Automated Sampling System | Inline, Unattended Reactor Sampling 24/7

Automated Sampling for Chemical Reactions

Increase productivity

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

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 and Reproducible

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

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.

hplc autoosampler

Ready for Critical Offline Analytics

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

chemical reaction sampling tools

Supports Reaction Understanding

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

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

automated reactor sampling system

automated reactor sampling system
automated reactor sampling system

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 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?

It is understood that sampling chemical reactions for offline analysis use analytical techniques to ascertain reaction status, yield, or impurity profiles. The sampling procedure, sadly, is not always an exact operation and poses difficulties for reactions involving heterogeneous mixtures, high temperatures, slurries, or air-sensitive chemistry. Delays in quenching can also result in extremely varied outcomes as well as erroneous and imprecise analytical data.

By offering an automated and reliable inline technique of acquiring representative samples from reactions, even under challenging circumstances, EasySampler was created to overcome these difficulties. Scientists have been using EasySampler to help their synthetic chemistry and process development work at Pfizer and other pharmaceutical businesses.

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: 

  1. Pressure range: 1.013 bar – 10 bar (14.7 psi – 145 psi) 
  2. Temperature range: 20 to 100 °C 
  3. Reactor volume: up to 2500 mL 
  4. Number of samples per sleeve: 1 reaction (with up to 24 samples)
  5. 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
  • Reduced contamination risk
  • 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.

 

autosampling of a slurry solution
pfizer automated sampling

Pfizer evaluerer automatisk prøvetaking for forbedret urenhetsprofilering

Uovervåket, representativ prøvetaking av et bredt spekter av kjemiske reaksjoner

pfizer autosampling

Sampling of Chemical Reactions at Pfizer

Automated Chemical Reaction Sampling

Det moderne synteselaboratoriet

Det moderne synteselaboratoriet

En ny arbeidsplass for kjemikere

Endpoint Detection of a Hydrogenation

Endpoint Detection of a Hydrogenation

Sampling Reactions at Elevated Pressure

Automated Chemical Sampling Systems in Journal Publications

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 both academia and industry to support data-rich experimentation to advance their research.

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
  • Kukor, A. J., St-Jean, F., Stumpf, A., Malig, T. C., Piechowicz, K. A., Kurita, K., & He...
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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 both academia and industry to support data-rich experimentation to advance their research.

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
  • Kukor, A. J., St-Jean, F., Stumpf, A., Malig, T. C., Piechowicz, K. A., Kurita, K., & Hein, J. E. (2023c). 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 Communications13(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 Catalysis12(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 Analysis209, 114533. https://doi.org/10.1016/j.jpba.2021.114533
  • Malig, T. C., Kumar, A., & Kurita, K. L. (2022b). Online and In Situ Monitoring of the Exchange, Transmetalation, and Cross-Coupling of a Negishi Reaction. Organic Process Research & Development26(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. Chemsuschem16(2). https://doi.org/10.1002/cssc.202201981
  • Wheelhouse, K. M. P., Fenner, S., & Whiting, M. (2022a). 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 & Development25(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 Chemistry86(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 & Development25(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 Catalysis10(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 & Engineering5(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 & Development23(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 & Engineering4(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. Science366(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 & Development23(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 Research59(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 & Engineering2(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. Tetrahedron73(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 & Development21(1), 65–74. https://doi.org/10.1021/acs.oprd.6b00345
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