The application of design of experiments (DoE) reaction optimisation and solvent selection in the development of new synthetic chemistry

Optimizing N,N,N-trimethyl chitosan synthesis: A design of experiments (DoE) approach

This study aimed to optimize the synthesis of trimethyl chitosan (TMC) with a high degree of N,N,N-trimethylation (DTM) through a one-step procedure, minimizing reagent use, reaction time, and avoiding O-methylation, using the Design of Experiments (DoE) approach. Initially, sequential designs were done. Following the determination of the initial conditions a Fractional Factorial Design was used, investigating methyl iodide (MeI) and NaHCO3 molar ratios, temperature, and reaction time on DTM. MeI and NaHCO3 molar ratios were found to be significant (p-values equal to 0.02 and 0.02, respectively), the reaction temperature (p = 0.04) displayed a non-linear effect, while the reaction time was found to be non-significant (p = 0.93). Finally, a Full Factorial Design was done to optimize temperature and base addition methods. Incremental addition of the base was determined to be feasible without affecting the DTM, thereby preventing any viscosity-related problems. DTM was achieved up to 72 % in a one-step procedure, with no O-methylation. These optimized conditions offer a cost-effective, one-step synthesis method for TMC production, holding significant promise for industrial applications by avoiding multistep reactions, ensuring minimal reagent use, and preventing O-methylation. The findings mark a substantial advancement in TMC synthesis, presenting a streamlined and efficient approach with substantial practical implications for process development.

Flow-based bioconjugation of coumarin phosphatidylethanolamine probes: Optimised synthesis and membrane molecular dynamics studies

A series of phosphatidylethanolamine fluorescent probes head-labelled with 3-carboxycoumarin was prepared by an improved bioconjugation approach through continuous flow synthesis. The established procedure, supported by a design of experiment (DoE) set-up, resulted in a significant reduction in the reaction time compared to the conventional batch method, in addition to a minor yield increase. The characterization of these probes was enhanced by an in-depth molecular dynamics (MD) study of the behaviour of a representative probe of this family, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine labelled with 3-carboxycoumarin (POPE-COUM), in bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/1-stearoyl-2-linoleoyl-sn-glycero-3-phosphocholine (SLPC) 2:1, mimicking the composition of the egg yolk lecithin membranes recently used experimentally by our group to study POPE-COUM as a biomarker of the oxidation state and integrity of large unilamellar vesicles (LUVs). The MD simulations revealed that the coumarin group is oriented towards the bilayer interior, leading to a relatively internal location, in agreement with what is observed in the nitrobenzoxadiazole fluorophore of commercial head-labelled NBD-PE probes. This behaviour is consistent with the previously stated hypothesis that POPE-COUM is entirely located within the LUVs structure. Hence, the delay on the oxidation of the probe in the oxygen radical absorbance capacity (ORAC) assays performed is related with the inaccessibility of the probe until alteration of the LUV structure occurs. Furthermore, our simulations show that POPE-COUM exerts very little global and local perturbation on the host bilayer, as evaluated by key properties of the unlabelled lipids. Together, our findings establish PE-COUM as suitable fluorescent lipid analogue probes.

General Installation of (4H)-Imidazolone cis-Amide Bioisosteres Along the Peptide Backbone

Imidazolones represent an important class of heterocycles present in a wide range of pharmaceuticals, metabolites, and bioactive natural products and serve as the active chromophore in green fluorescent protein. Recently, imidazolones have received attention for their ability to act as a nonaromatic amide bond bioisotere which improves pharmacological properties. Herein, we present a tandem amidine installation and cyclization with an adjacent ester to yield (4H)-imidazolone products. Using amino acid building blocks, we can access the first examples of α-chiral imidazolones that have been previously inaccessible. Additionally, our method is amenable to on-resin installation which can be seamlessly integrated into existing solid-phase peptide synthesis protocols. Finally, we show that peptide imidazolones are potent cis-amide bond surrogates that preorganize linear peptides for head-to-tail macrocyclization. This work represents the first general approach to the backbone and side-chain insertion of imidazolone bioisosteres at various positions in linear and cyclic peptides.

Direct Heterocycle C-H Alkenylation via Dual Catalysis Using a Palladacycle Precatalyst: Multifactor Optimization and Scope Exploration Enabled by High-Throughput Experimentation

One of the major challenges in developing catalytic methods for C-C bond formation is the identification of generally applicable reaction conditions, particularly if multiple substrate structural classes are involved. Pd-catalyzed direct arylation reactions are powerful transformations that enable direct functionalization of C-H bonds; however, the corresponding direct alkenylation reactions, using vinyl (pseudo) halide electrophiles, are less well developed. Inspired by process development efforts toward GSK3368715, an investigational active pharmaceutical ingredient, we report that a Pd(II) palladacycle derived from tri-tert-butylphosphine and Pd(OAc)2 is an effective single-component precatalyst for a variety of direct alkenylation reactions. High-throughput experimentation identified optimal solvent/base combinations for a variety of HetAr-H substrate classes undergoing C-H activation without the need for cocatalysts or stoichiometric silver bases (e.g., Ag2CO3). We propose this reaction proceeds via a dual cooperative catalytic mechanism, where in situ-generated Pd(0) supports a canonical Pd(0)/(II) cross-coupling cycle and the palladacycle effects C-H activation via CMD in a redox-neutral cycle. In all, 192 substrate combinations were tested with a hit rate of approximately 40% and 24 isolated examples. Importantly, this method was applied to prepare a key intermediate in the synthesis of GSK3368715 on multigram scale.

Implementation of Quality by Design Approaches for Development and Validation of Reverse-Phase High-Performance Liquid Chromatography Assay Method for Determination of Glycyrrhizin in Nanoformulation

Glycyrrhizin (GL) is the principal constituent of Glycyrrhiza glabra, having antiallergic, anticancer, anti-inflammatory, and antimicrobial action. The reverse-phase high-performance liquid chromatography (RP-HPLC) analytical method was used to quantitatively estimate GL in a nanoformulation and validated as per International Conference on Harmonization Q2 (R1) standards. A stationary phase of the C18-HL reversed-phase column and a mobile phase of acetonitrile and water were used for effective elution. The chromatographic conditions of RP-HPLC were optimized utilizing a quality-by-design approach to accomplish the required chromatographic separation of GL from its nanoformulation with minimal experimental runs. Optimized RP-HPLC conditions for the assay method consist of acetonitrile (41%) and water, pH 1.8, balanced with phosphoric acid (0.1%) as a mobile phase with a flow rate of 1 mL/min. The retention time was found at 7.25 min, and method validation confirmed its sensitivity, preciseness, accuracy, and robustness.

DoE-Assisted Development of a 2H-MoS2 -Catalyzed Approach for the Production of Indole Derivatives

2H-MoS2 is an appealing semiconductor because of its Earth-abundant nature, cheapness, and low toxicity. This material has shown promising catalytic activity for various energy-related processes, but its use in catalysis for C-C bond forming reactions towards useful organic compounds is still largely unexplored. The lack of examples in organic synthesis is mainly due to the intrinsic difficulties of using bulk 2H-MoS2 (e. g., low surface area), which implies the reliance on high catalytic loadings for obtaining acceptable yields. This makes the optimization process more expensive and tedious. Here, we report the development of a 2H-MoS2 -mediated synthesis of valuable bis(indolyl)methane derivatives, using indoles and benzaldehydes as starting materials. Exploiting the Design of Experiments (DoE) method, we identified the critical parameters affecting the catalytic performance of commercial 2H-MoS2 powder and optimized the reaction conditions. Lastly, we demonstrated that the catalytic system has versatility and good tolerance towards functional group variations of the reagents.

A Customized Bayesian Algorithm to Optimize Enzyme-Catalyzed Reactions

Design of experiments (DoE) plays an important role in optimizing the catalytic performance of chemical reactions. The most commonly used DoE relies on the response surface methodology (RSM) to model the variable space of experimental conditions with the fewest number of experiments. However, the RSM leads to an exponential increase in the number of required experiments as the number of variables increases. Herein we describe a Bayesian optimization algorithm (BOA) to optimize the continuous parameters (e.g., temperature, reaction time, reactant and enzyme concentrations, etc.) of enzyme-catalyzed reactions with the aim of maximizing performance. Compared to existing Bayesian optimization methods, we propose an improved algorithm that leads to better results under limited resources and time for experiments. To validate the versatility of the BOA, we benchmarked its performance with biocatalytic C-C bond formation and amination for the optimization of the turnover number. Gratifyingly, up to 80% improvement compared to RSM and up to 360% improvement vs previous Bayesian optimization algorithms were obtained. Importantly, this strategy enabled simultaneous optimization of both the enzyme's activity and selectivity for cross-benzoin condensation.

Bayesian Optimization-Assisted Screening to Identify Improved Reaction Conditions for Spiro-Dithiolane Synthesis

Bayesian optimization (BO)-assisted screening was applied to identify improved reaction conditions toward a hundred-gram scale-up synthesis of 2,3,7,8-tetrathiaspiro[4.4]nonane (1), a key synthetic intermediate of 2,2-bis(mercaptomethyl)propane-1,3-dithiol [tetramercaptan pentaerythritol]. Starting from the initial training set (ITS) consisting of six trials sampled by random screening for BO, suitable parameters were predicted (78% conversion yield of spiro-dithiolane 1) within seven experiments. Moreover, BO-assisted screening with the ITS selected by Latin hypercube sampling (LHS) further improved the yield of 1 to 89% within the eight trials. The established conditions were confirmed to be satisfactory for a hundred grams scale-up synthesis of 1.

Prediction Model Based on DoE and FTIR Data to Control Fast Setting and Early Shrinkage of Alkaline-Activated Slag/Silica Fume Blended Cementitious Material

This study aims to develop a material-saving performance prediction model for fast-hardening alkali-activated slag/silica fume blended pastes. The hydration process in the early stage and the microstructural properties after 24 h were analyzed using design of experiments (DoE). The experimental results show that the curing time and the FTIR wavenumber of the Si-O-T (T = Al, Si) bond in the band range of 900-1000 cm^-1 after 24 h can be predicted accurately. In detailed investigations, low wavenumbers from FTIR analysis were found to correlate with reduced shrinkage. The activator exerts a quadratic and not a silica modulus-related conditioned linear influence on the performance properties. Consequently, the prediction model based on FTIR measurements proved to be suitable in evaluation tests for predicting the material properties of those binders in the building chemistry sector.

Epoxide of Diosgenin Acetate Synthesis: DoE for Diastereoselective Yield Optimization, Antimicroibial, antioxidant and antiproliferative effects

Diosgenin and its derivatives have proved a huge importance in diverse biological activities. The optimized production of the diastereoisomers of the epoxide of diosgenin acetate by means of mCPBA is reported herein. This transformation had a previous design of experiments using the application of a statistical factorial DoE of 4 parameters (n^k), where one variable is varied at a time, while others stay constant. The temperature showed the greatest effect on the reaction yield; so, at 298 K the diastereomeric ratio 3:1 of α and β-epoxides, normally found, was raised to 1:1. Time was the second significant variable, but due to its high correlation with temperature, 30 minutes were required for a global 90% conversion at least. These diastereoisomers were characterized both isolated and in the mixtures obtained, to determine their antioxidant, antimicrobial and antiproliferative activity, finding a low antioxidant capacity by DPPH, but antimicrobial activity at the level of penicillin in gram negative bacteria by 1β better to 1α. The antiproliferative capacity was higher for diastereoisomer β, agreeing with the proportion of the mixture obtained by different conditions, increasing this in relation to the amount of this diastereoisomer present in hormone-dependent cancer cell lines such as Hela, PC-3 and MCF-7, with 10.0 µM obtained values of viability at 21.8 %, 35.8 % and 12.3 % respectively. DoE optimization allows to manipulate the ratio between diastereoisomers with the minimum number of experiments, extending the analysis of the effect of the ratio between diastereoisomers and the in silico potential as well as the biological activity.

Nickel-Catalyzed Isomerization of Homoallylic Alcohols

Nickel-catalyzed isomerizations of homoallylic alcohols and a bishomoallylic alcohol are presented. These isomerization reactions occur in the presence of a simple nickel catalyst that does not require addition of an exogenous ligand. The corresponding ketone products are generated in ≤98% yield.

Loteprednol-Loaded Nanoformulations for Corneal Delivery by Quality-by-Design Concepts: Optimization, Characterization, and Anti-inflammatory Activity

Loteprednol etabonate (LE) is a topical corticosteroid that uses inflammatory conditions of the eye. It has a low ocular bioavailability and side effects such as corneal disorder, eye discharge, and ocular discomfort. Therefore, it was decided to select the delivery systems, which are solid lipid nanoparticles (SLN), nanostructured lipid carriers (NLC), and nanoemulsion (NE). Design of experiments (DoE) of SLN, NLC, and NE formulations were formulated by using the quality by design (QbD) approach. Precirol® ATO 5 and oleic acid were used as solid and liquid lipids, respectively, in SLN, NLC, and NE formulations. Physiochemical characterization was performed on the formulations. The optimized formulations' inflammatory effects have been appraised on human corneal epithelial cells employing the ELISA test. Physicochemical characterization studies and inflammatory effects were appraised. The sizes of optimized formulations of SLN, NLC, and NE were 86.19 nm, 82.38 nm, and 126.35 nm, respectively, with minimum polydispersity. The release behavior of the formulations is composed of both diffusion and erosion. ELISA test results proved that the formulations significantly reduced IL-1 and IL-6 levels (p < 0.05). D-optimal mixture experimental design allowed us to develop the most precise formulations of SLN, NLC, and NE. Furthermore, the optimized formulations could be promising candidates for treating an inflammation-based corneal disease of the eye.

A Brief Introduction to Chemical Reaction Optimization

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

Amelioration of lipopeptide biosurfactants for enhanced antibacterial and biocompatibility through molecular antioxidant property by methoxy and carboxyl moieties

Biosurfactants having surface-active biomolecules have been the cynosure in environment research due to their vast application. However, the lack of information about their low-cost production and detailed mechanistic biocompatibility limits the applicability. The study explores techniques for the production and design of low-cost, biodegradable, and non-toxic biosurfactants from Brevibacterium casei strain LS14 and excavates the mechanistic details of their biomedical properties like antibacterial effects and biocompatibility. Taguchi's design of experiment was used to optimize for enhancing biosurfactant production by optimal factor combinations like Waste glycerol (1%v/v), peptone (1%w/v), NaCl 0.4% (w/v), and pH 6. Under optimal conditions, the purified biosurfactant reduced the surface tension to 35 mN/m from 72.8 mN/m (MSM) and a critical micelle concentration of 25 mg/ml was achieved. Spectroscopic analyses of the purified biosurfactant using Nuclear Magnetic Resonance suggested it as a lipopeptide biosurfactant. The evaluation of mechanistic antibacterial, antiradical, antiproliferative, and cellular effects indicated the efficient antibacterial activity (against Pseudomonas aeruginosa) of biosurfactants due to free radical scavenging activity and oxidative stress. Moreover, the cellular cytotoxicity was estimated by MTT and other cellular assays revealing the phenomenon as the dose-dependent induction of apoptosis due to free radical scavenging with an LC50 of 55.6 ± 2.3 mg/ml.

Design and Investigation of a Photocatalytic Setup for Efficient Biotransformations Within Recombinant Cyanobacteria in Continuous Flow

Photo- and biocatalysis show many advantages as more sustainable solutions for the production of fine chemicals. In an effort to combine the benefits and the knowledge of both these areas, a continuous photobiocatalytic setup was designed and optimized to carry out whole-cell biotransformations within cells of the cyanobacterium Synechocystis sp. PCC 6803 expressing the gene of the ene-reductase YqjM from B. subtilis. The effect of the light intensity and flow rate on the specific activity in the stereoselective reduction of 2-methyl maleimide was investigated via a design-of-experiments approach. The cell density in the setup was further increased at the optimal operating conditions without loss in specific activity, demonstrating that the higher surface area/volume ratio in the coil reactor improved the illumination efficiency of the process. Furthermore, different reactor designs were compared, proving that the presented approach was the most cost- and time-effective solution for intensifying photobiotransformations within cyanobacterial cells.

A Multi-Objective Active Learning Platform and Web App for Reaction Optimization

We report the development of an open-source experimental design via Bayesian optimization platform for multi-objective reaction optimization. Using high-throughput experimentation (HTE) and virtual screening data sets containing high-dimensional continuous and discrete variables, we optimized the performance of the platform by fine-tuning the algorithm components such as reaction encodings, surrogate model parameters, and initialization techniques. Having established the framework, we applied the optimizer to real-world test scenarios for the simultaneous optimization of the reaction yield and enantioselectivity in a Ni/photoredox-catalyzed enantioselective cross-electrophile coupling of styrene oxide with two different aryl iodide substrates. Starting with no previous experimental data, the Bayesian optimizer identified reaction conditions that surpassed the previously human-driven optimization campaigns within 15 and 24 experiments, for each substrate, among 1728 possible configurations available in each optimization. To make the platform more accessible to nonexperts, we developed a graphical user interface (GUI) that can be accessed online through a web-based application and incorporated features such as condition modification on the fly and data visualization. This web application does not require software installation, removing any programming barrier to use the platform, which enables chemists to integrate Bayesian optimization routines into their everyday laboratory practices.

Application of tools and techniques of quality by design in pharmaceutical process

Purpose

The purpose of this article is to demonstrate the application of the tools and techniques of Quality by Design (QbD) approach in an Indian pharmaceutical drug product manufacturing company and to understand the challenges, managerial implications and lessons learned while implementing this initiative.

Design/methodology/approach

This work adopts the Action Research methodology for impurity reduction in a drug product manufacturing company in India by using the tools and techniques of QbD approach. Various QbD tools like Design of experiments, process capability evaluation and control charts were effectively utilized for the study.

Findings

As a part of QbD implementation in the organization, a specific drug product was identified and the impurity level in the product was studied. Significant variables impacting the impurity were identified and the optimum levels for the significant variables were identified through design of experiments. The solutions were implemented and the impurity levels were reduced significantly.

Research limitations/implications

Even though the article is based on a single case study related to tools and techniques of QbD in a single organization in India, the identified problem is a generic product quality related issue for any pharmaceutical drug product manufacturing company. Hence the findings of this research are applicable to pharmaceutical drug manufacturing industry in general.

Originality/value

This article illustrates the systematic usage of various tools and techniques of QbD methodology in a pharmaceutical drug product manufacturing company. The usage of Design of Experiments for process optimization and application of other tools and techniques are ready references for the practitioners and novice users in the field.

Synthesis of oxaboranes via nickel-catalyzed dearylative cyclocondensation

We report Ni-catalyzed dearylative cyclocondensation of aldehydes, alkynes, and triphenylborane. The reaction is initiated by oxidative cyclization of the aldehyde and alkyne coupling partners to generate an oxanickelacyclopentene which reacts with triphenylborane to form oxaboranes. This formal dearylative cyclocondensation reaction generates oxaboranes in moderate-to-high yields (47–99%) with high regioselectivities under mild reaction conditions. This approach represents a direct and modular synthesis of oxaboranes which are difficult to access using current methods. These oxaboranes are readily transformed into valuable building blocks for organic synthesis and an additional class of boron heterocycles. Selective homocoupling forms oxaboroles, oxidation generates aldol products, and reduction and arylation form substituted allylic alcohols.

Oxaboranes are prepared via a nickel-catalyzed dearylative cyclocondensation reaction in up to 99% yield and excellent regioselectivity. These oxaborane products can be further transformed into a variety of synthetically useful building blocks.

DoE-Driven Development of an Organocatalytic Enantioselective Addition of Acetaldehyde to Nitrostyrenes in Water

The development of an enantioselective enamine‐catalysed addition of masked acetaldehyde to nitroalkenes via a rational approach helped to move away from the use of chloroform. The presented research allows the use of water as a reaction medium, therefore improving the industrial relevance of a protocol to access very important pharmaceutical intermediates. Critical to the success is the use of chemometrics‐assisted ‘Design of Experiments’ (DoE) optimisation during the development of the presented new synthetic approach, which allows to investigate the chemical space in a rational way.

Experimentally designed chemometric models for the assay of toxic adulterants in turmeric powder

Turmeric is an indispensable culinary spice in different cultures and a principal component in traditional remedies. Toxic metanil yellow (MY), acid orange 7 (AO) and lead chromate (LCM) are deliberately added to adulterate turmeric powder. This work compares the ability of multivariate chemometric models with those of artificial intelligent networks to enhance the selectivity of spectral data for the rapid assay of these three adulterants in turmeric powder. Using a custom experimental design, we provide a data-driven optimization for the sensitive parameters of the partial least squares model (PLS), artificial neural network (ANN) and genetic algorithm (GA). The optimized models are validated using sets of genuine turmeric samples from five different geographical regions spiked with standard adulterant concentrations. The optimized GA-PLS and GA-ANN models reduce the root mean square error of prediction by 18.4%, 31.1% and 55.3% and 25.0%, 69.9% and 88.4% for MY, AO and LCM, respectively.

Chemometrically Assisted Optimization of Pregabalin Fluorescent Derivatization Reaction with a Novel Xanthone Analogue and Validation of the Method for the Determination of Pregabalin in Bulk via a Plate Reader

Quantitation of chromophore-free analytes is always a challenge. To this purpose, derivatization of the analyte constitutes a common strategy, leading to a product with a strong signal. In the current study, a novel xanthone analogue was utilized for the first time for the derivatization of pregabalin, a model analyte with a primary amine moiety that lacks a chromophore. The fact that only the xanthene-based derivative, formed after the derivatization reaction fluoresces, enables avoiding its chromatographic separation from the reagent and thus reducing the analysis time of a series of samples in 1–2 min via a plate reader. The reaction conditions were optimized via a central composite design (CCD), with fluorescence signal as the measure of the yield. The following factors that affect the derivatization reaction were chosen: (a) temperature, (b) reaction time, and (c) triethylamine solution volume used to drive the reaction to completion. After the identification of the optimal conditions, the method was validated according to ICH guidelines, using a fluorescence plate reader for signal measurement (λex = 540, λem = 615 nm). Finally, the newly developed high-throughput method was applied to the determination of drug content in pregabalin bulk.

Bayesian based reaction optimization for complex continuous gas–liquid–solid reactions

In recent years, self-optimization strategies have been gradually utilized for the determination of optimal reaction conditions owing to their high convenience and independence from researchers' experience.

3D printed ceramics as solid supports for enzyme immobilization: an automated DoE approach for applications in continuous flow

In recent years, 3D printing has emerged in the field of chemical engineering as a powerful manufacturing technique to rapidly design and produce tailor-made reaction equipment. In fact, reactors with complex internal geometries can be easily fabricated, optimized and interchanged in order to respond to precise process needs, such as improved mixing and increased surface area. These advantages make them interesting especially for catalytic applications, since customized structured bed reactors can be easily produced. 3D printing applications are not limited to reactor design, it is also possible to realize functional low cost alternatives to analytical equipment that can be used to increase the level of process understanding while keeping the investment costs low. In this work, in-house designed ceramic structured inserts printed via vat photopolymerization (VPP) are presented and characterized. The flow behavior inside these inserts was determined with residence time distribution (RTD) experiments enabled by in-house designed and 3D printed inline photometric flow cells. As a proof of concept, these structured inserts were fitted in an HPLC column to serve as solid inorganic supports for the immobilization of the enzyme Phenolic acid Decarboxylase (bsPAD), which catalyzes the decarboxylation of cinnamic acids. The conversion of coumaric acid to vinylphenol was chosen as a model system to prove the implementation of these engineered inserts in a continuous biocatalytic application with high product yield and process stability. The setup was further automated in order to quickly identify the optimum operating conditions via a Design of Experiments (DoE) approach. The use of a systematic optimization, together with the adaptability of 3D printed equipment to the process requirements, render the presented approach highly promising for a more feasible implementation of biocatalysts in continuous industrial processes. Graphical abstract.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41981-021-00163-4.

Indium-Catalysed Transfer Hydrogenation for the Reductive Cyclisation of 2-Alkynyl Enones towards Trisubstituted Furans

Indium tribromide catalysed the transfer hydrogenation from dihydroaromatic compounds, such as the commercially available γ-terpinene, to enones, which resulted in the cyclisation to trisubstituted furan derivatives. The reaction was initiated by a Michael addition of a hydride nucleophile to the enone subunit followed by a Lewis-acid-assisted cyclisation and the formation of a furan-indium intermediate and a Wheland intermediate derived from the dihydroaromatic starting material. The product was formed by protonation from the Wheland complex and replaced the indium tribromide substituent. In addition, a site-specific deuterium labelling of the dihydroaromatic HD surrogates resulted in site specific labelling of the products and gave useful insights into the reaction mechanism by H-D scrambling.

The green solvent: a critical perspective

Solvents are important in most industrial and domestic applications. The impact of solvent losses and emissions drives efforts to minimise them or to avoid them completely. Since the 1990s, this has become a major focus of green chemistry, giving rise to the idea of the 'green' solvent. This concept has generated a substantial chemical literature and has led to the development of so-called neoteric solvents. A critical overview of published material establishes that few new materials have yet found widespread use as solvents. The search for less-impacting solvents is inefficient if carried out without due regard, even at the research stage, to the particular circumstances under which solvents are to be used on the industrial scale. Wider sustainability questions, particularly the use of non-fossil sources of organic carbon in solvent manufacture, are more important than intrinsic 'greenness'. While solvency is universal, a universal solvent, an alkahest, is an unattainable ideal.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10098-021-02188-8.

Use of Design of Experiments (DoE) to Model the Sulphate Agent Amount of (Ultra)Finely Ground and Fast Hardening Portland Cement Clinker

This paper presents a model to calculate the sulphate agent amount and sulphate agent ratio for fine grounded and fast hardening Portland cement clinker. Despite sufficient knowledge about the influence of calcium sulphate on the hydration process of cement, the sulphate agent amount is mostly adjusted empirically. As a result, often a wide and unfeasible experimental matrix has to be tested. In this work, Design of Experiments (DoE) was used in combination with in-situ X-ray diffraction (XRD) tests to accurately adjust the sulphate agent of different finely ground cement by calculation. With only 42 tests, it was possible to analyse in total the influence of the sulphate agent, the grinding fineness and the use of C-S-H-seeds for the use in fast-hardening Portland cement-based systems. In addition, it was found that a hemihydrate to anhydrite content of 25/75 leads to a stabilisation of the hydrated system in the first 24 h of hydration. A model for the optimisation of the sulphate agent composition in dependency of the cement fineness could be determined. Furthermore, it was shown that the DoE also provides optimal results in material sciences in a resource-saving way.

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is often the first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical when extended to higher dimensional input spaces, when complicated measurement constraints are present, or prior information known about the beam response is scarce. Here in this work, we describe an adaptation of the popular Bayesian optimization algorithm, which enables a turn-key exploration of input parameter spaces. Our algorithm replaces  the need for parameter scans while minimizing prior information needed about the measurement's behavior and associated measurement constraints. We experimentally demonstrate that our algorithm autonomously conducts an adaptive, multi-parameter exploration of input parameter space, potentially orders of magnitude faster than conventional grid-like parameter scans, while making highly constrained, single-shot beam phase-space measurements and accounts for costs associated with changing input parameters. In addition to applications in accelerator-based scientific experiments, this algorithm addresses challenges shared by many scientific disciplines, and is thus applicable to autonomously conducting experiments over a broad range of research topics.

Scalable 18F processing conditions for copper-mediated radiofluorination chemistry facilitate DoE optimization studies and afford an improved synthesis of [18F]olaparib

A convenient and scalable base-free method for processing [¹⁸F]fluoride as [¹⁸F]TBAF is reported and applied to copper-mediated radiofluorination radiosyntheses. A central feature of this method is that a single production of [¹⁸F]TBAF can be divided into small aliquots that can be used to perform multiple small-scale reactions in DoE optimization studies. The results of these studies can then be reliably translated to full batch tracer productions using automated synthesizers. The processing method was applied to the DoE optimization of [¹⁸F]olaparib, affording the tracer in high radiochemical yields via both manual (%RCY = 78 ± 6%, n = 4 (CMRF step only)) and automated (up to 80% (%RCY); 41% activity yield (%AY)) radiosynthesis procedures.

Simultaneous self-optimisation of yield and purity through successive combination of inline FT-IR spectroscopy and online mass spectrometry in flow reactions

Self-optimisation constitutes a very helpful tool for chemical process development, both in lab and in industrial applications. However, research on the application of model-free autonomous optimisation strategies (based on experimental investigation) for complex reactions of high industrial significance, which involve considerable intermediate and by-product formation, is still in an early stage. This article describes the development of an enhanced autonomous microfluidic reactor platform for organolithium and epoxide reactions that incorporates a successive combination of inline FT-IR spectrometer and online mass spectrometer. Experimental data is collected in real-time and used as feedback for the optimisation algorithms (modified Simplex algorithm and Design of Experiments) without time delay. An efficient approach to handle intricate optimisation problems is presented, where the inline FT-IR measurements are used to monitor the reaction’s main components, whereas the mass spectrometer’s high sensitivity permits insights into the formation of by-products. To demonstrate the platform’s flexibility, optimal reaction conditions of two organic syntheses are identified. Both pose several challenges, as complex reaction mechanisms are involved, leading to a large number of variable parameters, and a considerable amount of by-products is generated under non-ideal process conditions. Through multidimensional real-time optimisation, the platform supersedes labor- and cost-intensive work-up procedures, while diminishing waste generation, too. Thus, it renders production processes more efficient and contributes to their overall sustainability.

Graphical abstract

One-flow synthesis of tetrahydrocannabinol and cannabidiol using homo- and heterogeneous Lewis acids

Continuous flow chemistry holds great potential for the production of biologically relevant molecules. Herein, we present an approach for the continuous synthesis of cannabidiol and tetrahydrocannabinol in a one-flow system. The designed route consists of a reaction cascade involving Friedel-Crafts alkylation, subsequent ring opening and cyclisation in up to 45% yield. The reactions were successfully performed using both hetero- and homogeneous Lewis acids in continuous flow and provide yields that are similar to comparable batch processes.

Graphical abstract

Integration of Response Surface Methodology (RSM) and Principal Component Analysis (PCA) as an Optimization Tool for Polymer Inclusion Membrane Based-Optodes Designed for Hg(II), Cd(II), and Pb(II)

An optimization of the composition of polymer inclusion membrane (PIM)-based optodes, and their exposure times to metal ion solutions (Hg(II), Cd(II), and Pb(II)) was performed using two different chromophores, diphenylthiocarbazone (dithizone) and 1-(2-pyridylazo)-2-naphthol (PAN). Four factors were evaluated (chromophore (0.06-1 mg), cellulose triacetate (25-100 mg) and plasticizer amounts (25-100 mg), and exposure time (20-80 min)). Derringer's desirability functions values were employed as response variables to perform the optimization obtained from the results of three different processes of spectral data treatment: two full-spectrum methods (M1 and M3) and one band-based method (M2). The three different methods were compared using a heatmap of the coefficients and dendrograms of the Principal Component Analysis (PCA)reductions of their desirability functions. The final recommended M3 processing method, i.e., using the scores values of the first two principal components in PCA after subtraction of the normalized spectra of the membranes before and after complexation, gave more discernable differences between the PIMs in the Design of Experiments (DoE), as the nodes among samples appeared at longer distances and varyingly distributed in the dendrogram analysis. The optimal values were time of 35-65 min, 0.53 mg-1.0 mg of chromophores, plasticizers 34.4-71.9 of chromophores, and 62.5-100 mg of CTA, depending on the metal ion. In addition, the method yielded the best outcomes in terms of interpretability and an easily discernable color change so that it is recommended as a novel optimization method for this kind of PIM optode.

Applied biocatalysis beyond just buffers - from aqueous to unconventional media. Options and guidelines

In nature, enzymes conventionally operate under aqueous conditions. Because of this, aqueous buffers are often the choice for reaction media when enzymes are applied in chemical synthesis. However, to meet the demands of an industrial application, due to the poor water solubility of many industrially relevant compounds, an aqueous reaction system will often not be able to provide sufficient substrate loadings. A switch to a non-aqueous solvent system can provide a solution, which is already common for lipases, but more challenging for biocatalysts from other enzyme classes. The choices in solvent types and systems, however, can be overwhelming. Furthermore, some engineering of the protein structure of biocatalyst formulation is required. In this review, a guide for those working with biocatalysts, who look for a way to increase their reaction productivity, is presented. Examples reported clearly show that bulk water is not necessarily required for biocatalytic reactions and that clever solvent systems design can support increased product concentrations thereby decreasing waste formation. Additionally, under these conditions, enzymes can also be combined in cascades with other, water-sensitive, chemical catalysts. Finally, we show that the application of non-aqueous solvents in biocatalysis can actually lead to more sustainable processes. At the hand of flowcharts, following simple questions, one can quickly find what solvent systems are viable.

Site-Selective Acylation of Pyranosides with Oligopeptide Catalysts

Herein, we report the oligopeptide-catalyzed site-selective acylation of partially protected monosaccharides. We identified catalysts that invert site-selectivity compared to N-methylimidazole, which was used to determine the intrinsic reactivity, for 4,6-O-protected glucopyranosides (trans-diols) as well as 4,6-O-protected mannopyranosides (cis-diols). The reaction yields up to 81% of the inherently unfavored 2-O-acetylated products with selectivities up to 15:1 using mild reaction conditions. We also determined the influence of protecting groups on the reaction and demonstrate that our protocol is suitable for one-pot reactions with multiple consecutive protection steps.

C-H Activation: Toward Sustainability and Applications

Since the definition of the "12 Principles of Green Chemistry" more than 20 years ago, chemists have become increasingly mindful of the need to conserve natural resources and protect the environment through the judicious choice of synthetic routes and materials. The direct activation and functionalization of C-H bonds, bypassing intermediate functional group installation is, in abstracto, step and atom economic, but numerous factors still hinder the sustainability of large-scale applications. In this Outlook, we highlight the research areas seeking to overcome the sustainability challenges of C-H activation: the pursuit of abundant metal catalysts, the avoidance of static directing groups, the replacement of metal oxidants, and the introduction of bioderived solvents. We close by examining the progress made in the subfield of aryl C-H borylation from its origins, through highly efficient but precious Ir-based systems, to emerging 3d metal catalysts. The future growth of this field will depend on industrial uptake, and thus we urge researchers to strive toward sustainable C-H activation.

Flow chemistry for process optimisation using design of experiments

Implementing statistical training into undergraduate or postgraduate chemistry courses can provide high-impact learning experiences for students. However, the opportunity to reinforce this training with a combined laboratory practical can significantly enhance learning outcomes by providing a practical bolstering of the concepts. This paper outlines a flow chemistry laboratory practical for integrating design of experiments optimisation techniques into an organic chemistry laboratory session in which students construct a simple flow reactor and perform a structured series of experiments followed by computational processing and analysis of the results.

Computational Mapping of Dirhodium(II) Catalysts

The chemistry of dirhodium(II) catalysts is highly diverse, and can enable the synthesis of many different molecular classes. A tool to aid in catalyst selection, independent of mechanism and reactivity, would therefore be highly desirable. Here, we describe the development of a database for dirhodium(II) catalysts that is based on the principal component analysis of DFT-calculated parameters capturing their steric and electronic properties. This database maps the relevant catalyst space, and may facilitate exploration of the reactivity landscape for any process catalysed by dirhodium(II) complexes. We have shown that one of the principal components of these catalysts correlates with the outcome (e.g. yield, selectivity) of a transformation used in a molecular discovery project. Furthermore, we envisage that this approach will assist the selection of more effective catalyst screening sets, and, hence, the data-led optimisation of a wide range of rhodium-catalysed transformations.

Using design of experiment to obtain a systematic understanding of the effect of synthesis parameters on the properties of perovskite nanocrystals

Design of experiments was used to systematically investigate the synthesis of MAPbI₃ nanoparticles in a flow reactor. By controlling the solvents and the ligands, we were able to tune the MAPbI₃ photoluminescence peak between 614 and 737 nm.