Development of a high intensity parallel photoreactor for high throughput screening

Qi, Ning; Wismer, Michael K.; Conway, Donald V.; Krska, Shane W.; Dreher, Spencer D.; Lin, Shishi

doi:10.1039/d1re00317h

Cited by 19 publications

(15 citation statements)

References 26 publications

(21 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although automation is not necessary for reaction implementation using this setup (unlike the 1536-well MTP approach), the SBS footprint of these reactors means that they are compatible with a variety of different platforms for automated liquid and solid handling 214,215 to streamline reaction implementation and optimization. The flexibility and accessibility of this 96-well approach has led to widespread usage with multiple literature examples for HTE optimization 216,217 is a commonly reported HTE method which can facilitate the collection of thousands of data points within a multiparameter optimization. 227−229 Due to the minute volumes of material employed in this approach, access to specialized liquid handling robotics is required.…”

Section: Multifactorial Optimizationmentioning

confidence: 99%

A Brief Introduction to Chemical Reaction Optimization

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Section: Multifactorial Optimizationmentioning

confidence: 99%

A Brief Introduction to Chemical Reaction Optimization

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Optimization of reaction conditions and development of methodology is the first stage in organic synthesis. To address this aim, compact metal reactors have been developed, allowing the installation of several reactors to carry out many experiments at once to accelerate the optimization of organic synthesis conditions 70 . In the present work, we designed photochemical reactors that may be effectively manufactured using 3D printing technology (Figs.…”

Section: Resultsmentioning

confidence: 99%

Exploring metallic and plastic 3D printed photochemical reactors for customizing chemical synthesis

Gordeev

Erokhin

Kobelev

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Visible light photocatalysis is a rapidly developing branch of chemical synthesis with outstanding sustainable potential and improved reaction design. However, the challenge is that many particular chemical reactions may require dedicated tuned photoreactors to achieve maximal efficiency. This is a critical stumbling block unless the possibility for reactor design becomes available directly in the laboratories. In this work, customized laboratory photoreactors were developed with temperature stabilization and the ability to adapt different LED light sources of various wavelengths. We explore two important concepts for the design of photoreactors: reactors for performing multiple parallel experiments and reactors suitable for scale-up synthesis, allowing a rapid increase in the product amount. Reactors of the first type were efficiently made of metal using metal laser sintering, and reactors of the second type were successfully manufactured from plastic using fused filament fabrication. Practical evaluation has shown good accuracy of the temperature stabilization in the range typically required for organic synthesis for both types of reactors. Synthetic application of 3D printed reactors has shown good utility in test reactions—furan C–H arylation and thiol-yne coupling. The critical effect of temperature stabilization was established for the furan arylation reaction: heating of the reaction mixture may lead to the total vanishing of photochemical effect.

show abstract

“…Importantly, the resulting binary classification task enables the identification of sufficiently productive reactions (> 10% or 20% product LCAP) for medicinal chemistry campaigns. 46 Each model was evaluated based on its ability to recommend hits (reactions with a product LCAP of >= 0, 10 or 20%). The corresponding metric is precision@N, which is calculated by using the model to recommend N reactions it predicts to be hits and then evaluating the percentage of those reactions that are classified correctly in the desired product LCAP bin.…”

Section: Modellingmentioning

confidence: 99%

Roadmap to Pharmaceutically Relevant Reactivity Models Leveraging High-Throughput Experimentation

Kalyani

Struble

et al. 2022

Preprint

View full text Add to dashboard Cite

The merger of High-Throughput Experimentation (HTE) and data science presents an opportunity to both accelerate and inspire innovations in synthetic chemistry. Similarly, developments in machine learning (ML) have enabled the distillation of large and complex data sets into predictive models capable of generalizing patterns in the data. However, efforts to merge HTE with ML remain constrained by a few reported datasets with limited structural diversity and corresponding trained models that do not extrapolate well to substrates beyond the training set. Herein, we detail the first ML models for Pd-catalyzed C–N couplings using pharmaceutically relevant structurally diverse large data sets (~ 5000 unique products) generated using nanomole scale compatible chemistry. Careful consideration is given to both the diversity of the data set and accurate model predictions for substrates bearing features beyond those present in the training set. The structural diversity in the data set is enabled by leveraging the Merck & Co., Inc Building Block Collection with an initial focus on C–N coupling using secondary amines. The large dataset enables the systematic evaluation of model performance using five different data-splitting strategies. These five splits are carefully designed to evaluate the model’s ability to extrapolate beyond the substrates in the training set. The accuracy of classification models built with a lens toward application to medicinal chemistry campaigns exceeded the baseline precision-recall by 25-67% depending on the splitting strategy. These results would manifest as significant enrichment of successful C–N couplings using the hits recommended by the models. In addition, the accuracy of the best models for each of the five splits ranges between 70-87% suggesting excellent overall predictivity of the models even for completely unseen substrates.

show abstract

Development of a high intensity parallel photoreactor for high throughput screening

Abstract: Enhanced reactivity of decarboxylative cross-coupling using a new parallel photoreactor.

Cited by 19 publications

References 26 publications

A Brief Introduction to Chemical Reaction Optimization

A Brief Introduction to Chemical Reaction Optimization

Exploring metallic and plastic 3D printed photochemical reactors for customizing chemical synthesis

Roadmap to Pharmaceutically Relevant Reactivity Models Leveraging High-Throughput Experimentation

Contact Info

Product

Resources

About