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this way, the entire space can also be represented graphically as a contour plot; this allows the behavior of the factors to be more easily understood and interpreted, as well as allowing predicted response maxima to be easily identified. The response is often also mathematically transformed to give better predictabili...	{ "page_id": null, "source": 7334, "title": "from dpo" }
are incorporated into the model. However, all experimental factor and interaction terms can be added or removed from a DoE model depending on whether their contribution to the model is significant. To accurately isolate and determine interaction effects, specific DoE designs can be implemented. Within each design, the ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
a relatively low expertise barrier-to-entry, given the advent of DoE software, and provides bench scientists with tools to identify significant experimental variables and model their data. (34) Although there are several options for DoE designs, the statistical knowledge necessary for chemists to select the correct exp...	{ "page_id": null, "source": 7334, "title": "from dpo" }
knowledge gap, practical kinetic analysis is discussed in this review and how it relates to reaction optimization. When these kinetic models are constructed, they enable scientists to understand and simulate reactions to determine optimal regions of parameter space in silico. The physical modeling of a reaction typical...	{ "page_id": null, "source": 7334, "title": "from dpo" }
a zero-order, second-order or even noninteger-order dependence, as it is much more practical to describe the physical model in this way. (92−97) The physical models generated from kinetic analysis contain ingrained chemical information that, unlike their empirical model counterparts, can be used to extrapolate reaction...	{ "page_id": null, "source": 7334, "title": "from dpo" }
the visual determination of high-interest experimental parameters for process optimization. One example of this application is in the continuous-flow aqueous reduction of 4-nitrophenol, 20, to 4-aminophenol, 21, using gold nanoparticles (AuNPs) by Chamberlain and co-workers (Scheme 5). (101) This kinetic study related ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
reciprocal of the concentration data (c). However, when both reactants are not the same, more complex plotting can confirm an overall second-order reaction (d). Additional modeling, such as the conventional modeling of enzymatic (and sometimes other catalytic) reactions, known as Michaelis–Menten kinetics, can also be ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
barrier to access this form of kinetic analysis, namely, coding and mathematical knowledge. Software solutions have been developed to aid in this kinetic model fitting (Compunetics, (121) Berkeley Madonna, (122) DynoChem, (123) COPASI (124)) that often require minimal coding expertise, which have been adopted by proces...	{ "page_id": null, "source": 7334, "title": "from dpo" }
product inhibition. Therefore, precise kinetic parameters cannot be elucidated, but the plots required are simple to construct and easy to interpret, which allows easy determination of this kinetic information. Because of its systematic approach to analysis, RPKA has been widely adopted in process chemistry settings an...	{ "page_id": null, "source": 7334, "title": "from dpo" }
first-order dependence on the cobalt concentration, a zero-order dependence on the alkyne and a partial negative-order in the benzylamide concentration. The authors suggested that this partial negative-order finding was a result of off-cycle unproductive binding interactions with the catalyst, thereby decreasing the ef...	{ "page_id": null, "source": 7334, "title": "from dpo" }
Self-Optimization Self-optimization is a modern approach to automating the discovery of optimal reaction conditions for chemical processes which does not require the determination of explicit mechanistic or empirical models. Self-optimization proceeds through iterative cycles of automated reaction execution, quantifica...	{ "page_id": null, "source": 7334, "title": "from dpo" }
scientist, saving time and money. Additionally, self-optimizing systems offer a more consistent way of generating data than human driven reaction optimization. This means that self-optimization has the potential to not only accelerate reaction optimization but also provide data that will enable predictive modeling in t...	{ "page_id": null, "source": 7334, "title": "from dpo" }
running the reactor for an extended period (157) or numbering-up, (158) as discussed in section 7. However, three major challenges are faced by researchers using automated flow reactors for self-optimization. First, automated flow reactors can consume large amounts of starting material and solvent due to the need to fl...	{ "page_id": null, "source": 7334, "title": "from dpo" }
continuous variables (residence time, base equivalents, and temperature) and two categorical variables (catalyst and base) were varied to maximize the yield of 4-(p-tolyl)morpholine (34). In the chart, each column contains data for a different catalyst and base combination, and the experiments in each column are shown ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
solvents. Hein and co-workers conducted self-optimization of a stereoselective Suzuki coupling reaction using a ChemSpeed liquid handling robot, varying the ligand, several stoichiometries, and temperature to maximize the formation of the E-product and minimize the Z-product, as shown in Figure 11. (149) This self-opti...	{ "page_id": null, "source": 7334, "title": "from dpo" }
material is removed from the flow path for analysis. (169) This sampling is typically initialized based on the residence time of the reaction or, in the case of droplet flow reactors, an in-line UV cell. In addition to HPLC, gas chromatography (GC) has also been reported in the literature, but this is much less common....	{ "page_id": null, "source": 7334, "title": "from dpo" }
are achieved that give the optimal desired output. 5.2.1. Local Optimization vs Global Optimization The two main classes of optimization algorithms are local and global optimization algorithms. Local optimization algorithms are designed to find the optimal values of a function closest to an initial guess. Therefore, if...	{ "page_id": null, "source": 7334, "title": "from dpo" }
as its name suggests, relies on sequential branching and fitting steps. The algorithm begins by subdividing the optimization domain into boxes with one data point each (i.e., branching) and subsequently builds full quadratic models for each box and its nearest neighbors (i.e., fitting). (174) SNOBFIT achieves global op...	{ "page_id": null, "source": 7334, "title": "from dpo" }
once the best categorical combination has been identified, it suggests further experiments to improve the fit of the model. However, this approach requires users to specify a kinetic model a priori, which may be difficult when a full reaction mechanism is not known, as discussed in section 4. Furthermore, because no mo...	{ "page_id": null, "source": 7334, "title": "from dpo" }
usage) with the constraint that yield must be greater than 90%. (150) This constraint was implemented to prevent the yield being maximized by simply adding higher loadings of an expensive catalyst. In other cases, researchers have optimized a weighted function of multiple objectives. (144,151,183) Both of these methods...	{ "page_id": null, "source": 7334, "title": "from dpo" }
(STY) would correspond with an approximate 10% increase in impurity yield, which the scientist can then consider based on the needs of the process. Figure 13 Figure 13. Multiobjective self-optimization of the N-benzylation of N-benzylation of α-methylbenzylamine 38 with benzyl bromide 39. (175) TSEMO (184) was used to ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
that are easy for humans but more complex for machines, such as phase separations, extractions, crystallizations, etc. Additionally, self-optimization has shown promise in the automated optimization of single reactions, but there is a wealth of reaction data available that current algorithms are unable to utilize. Very...	{ "page_id": null, "source": 7334, "title": "from dpo" }
6.1.1. Multifactorial Optimization With HTE, a large proportion of chemical optimization space can be examined at once in an “all vs all” manner, where one exhaustive (full factorial) screen may help to identify optimal conditions much faster and more efficiently than performing reactions individually (e.g., using OFAT...	{ "page_id": null, "source": 7334, "title": "from dpo" }
than precious transition-metal catalysts that may be employed in their synthesis. By downscaling chemical reactions into a miniaturized format, one can increase the number of data points gained during a HTE screen without the associated impact on material cost. For decades, biological assays have been routinely perform...	{ "page_id": null, "source": 7334, "title": "from dpo" }
common synthetic apparatus such as round-bottomed flasks into plate-based formats means that chemical synthesis can be economized, thereby increasing the density of information obtained from the same amount of material. Table 1. Chemical Reaction Limitations with Relation to Current Miniaturization Technologiesa a RBF,...	{ "page_id": null, "source": 7334, "title": "from dpo" }
a microscale reactor can be more time-consuming than the addition of liquids or stock solutions, the ability to use solids is important as it broadens the variety of chemical reactions that can be performed, as not all chemical reagents can be effectively dispensed as stock solutions due to issues such as heterogeneity...	{ "page_id": null, "source": 7334, "title": "from dpo" }
volumes in the range of 25 nL to 1.2 μL, or Beckman’s Echo liquid handler, which can dispense volumes in the range of 2.5 nL to 5 μL using Echo Acoustic Technology. These platforms are increasingly used for nanoscale (or even picoscale) synthesis of pharmaceutically relevant compounds with examples of also incorporatin...	{ "page_id": null, "source": 7334, "title": "from dpo" }
the high-throughput data acquisition of 1536 reactions in under 10 min and requiring only nanolitre volumes of crude reaction mixtures. These techniques are rapid, and in some cases the analysis can be performed directly from a 1536-well MTP, however, the equipment required can be expensive. Other options for rapid ana...	{ "page_id": null, "source": 7334, "title": "from dpo" }
(4) the level of quantification that can be achieved. With ultrafast techniques like MALDI, DESI, AE-MS, etc., quantitative data can be acquired providing an internal standard is added to the analytical samples prior to analysis, an authentic sample of the analytes can be obtained, and a calibration curve run to compar...	{ "page_id": null, "source": 7334, "title": "from dpo" }
and consequently there is a scarcity of reports of HTE used in continuous flow. More often continuous flow is used for the scaling up or continuous variable optimization of HTE hits identified in plates, (228,259,260) however, before this can be accomplished, reoptimization is often required as chemistry seldom transla...	{ "page_id": null, "source": 7334, "title": "from dpo" }
optimization. (262) This work utilizes “stopped-flow” experiments and machine learning models to map chemical reactivity and synthesize diversity-oriented libraries. This led to a system that can predict optimal synthesis conditions with 92% accuracy and a dramatic increase in the success rate of initial library screen...	{ "page_id": null, "source": 7334, "title": "from dpo" }
reaction outcomes of the same reaction might arise from human error in the laboratory, transcription, or limitations of the text mining software, varying analytical methods and different reaction scales (mg to kg scale). Moreover, it must be noted that generally literature data is biased toward higher yields as low yie...	{ "page_id": null, "source": 7334, "title": "from dpo" }
to parallelize organic synthesis, has fueled a rise in reports of ultraHTE where hundreds or thousands of chemical reactions can be executed in parallel on a miniaturized scale. Although limitations still exist with regards to the types of chemistry that are amenable to these plate-based formats, further development to...	{ "page_id": null, "source": 7334, "title": "from dpo" }
developments are sure to modernize the area further and increase the number of data sets available to data scientists. 6.2. Data Mining, Machine Learning, and Optimization Benchmarking Machine learning (ML) has already revolutionized various areas, such as image recognition, (264) natural language processing, (265) and...	{ "page_id": null, "source": 7334, "title": "from dpo" }
private reaction databases. 6.2.1. Molecular Parameterization Molecules must be translated to a machine-readable, typically numerical, format that can be used as an input for ML models, prior to their use. We refer to this translation process as molecular parametrization as it aims to capture relevant molecular propert...	{ "page_id": null, "source": 7334, "title": "from dpo" }
implicit understanding of electronegativity associated with different halides, for example. (268) A much more comprehensive parametrization approach is calculating molecular descriptors using density functional theory (DFT). DFT can be used to determine the ground/excited state of molecules and thus offer fundamental i...	{ "page_id": null, "source": 7334, "title": "from dpo" }
prediction tasks. One of the most widely used forms of graph neural networks in chemistry are message passing neural networks (MPNNs), which learn relationships between neighboring atoms through iterative “messages” passed along bonds. (274,275) MPNNs have been extended to generate fingerprints for reactions, with stat...	{ "page_id": null, "source": 7334, "title": "from dpo" }
by Elsevier, and the United States Patent and Trademark Office (USPTO) reaction database are the two most used sources for data-mined applications. The Reaxys database is proprietary and contains information on more than 56 million reactions from over 16 000 journals. In contrast, the USPTO database is accessible to th...	{ "page_id": null, "source": 7334, "title": "from dpo" }
(288) This is often caused by scientists using the same procedure for a standard reaction as is reported in the literature. Therefore, a filtering process often includes removing duplicate reactions, discarding reactions with missing key reactants or reagents (e.g., a Suzuki reaction should always have an organohalide ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
The downside of this approach is that optimal reaction conditions for a particular transformation often require going beyond the standard conditions used for a transformation. Therefore, reaction condition prediction models might be used to give suggestions of starting points for further optimization rather than predic...	{ "page_id": null, "source": 7334, "title": "from dpo" }
with reaction outcomes recorded and further model development are needed to create general ML models for reaction optimization. If successful, this research could be transformative in reaction optimization and transition the field to more direct predictions of optimal reaction conditions. For a recent review of in-dept...	{ "page_id": null, "source": 7334, "title": "from dpo" }
initially promising discoveries and reaction routes may not achieve broad deployment in industrial production. (300,301) While large companies can invest vast resources into solving scale-up related challenges, (302) smaller research organizations such as start-ups or academia might not be in place to allocate such res...	{ "page_id": null, "source": 7334, "title": "from dpo" }
significant reductions in surface area/volume ratios that imposes limitations on heat transfer rate, sensitivity to mixing, and different time of addition and removal of products. (306)Figure 20 summarizes the typical time ranges of characteristic mixing, heat transfer, and liquid space time (reactor volume divided per...	{ "page_id": null, "source": 7334, "title": "from dpo" }
process scale-up, in some cases, the experimental effort necessary to derive these models is extensive, making it infeasible to realize in the fast-paced process development environment. In such cases, Stitt and Simmons (303) recommend determination from benchtop optimization, at a minimum, the following information: (...	{ "page_id": null, "source": 7334, "title": "from dpo" }
control. Continuous processing, in contrast, allows for a significant cost and environmental footprint reduction (if solvents are recycled (322,323)) by faster conversion and increased productivity, reduced down-time, and improved quality by facilitating continuous monitoring of critical parameters. From the perspectiv...	{ "page_id": null, "source": 7334, "title": "from dpo" }
dimensions expressed in base units (combination of, e.g., meter, kilogram, second). Detailed instructions on the derivation and use of dimensional analysis equations, followed by practical examples of calculations for stirred-tank reactors, were provided by Zlokarnik (329,330) and Wild and co-workers. (331) These equat...	{ "page_id": null, "source": 7334, "title": "from dpo" }
intensification reactors were proposed by Commenge and Falk, (306) and an overview of different options was presented in an open-source database published by Gorak and co-workers. (339) Selected reactor architectures and the optimal conditions determined for a scaled-up process are frequently verified on a scale of pil...	{ "page_id": null, "source": 7334, "title": "from dpo" }
numbering-up is associated with high investment cost: numerous reactors are required instead of a single stirred-tank reactor, along with multiple process control devices. Detailed insights into the economics of numbering-up were described by Weber and Snowden-Swan, (345) and the potential to intensify the process can ...	{ "page_id": null, "source": 7334, "title": "from dpo" }
that are out of safe operating bounds: this includes reactions that are suggested at unsafe temperatures or concentrations. Thermal runaway occurs when the rate of an exothermic reaction is accelerated by increases in temperature. In the worst case, this rate acceleration can lead to secondary decomposition reactions t...	{ "page_id": null, "source": 7334, "title": "from dpo" }
to the excellent reviews by Yang on safety aspects of DMSO (354) and Pd-catalyzed reactions, (350) as well as the textbook by Stoessel on “Thermal Safety of Chemical Processes”. (355) 8. Conclusion In this review, we have outlined several modern techniques that are utilized for chemical reaction optimization to serve a...	{ "page_id": null, "source": 7334, "title": "from dpo" }
meet the needs of the modern laboratory. It is the hope that this timely review will prove the accessibility of these optimization techniques and help to encourage inspired chemists to incorporate them into their workflows. Author Information Corresponding Authors Connor J. Taylor - Astex Pharmaceuticals, 436 Cambridge...	{ "page_id": null, "source": 7334, "title": "from dpo" }
curation, formal analysis, investigation, writing-original draft, writing-review & editing; Kobi C. Felton formal analysis, investigation, methodology, writing-original draft, writing-review & editing; Rachel Grainger formal analysis, investigation, methodology, writing-original draft, writing-review & editing; Magda B...	{ "page_id": null, "source": 7334, "title": "from dpo" }
the NC State University and a MPhil Research from the University of Cambridge. Rachel Grainger received her MChem in Chemistry for Drug Discovery (University of Bath, 2010), and her Ph.D. under the supervision of Prof. Igor Larrosa (QMUL, 2014). She then moved to Cambridge (UK) and worked as a postdoc with Prof. Matthe...	{ "page_id": null, "source": 7334, "title": "from dpo" }
a Ph.D. with Professors Andrei Khlobystov and Neil Champness in Chemistry and Peter Beton in the School of Physics, working on the synthesis of novel functional fullerene molecules and the subsequent formation of fullerene/carbon nanotube peapod structures. He received his Ph.D. in 2009 and then joined the Nottingham N...	{ "page_id": null, "source": 7334, "title": "from dpo" }
C.J.T. is a Sustaining Innovation Postdoctoral Research Associate at Astex Pharmaceuticals and thanks Astex Pharmaceuticals for funding, as well as his Astex colleagues Mark Wade, Gianni Chessari, and David Rees for their support. K.C.F. has received Ph.D. funding from the Marshall Scholarship, Cambridge Trust, and BAS...	{ "page_id": null, "source": 7334, "title": "from dpo" }
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