Automated Reactor Sampling System

Q: What are some common applications for automated reactor sampling?

Impurity profiling Parallel synthesis Organometallic synthesis and chemistry C–H activation reactions Chemical reaction kinetics Design of Experiment (DoE) studies Synthesis reactions Flow chemistry High-pressure reactions Hydrogenation reactions Quality by design (QbD)

EasySampler for Unattended, Representative Sampling

Automated sampling enables increased productivity by addressing challenges associated with manual sampling tools such as pipettes and syringes. Automated, inline chemical reaction sampling with EasySampler™ is an intuitive and seamless extension that streamlines the experimental workflow for every chemist while eliminating the tedious task of manual sampling.

EasySampler is an automated and unattended sampling solution that delivers high-quality samples day and night for standard offline analysis, such as HPLC. This unique probe-based technology features a patented micro-pocket and allows for:

Sampling and quenching in situ and at reaction conditions
Taking samples at scheduled intervals
Diluting the sample in preparation for offline analysis
Simple operation with no expert knowledge required

Increase productivity and eliminate tedious tasks.

Automated Sampling for Chemical Reactions

Increase Productivity

Preprogram the unattended collection of precision samples, day or night to ensure high-quality samples are captured even if you are too busy to be in the lab.

Never Miss a Reaction Event

Automated and unattended sampling helps you thoroughly understand and define reaction pathways, kinetics, impurity profiles, and endpoints.

EasySampler representative and reproducible

Representative & Reproducible

Sample and quench at reaction conditions—even when manual sampling is impossible or very difficult due to challenging conditions.

EasySampler 1210 Automated Sampling System for Chemical Reactors

EasySampler 1210 System

EasySampler eliminates sampling challenges—taking representative and reproducible analytical samples from almost any chemical reaction has never been easier!

Automated and unattended
Gain complete reaction profiles and reaction understanding, and improve yield and product quality—never miss a sample.

Superior quality samples
Improved reaction information by linking process conditions with the points at which species form.

Wide range of chemistries
Easy sampling of a wide range of chemistries, including slurries and reactions that are air and moisture-sensitive, even at elevated temperature and pressure.

HPLC-Ready Samples around the Clock

Increased productivity and understanding

The obligations of the workday (or night) often do not allow sampling of reactions as often as required. This leads to lost or missing data. Frequently, these missing data points omit optimum end-point and important understanding of impurity formation. EasySampler executes representative and reproducible sampling including in-situ quench and dilution—providing LC-ready samples at any time.

Sampling from reactors with EasySampler enables scientists to optimize their workflow and productivity by enabling increased reaction understanding while eliminating tedious manual sample practices. For even further productivity gains, sampling can be automatically scheduled or triggered as a function of varying process parameters including temperature, stirring, dosing, pH, or other real-time process information.

Solution-Phase Sampling with EasyFrit Filter

Automated sampling for crystallization process development

Expand the capabilities of EasySampler with the seamless integration of EasyFrit. The EasyFrit filter is compatible with all EasySampler probes and allows for selective sampling of the solution phase despite the presence of suspended particles. This accessory creates an easy-to-use, automated sampling solution for crystallization studies.

EasySampler with EasyFrit facilitates data-rich experimentation throughout a controlled crystallization. Embedding this solution in a particle engineering workstation enables a better understanding of the solution-phase by creating impurity profiles, uncovering the effects of supersaturation on impurity, and providing kinetic and thermodynamic information of the crystallization process.

Truly Representative Reaction Progression

Eliminate critical data gaps

EasySampler's intuitive touchscreen allows scientists to preprogram sampling and dilution sequences to track reaction progression over time—without manual intervention. This allows every scientist to reproducibly capture a representative sample for offline analysis, such as HPLC or NMR, to understand reaction pathways, kinetics, intermediates, and impurity profiles.

Automated sampling with EasySampler can be used in round bottom flasks, jacketed lab reactors, or seamlessly integrated with automated chemical reactors. This allows straightforward identification of the impact of varying process conditions on reaction performance.

pfizer demonstrates automated chemical sampling

Pfizer Evaluates Automated Sampling

View this white paper that highlights four case studies where Pfizer researchers successfully used unattended, automated chemical reaction sampling:

Removing Barriers for Impurity and Kinetics Profiling in an Ullman Reaction
Improving Confidence by Measuring the Effect of Process Parameters on an Imidazolide Reaction
Extending Productivity with Endpoint Detection in a C–H Reaction
Ensuring Successful Scale-up of an Amination Reaction

Reactions that Pfizer successfully sampled include:

Thick slurries
Dark mixtures with inorganic salts present
Tri-phasic mixtures
Oxygen-sensitive reactions

Sample Challenging Reactions

From slurries to elevated temperature

Manual sampling does not always provide precise and reproducible samples, especially in heterogeneous and multiphase reactions or reactions at sub-ambient or elevated temperatures and pressures. Delays in quenching typically lead to variable results and inaccurate analytical information. EasySampler provides an automated and robust inline method of capturing and quenching samples from reactions—even under difficult conditions.

The flexible nature of EasySampler allows scientists to obtain high-quality samples from a variety of processes from vial to kilo scale equipment including pressure vessels and reactor systems.

automated reaction sampling at elevated temperatures

Representative, Reproducible Results

More high-quality data points per experiment

Automated sampling is a key enabler for reaction understanding as it eliminates sampling error and ensures that offline analytical results truly represent the reaction as it exists under process conditions.

Representative, reproducible results are achieved by:

Sampling from the same position in the reactor, at reaction conditions
Time-stamped samples—circumvent errors caused by variances in recordkeeping. Data can be easily combined with results from inline PAT-based analytical methods.
Automatic and seamless data collection—increase the number of samples and data quality that also supports data-rich experimentation

Limit Exposure to Hazardous Chemistry

Safety by Design

When working in the laboratory, scientists are potentially exposed to hazardous chemicals and are at risk of injury.

When taking samples manually using traditional sampling tools, the operator needs to open the reactor which can be exposed to toxic materials at elevated temperatures or pressures.

EasySampler automated reactor sampling system reduces the need for manual handling and exposure to hazardous chemicals, reducing risks and improving user safety.

automated reactor sampling system touchscreen

EasySampler—Critical for Data Rich Experimentation

automated sampling system for bioreactor

Inline, Continuous Sampling

EasySampler's unique, probe-based technology allows you to sample uninterrupted throughout the duration of the experiment.

Ready for Offline Analytics

Plan and execute sample, quench, and dilution sequences directly on the touchscreen or in iControl for accurate, reproducible samples.

Supports Reaction Understanding

Combine information on reaction progression and impurity formation with critical process parameters to support QbD initiatives.

EasySampler automated reactor sampling system

Expand Your Capabilities

With the connectivity kit, EasySampler sampling data is automatically transferred to, and reported with, the referring automated reactor system.

Increase automation capabilities and improve productivity by combining automated sampling with synthesis reactors. All data from every connected instrument is collected at the end of an experiment. Data is stored in a common location with optional email notifications with links to files for each experiment.

Chemical Sampling FAQs

What is an automated reactor sampling system and how does it work?

EasySampler combines three sampling steps into a single automated operation, sampling the same way, every time to provide reproducible and accurate samples.

Accurate sampling starts when the micro-pocket moves out and is immersed within the reaction mixture to ensure a representative sample is taken
In-situ quench immediately stops the reaction and ensures the time point is representative
Subsequent dilution and dispensing in the vial prepare samples for offline analysis

These steps allow samples to be highly reproducible and provide representative analytical results. Above all, automated samples can be taken at preprogrammed or scheduled times.

What are some common applications for automated reactor sampling?

What is the temperature range of the EasySampler probe?

At atmospheric pressure, EasySampler probes are rated for temperatures in the range of -20 to 140 °C. It is recommended to change sleeves after 100 samples within this temperature range, at atmospheric pressure. For reactions at elevated pressures, between 1.013 bar and 10 bar, the temperature range is 20 to 100 °C.

Why should I automate my sampling of chemical reactions?

Sampling chemical reactions for offline analysis to determine reaction progress or impurity profiles is standard practice. However, the manual sampling process is challenging because it requires physical presence and experience, especially with air-sensitive reactions, reactions at elevated pressure, or studies with heterogeneous mixtures.

Benefits from automating manual sampling include:

Increased sample-to-sample representativeness and overall quality of data
Increased productivity by freeing scientists from time-consuming work
Increased efficiency by capturing more data from a single experiment and fewer repetitions
Increased understanding of complete and comprehensive datasets spanning over multiple hours/days
Sample at fixed time intervals or upon reaction events like reaching temperature setpoint or pH

Automate your sampling today with EasySampler.

I have a reactor from another vendor; can I use EasySampler with this reactor?

Yes, EasySampler can function as a stand-alone device and can be used in any reactor, including tube reactors, round-bottomed flasks, jacked lab reactors (JLR), and automated lab reactors (ALR). Points to consider:

All models of EasySampler probes are 9.5 mm in diameter
An appropriate adapter should be used to fit the EasySampler probe securely into the reactor port

Can EasySampler be used to sample reactions at elevated pressure?

Yes, EasySampler can sample reactions under pressure if all the following reaction conditions are met:

Pressure range: 1.013 bar – 10 bar (14.7 psi – 145 psi)
Temperature range: 20 to 100 °C
Reactor volume: up to 2500 mL
Number of samples per sleeve: 1 reaction (with up to 24 samples)
High-pressure adapter: An appropriate high-pressure adapter (P/N14474404) must be used to securely position the EasySampler probe in the reactor

Note: Use of the EasySampler probe at elevated pressure (between 1.013 bar to 10 bar) will reduce the temperature range to 20 °C to 100 °C, the maximum reactor volume to 2500 mL, and the maximum number of samples per sleeve to 1 reaction (with up to 24 samples).

What is the automated sampling process?

The automated sampling process refers to the use of automated systems and equipment to collect samples for analysis in various industries such as pharmaceuticals and chemical manufacturing.

Automated sampling typically involves the use of a sampling system that is designed to obtain representative samples of materials or substances from a process. The sample is then typically transfered to analytical instrument for analysis.

What are the benefits of automated sampling over a manual injection system?

There are several benefits of automated sampling over a manual injection system, including:

Improved accuracy
Increased efficiency
Consistency
Increased safety
Cost savings

What is the purpose of automated sampling in reaction modeling?

The purpose of automated sampling in reaction modeling is to obtain data on the reaction progress over time and to analyze the behavior of the reaction under different conditions. Automated sampling systems can be used to collect samples at regular intervals, allowing researchers to monitor the reaction progress and to identify reaction intermediates, products, and byproducts. This information can then be used to develop mathematical models to describe the reaction and to optimize the reaction conditions.

Learn more about chemical reaction modeling.

What are the challenges when sampling slurries?

Slurries are heterogeneous mixtures containing different types and sizes of particles, which can make it difficult to obtain representative samples. The particles in the slurry can cause blockages in the sampling equipment, which can affect the accuracy and representativeness of the sample.

EasySampler allows for selective sampling of the solution phase despite the presence of suspended particles. This autosampler creates an easy-to-use, automated sampling solution for crystallization studies.

Automated Chemical Sampling Resources

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Sampling of Chemical Reactions at Pfizer

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Continued automated sampling with the EasySampler supports reaction and impurity profiling studies. A list of publications from peer-reviewed journals focuses on exciting and novel applications of EasySampler by researchers in academia and industry to support data-rich experimentation and advance their research.

2024

Agrawal, S., Rawal, S. H., Reddy, V. R., & Merritt, J. M. (2024). Use of automation, dynamic image analysis, and process analytical technologies to enable data rich particle engineering efforts at the Drug Substance / Drug Product interface: A case study using Lovastatin. Process Safety and Environmental Protection/Transactions of the Institution of Chemical Engineers. Part B, Process Safety and Environmental Protection/Chemical Engineering Research and Design/Chemical Engineering Research & Design. https://doi.org/10.1016/j.cherd.2024.04.032
McMullen, J. P., Wyvratt, B. M., Hong, C. M., & Purohit, A. K. (2024). Integrating Functional Principal Component Analysis with Data-Rich Experimentation for Enhanced Drug Substance Development. Organic Process Research & Development, 28(3), 719–728. https://doi.org/10.1021/acs.oprd.3c00379

2023

Cox, R. J., McCreanor, N. G., Morrison, J. A., Munday, R. H., & Taylor, B. (2023). Copper-Catalyzed Racemization-Recycle of a quaternary center and optimization using a combined Kinetics-DOE/MLR modeling approach. Journal of Organic Chemistry, 88(9), 5275–5284. https://doi.org/10.1021/acs.joc.2c02588
Deem, M. C., & Hein, J. E. (2023). A Method for Converting HPLC Peak Area from Online Reaction Monitoring to Concentration Using Nonlinear Regression. Journal of Organic Chemistry, 88(2), 1292–1297. https://doi.org/10.1021/acs.joc.2c02737
Kaldre, D., Stocker, S., Linder, D., Reymond, H., Schuster, A., Lamerz, J., Hildbrand, S., Püntener, K., Berry, M., & Sedelmeier, J. (2023). Development of a continuous flow grignard reaction to manufacture a key intermediate of Ipatasertib. Organic Process Research & Development. https://doi.org/10.1021/acs.oprd.3c00235
Kukor, A. J., St-Jean, F., Stumpf, A., Malig, T. C., Piechowicz, K. A., Kurita, K., & Hein, J. E. (2023). Guided optimization of a Crystallization-Induced diastereomer transformation to access a key navoximod intermediate. Reaction Chemistry and Engineering, 8(6), 1294–1299. https://doi.org/10.1039/d3re00077j

2022

Deadman, B. J., Gian, S., Lee, V. E. Y., Adrio, L. A., Hellgardt, K., & Hii, K. K. (2022). On-demand, in situ, generation of ammonium caroate (peroxymonosulfate) for the dihydroxylation of alkenes to vicinal diols. Green Chemistry. https://doi.org/10.1039/d2gc00671e
Deem, M. C., Derasp, J. S., Malig, T. C., Legard, K., Berlinguette, C. P., & Hein, J. E. (2022). Ring walking as a regioselectivity control element in Pd-catalyzed C-N cross-coupling. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-30255-1
Kukor, A. J., Depner, N., Cai, I., Tucker, J. V., Culhane, J. C., & Hein, J. E. (2022). Enantioselective synthesis of (−)-tetrabenazine via continuous crystallization-induced diastereomer transformation. Chemical Science, 13(36), 10765–10772. https://doi.org/10.1039/d2sc01825j
LaPorte, A. J., Shi, Y., Hein, J. E., & Burke, M. D. (2022). Stereospecific Csp3 Suzuki–Miyaura Cross-Coupling That Evades β-Oxygen Elimination. ACS Catalysis, 12(17), 10905–10912. https://doi.org/10.1021/acscatal.2c03245
Lomont, J. P., Ralbovsky, N. M., Guza, C., Saha-Shah, A., Burzynski, J., Konietzko, J., Wang, S.-C., McHugh, P. M., Mangion, I., & Smith, J. P. (2022). Process monitoring of polysaccharide deketalization for vaccine bioconjugation development using in situ analytical methodology. Journal of Pharmaceutical and Biomedical Analysis, 209, 114533. https://doi.org/10.1016/j.jpba.2021.114533
Malig, T. C., Kumar, A., & Kurita, K. L. (2022). Online and In Situ Monitoring of the Exchange, Transmetalation, and Cross-Coupling of a Negishi Reaction. Organic Process Research & Development, 26(5), 1514–1519. https://doi.org/10.1021/acs.oprd.2c00081
Spöring, J., Wiesenthal, J., Pfennig, V., Gätgens, J., Beydoun, K., Bolm, C., Klankermayer, J., & Rother, D. (2022). Effective production of selected dioxolanes by sequential bio‐ and chemocatalysis enabled by adapted solvent switching. Chemsuschem, 16(2). https://doi.org/10.1002/cssc.202201981
Wheelhouse, K. M. P., Fenner, S., & Whiting, M. (2022). Application of High-Throughput experimentation in identification of conditions for selective nitro group hydrogenation. In Acs Symposium Series (pp. 79–91). https://doi.org/10.1021/bk-2022-1420.ch005

2021

Ashworth, I. W., Frodsham, L., Moore, P., & Ronson, T. O. (2021). Evidence of Rate Limiting Proton Transfer in an SNAr Aminolysis in Acetonitrile under Synthetically Relevant Conditions. The Journal of Organic Chemistry. https://doi.org/10.1021/acs.joc.1c01768
Jurica, J. A., & McMullen, J. P. (2021). Automation Technologies to Enable Data-Rich Experimentation: Beyond Design of Experiments for Process Modeling in Late-Stage Process Development. Organic Process Research & Development, 25(2), 282–291. https://doi.org/10.1021/acs.oprd.0c00496
Kukor, A. J., Guy, M. A., Hawkins, J. M., & Hein, J. E. (2021). A robust new tool for online solution-phase sampling of crystallizations. Reaction Chemistry and Engineering, 6(11), 2042–2049. https://doi.org/10.1039/d1re00284h
Pollack, S. R., & Dion, A. (2021). Metal-Free Stereoselective Synthesis of (E)- and (Z)-N-Monosubstituted β-Aminoacrylates via Condensation Reactions of Carbamates. The Journal of Organic Chemistry, 86(17), 11748–11762. https://doi.org/10.1021/acs.joc.1c01212
Zhao, X., Webb, N. J., Muehlfeld, M. P., Stottlemyer, A. L., & Russell, M. W. (2021). Application of a Semiautomated Crystallizer to Study Oiling-Out and Agglomeration Events—A Case Study in Industrial Crystallization Optimization. Organic Process Research & Development, 25(3), 564–575. https://doi.org/10.1021/acs.oprd.0c00494

2020

Malig, T. C., Yunker, L. P. E., Steiner, S., & Hein, J. E. (2020). Online High-Performance Liquid Chromatography Analysis of Buchwald–Hartwig Aminations from within an Inert Environment. ACS Catalysis, 10(22), 13236–13244. https://doi.org/10.1021/acscatal.0c03530
Malig, T. C., Tan, Y., Wisniewski, S. R., Higman, C. S., Carrasquillo-Flores, R., Ortiz, A., Purdum, G. E., Kolotuchin, S., & Hein, J. E. (2020). Development of a telescoped synthesis of 4-(1H)-cyanoimidazole core accelerated by orthogonal reaction monitoring. Reaction Chemistry & Engineering, 5(8), 1421–1428. https://doi.org/10.1039/d0re00234h

2019

Beutner, G. L., Coombs, J. R., Green, R. A., Inankur, B., Lin, D., Qiu, J., Roberts, F., Simmons, E. M., & Wisniewski, S. R. (2019). Palladium-Catalyzed Amidation and Amination of (Hetero)aryl Chlorides under Homogeneous Conditions Enabled by a Soluble DBU/NaTFA Dual-Base System. Organic Process Research & Development, 23(8), 1529–1537. https://doi.org/10.1021/acs.oprd.9b00196
Carter, H. L., Connor, A. W., Hart, R., McCabe, J., McIntyre, A. C., McMillan, A. E., Monks, N. R., Mullen, A. K., Ronson, T. O., Steven, A., Tomasi, S., & Yates, S. D. (2019). Rapid route design of AZD7594. Reaction Chemistry & Engineering, 4(9), 1658–1673. https://doi.org/10.1039/c9re00118b
Huffman, M. A., Fryszkowska, A., Alvizo, O., Borra-Garske, M., Campos, K. R., Canada, K. A., Devine, P. N., Duan, D., Forstater, J. H., Grosser, S. T., Halsey, H. M., Hughes, G. J., Jo, J., Joyce, L. A., Kolev, J. N., Liang, J., Maloney, K. M., Mann, B. F., Marshall, N. M., & McLaughlin, M. (2019). Design of an in vitro biocatalytic cascade for the manufacture of islatravir. Science, 366(6470), 1255–1259. https://doi.org/10.1126/science.aay8484
Mennen, S. M., Alhambra, C., Allen, C. L., Barberis, M., Berritt, S., Brandt, T. A., Campbell, A. D., Castañón, J., Cherney, A. H., Christensen, M., Damon, D. B., Eugenio de Diego, J., García-Cerrada, S., García-Losada, P., Haro, R., Janey, J., Leitch, D. C., Li, L., Liu, F., Lobben, P. C., MacMillan, D. W. C., Magano, J., McInturff, E., Monfette, S., Post, R. J., Schultz, D., Sitter, B., Stevens, J. M., Strambeanu, I. I., Twilton, J., Wang, K., & Zajac, M. A. (2019). The Evolution of High-Throughput Experimentation in Pharmaceutical Development and Perspectives on the Future. Organic Process Research & Development, 23(6), 1213–1242. https://doi.org/10.1021/acs.oprd.9b00140
Wang, K., Han, L., Mustakis, J., Li, B., Magano, J., Damon, D. B., Dion, A., Maloney, M. T., Post, R., & Li, R. (2019). Kinetic and Data-Driven Reaction Analysis for Pharmaceutical Process Development. Industrial & Engineering Chemistry Research, 59(6), 2409–2421. https://doi.org/10.1021/acs.iecr.9b03578

2018

Nykaza, T. V., Ramirez, A., Harrison, T. S., Luzung, M. R., & Radosevich, A. T. (2018). Biphilic Organophosphorus-Catalyzed Intramolecular Csp2–H Amination: Evidence for a Nitrenoid in Catalytic Cadogan Cyclizations. Journal of the American Chemical Society, 140(8), 3103–3113. https://doi.org/10.1021/jacs.7b13803

2017

Malig, T. C., Koenig, J. D. B., Situ, H., Chehal, N. K., Hultin, P. G., & Hein, J. E. (2017). Real-time HPLC-MS reaction progress monitoring using an automated analytical platform. Reaction Chemistry & Engineering, 2(3), 309–314. https://doi.org/10.1039/c7re00026j
Rougeot, C., Situ, H., Cao, B. H., Vlachos, V., & Hein, J. E. (2017). Automated reaction progress monitoring of heterogeneous reactions: crystallization-induced stereoselectivity in amine-catalyzed aldol reactions. Reaction Chemistry & Engineering, 2(2), 226–231. https://doi.org/10.1039/c6re00211k
Zawatzky, K., Grosser, S., & Welch, C. J. (2017). Facile kinetic profiling of chemical reactions using MISER chromatographic analysis. Tetrahedron, 73(33), 5048–5053. https://doi.org/10.1016/j.tet.2017.05.048

2016

Duan, S., Place, D., Perfect, H. H., Ide, N. D., Maloney, M., Sutherland, K., Price Wiglesworth, K. E., Wang, K., Olivier, M., Kong, F., Leeman, K., Blunt, J., Draper, J., McAuliffe, M., O’Sullivan, M., & Lynch, D. (2016). Palbociclib Commercial Manufacturing Process Development. Part I: Control of Regioselectivity in a Grignard-Mediated SNAr Coupling. Organic Process Research & Development, 20(7), 1191–1202. https://doi.org/10.1021/acs.oprd.6b00070
Gurung, S. R., Mitchell, C., Huang, J., Jonas, M., Strawser, J. D., Daia, E., Hardy, A., O’Brien, E., Hicks, F., & Papageorgiou, C. D. (2016). Development and Scale-up of an Efficient Miyaura Borylation Process Using Tetrahydroxydiboron. Organic Process Research & Development, 21(1), 65–74. https://doi.org/10.1021/acs.oprd.6b00345

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