long stabilization times of continuous crystallization, and thermodynamic limitations of flash vaporization. Our work reveals the benefits of systematic digital evaluation of process configurations that operate under feasible conditions and compliant product quality attributes.

Comparing Integrated Continuous Process "LaVortex®" and Conventional Batch Processes for the Pharmaceutical Manufacturing of Acetaminophen Oral Dosage Formulations: Challenges and Pharmaceutical Properties of the Granular and Tableted Products

LaVortex® was developed as a novel free-flow continuous granulation/drying (CGD) system. In this study, we compared the advantages and disadvantages of granules prepared by continuous and batchwise manufacturing systems. Granules containing 30 % acetaminophen were manufactured under various operating conditions using CGD system, with comparison granules manufactured using conventional batch systems that involve a combination of fluid bed granulation (FG), agitation granulation (AG), continuous drying, fluid bed drying, and/or shelf drying, after which the pharmaceutical properties of each type of manufactured granule were evaluated. Cumulative particle-size distributions were determined by sieving, powder flowabilities were determined by angle of repose measurements, and scanning electron microscopy was employed to examine granule morphologies. The CGD system produced fine-to-large spherical or ellipsoidal granules that exhibited excellent powder fluidities and tabletabilities that are almost identical to those of AG granules. Moreover, the CGD granules exhibited better powder flowability than the FG granules. The addition of water promoted CGD-granule growth and improved significantly powder flowability, and did a little in tabletability. Small spherical granules with good fluidity suitable for fine-particle-coating core materials, or large granules with excellent fluidity and tabletability, were prepared by adjusting the values of the elemental parameters of the CGD process.

Scalable mRNA Machine for Regulatory Approval of Variable Scale between 1000 Clinical Doses to 10 Million Manufacturing Scale Doses

The production of messenger ribonucleic acid (mRNA) and other biologics is performed primarily in batch mode. This results in larger equipment, cleaning/sterilization volumes, and dead times compared to any continuous approach. Consequently, production throughput is lower and capital costs are relatively high. Switching to continuous production thus reduces the production footprint and also lowers the cost of goods (COG). During process development, from the provision of clinical trial samples to the production plant, different plant sizes are usually required, operating at different operating parameters. To speed up this step, it would be optimal if only one plant with the same equipment and piping could be used for all sizes. In this study, an efficient solution to this old challenge in biologics manufacturing is demonstrated, namely the qualification and validation of a plant setup for clinical trial doses of about 1000 doses and a production scale-up of about 10 million doses. Using the current example of the Comirnaty BNT162b2 mRNA vaccine, the cost-intensive in vitro transcription was first optimized in batch so that a yield of 12 g/L mRNA was achieved, and then successfully transferred to continuous production in the segmented plug flow reactor with subsequent purification using ultra- and diafiltration, which enables the recycling of costly reactants. To realize automated process control as well as real-time product release, the use of appropriate process analytical technology is essential. This will also be used to efficiently capture the product slug so that no product loss occurs and contamination from the fill-up phase is <1%. Further work will focus on real-time release testing during a continuous operating campaign under autonomous operational control. Such efforts will enable direct industrialization in collaboration with appropriate industry partners, their regulatory affairs, and quality assurance. A production scale-operation could be directly supported and managed by data-driven decisions.

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?

Towards Antibiotic Synthesis in Continuous-Flow Processes

Continuous-flow chemistry has become a mainstream process and a notable trend among emerging technologies for drug synthesis. It is routinely used in academic and industrial laboratories to generate a wide variety of molecules and building blocks. The advantages it provides, in terms of safety, speed, cost efficiency and small-equipment footprint compared to analog batch processes, have been known for some time. What has become even more important in recent years is its compliance with the quality objectives that are required by drug-development protocols that integrate inline analysis and purification tools. There can be no doubt that worldwide government agencies have strongly encouraged the study and implementation of this innovative, sustainable and environmentally friendly technology. In this brief review, we list and evaluate the development and applications of continuous-flow processes for antibiotic synthesis. This work spans the period of 2012-2022 and highlights the main cases in which either active ingredients or their intermediates were produced under continuous flow. We hope that this manuscript will provide an overview of the field and a starting point for a deeper understanding of the impact of flow chemistry on the broad panorama of antibiotic synthesis.

Bayesian Self-Optimization for Telescoped Continuous Flow Synthesis

The optimization of multistep chemical syntheses is critical for the rapid development of new pharmaceuticals. However, concatenating individually optimized reactions can lead to inefficient multistep syntheses, owing to chemical interdependencies between the steps. Herein, we develop an automated continuous flow platform for the simultaneous optimization of telescoped reactions. Our approach is applied to a Heck cyclization-deprotection reaction sequence, used in the synthesis of a precursor for 1-methyltetrahydroisoquinoline C5 functionalization. A simple method for multipoint sampling with a single online HPLC instrument was designed, enabling accurate quantification of each reaction, and an in-depth understanding of the reaction pathways. Notably, integration of Bayesian optimization techniques identified an 81 % overall yield in just 14 h, and revealed a favorable competing pathway for formation of the desired product.

Continuous Extraction of 2-Chloroethyl isocyanate for 1-(2-chloroethyl)-3-cyclohexylurea Purification

This study details the development of simulation-aided design, development, and successful operation of a continuous liquid-liquid extraction platform made with 1.5 mm tubing for the extraction of 2-chloroethyl isocyanate, an important reagent in the synthesis of cancer drugs. Preliminary solvent screening was carried out with partition coefficient calculations to determine solvents of interest. Next, batch and flow extraction experiments of 2-chloroethyl isocyanate in 2-methyl tetrahydrofuran and water were conducted to estimate extraction parameters. Following parameter estimation, experimental and model values for KLa were determined in the range of 1.13×10-3 to 36.0×10-3 s-1. Simulations of the extraction of 2-chloroethyl isocyanate were found to agree with experimental data resulting in a maximum efficiency of 77% and percent extraction of 69% for the continuous platform. Finally, model selection and discrimination was implemented for design space generation with experimental and model determined KLa values to guide lab-scale operation.

Microreactor Technology: Identifying Focus Fields and Emerging Trends by Using CiteSpace II

Microreactors have gained widespread attention from academia and industrial researchers due to their exceptionally fast mass and heat transfer and flexible control. In this work, CiteSpace software was used to systematically analyze the relevant literature to gain a comprehensively understand on the research status of microreactors in various fields. The results show that the research depth and application scope of microreactors are continuing to expand. The top 10 most popular research fields are photochemistry, pharmaceutical intermediates, multistep flow synthesis, mass transfer, computational fluid dynamics, μ-TAS (micro total analysis system), nanoparticles, biocatalysis, hydrogen production, and solid-supported reagents. The evolution trends of current focus areas are examined, including photochemistry, mass transfer, biocatalysis and hydrogen production and their milestone literature is analyzed in detail. This article demonstrates the development of different fields of microreactors technology and highlights the unending opportunities and challenges offered by this fascinating technology.

Inline purification in continuous flow synthesis – opportunities and challenges

Continuous flow technology has become the method of choice for many academic and industrial researchers when developing new routes to chemical compounds of interest. With this technology maturing over the last decades, robust and oftentimes automated processes are now commonly exploited to generate fine chemical building blocks. The integration of effective inline analysis and purification tools is thereby frequently exploited to achieve effective and reliable flow processes. This perspective article summarizes recent applications of different inline purification techniques such as chromatography, extractions, and crystallization from academic and industrial laboratories. A discussion of the advantages and drawbacks of these tools is provided as a guide to aid researchers in selecting the most appropriate approach for future applications. It is hoped that this perspective contributes to new developments in this field in the context of process and cost efficiency, sustainability and industrial uptake of new flow chemistry tools developed in academia.

To infinity and beyond: Strategies for fabricating medicines in outer space

Recent advancements in next generation spacecrafts have reignited public excitement over life beyond Earth. However, to safeguard the health and safety of humans in the hostile environment of space, innovation in pharmaceutical manufacturing and drug delivery deserves urgent attention. In this review/commentary, the current state of medicines provision in space is explored, accompanied by a forward look on the future of pharmaceutical manufacturing in outer space. The hazards associated with spaceflight, and their corresponding medical problems, are first briefly discussed. Subsequently, the infeasibility of present-day medicines provision systems for supporting deep space exploration is examined. The existing knowledge gaps on the altered clinical effects of medicines in space are evaluated, and suggestions are provided on how clinical trials in space might be conducted. An envisioned model of on-site production and delivery of medicines in space is proposed, referencing emerging technologies (e.g. Chemputing, synthetic biology, and 3D printing) being developed on Earth that may be adapted for extra-terrestrial use. This review concludes with a critical analysis on the regulatory considerations necessary to facilitate the adoption of these technologies and proposes a framework by which these may be enforced. In doing so, this commentary aims to instigate discussions on the pharmaceutical needs of deep space exploration, and strategies on how these may be met.

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Space is a hostile environment that threatens human health and drug stability.

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Data on the behaviour of medicines in space is critical but lacking.

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Novel drug manufacturing and delivery strategies are needed to safeguard crewmembers’ safety.

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Chemputing, synthetic biology, and 3D printing are examples of such emerging technologies.

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A regulatory framework for space medicines must be implemented to assure quality.

A perspective on automated advanced continuous flow manufacturing units for the upgrading of biobased chemicals toward pharmaceuticals

Biomass is a renewable, almost infinite reservoir of a large diversity of highly functionalized chemicals. The conversion of biomass toward biobased platform molecules through biorefineries generally still lacks economic viability. Profitability could be enhanced through the development of new market opportunities for these biobased platform chemicals. The fine chemical industry, and more specifically the manufacturing of pharmaceuticals is one of the sectors bearing significant potential for these biobased building blocks to rapidly emerge and make a difference. There are, however, still many challenges to be dealt with before this market can thrive. Continuous flow technology and its integration for the upgrading of biobased platform molecules for the manufacturing of pharmaceuticals is foreseen as a game-changer. This perspective reflects on the main challenges relative to chemical, process, regulatory and supply chain-related burdens still to be addressed. The implementation of integrated continuous flow processes and their automation into modular units will help for tackling with these challenges.

Graphical abstract

Synthesis of Ibuprofen Monoglyceride Using Novozym®435: Biocatalyst Activation and Stabilization in Multiphasic Systems

This work was focused on the enzymatic esterification of glycerol and ibuprofen at high concentrations in two triphasic systems composed of toluene+ibuprofene (apolar) and glycerol or glycerol–water (polar) liquid phases, and a solid phase with the industrial immobilized lipase B from Candida antarctica named Novozym®435 (N435) acting as the biocatalyst. Based on a preliminary study, the concentration of the enzyme was set at 30 g·L−1 and the stirring speed at 720 r.p.m to reduce external mass transfer limitations. To obtain more information on the reaction system, it was conducted at a wide range of temperatures (50 to 80 °C) and initial concentrations of ibuprofen (20–100 g·L−1, that is, 97 to 483 mM). Under these experimental conditions, the external mass transfer, according to the Mears criterion (Me = 1.47–3.33·10−4 << 0.15), was fast, presenting no limitation to the system productivity, regardless of the presence of water and from 50 to 80 °C. Considering that the enzyme is immobilized in a porous ion-exchange resin, limitations due to internal mass transfer can exist, depending on the values of the effectiveness factor (η). It varied from 0.14 to 0.23 at 50 to 80 °C and 0.32–1 mm particle diameter range in the absence of water, and in the same ranges, from 0.40 to 0.66 in the presence of 7.4% w/w water in the glycerol phase. Thus, it is evident that some limitation occurs due to mass transfer inside the pores, while the presence of water in the polar phase increases the productivity 3–4 fold. During the kinetic study, several kinetic models were proposed for both triphasic reacting systems, with and without first-order biocatalyst deactivation, and their fit to all relevant experimental data led to the observation that the best kinetic model was a reversible hyperbolic model with first-order deactivation in the anhydrous reaction system and a similar model, but without deactivation, for the system with added water at zero time. This fact is in sharp contrast to the use of N435 in a water-glycerol monophasic system, where progressive dissolution of ibuprofen in the reacting media, together with a notable enzyme deactivation, is observed.

Accelerating space radiation countermeasure development through drug repurposing

The discovery of safe and effective radiation countermeasures (MCM) for long-duration spaceflight is challenging due to the complexity of the space radiation biology and high safety requirements. There are few if any clinically-validated molecular targets for this use case, and preclinical models have several known limitations. These challenges make the evaluation of existing FDA-approved drugs for this indication, or drug repurposing, an attractive strategy to accelerate space radiation countermeasure development. Drug repurposing offers several advantages over de novo drug discovery including established manufacturing methods, human clinical safety data, and well-understood dosing and pharmacokinetic considerations. There are limitations working with a fixed set of possible candidate compounds, but some properties of repurposed drugs can be tailored for well-defined new indications through reformulation and development of drug combinations. Drug repurposing is thus an attractive strategy for mitigating the high risks and costs of drug development and delivering new countermeasures to protect human from space radiation in long-term missions.