Automated platforms for reaction self-optimization in flow

Automation is a reality in everyday life, including in the chemical synthesis environment. It relegates time-consuming and repetitive tasks to machines, saving time for other activities that provide more value to scientists. The development of intelligent feedback controls applying novel algorithms with real-time reaction analysis and their combination with automation bring new opportunities for discovery, process optimization and work-up processes, that until now have been conducted using traditional manual procedures. Furthermore, the current trend is to increase the autonomy of automated platforms that can guide the optimization process with minimal human intervention (self-optimization). This article highlights recent progress in continuous flow self-optimizing platforms. Monitoring techniques, intelligent algorithms, as well as the autonomous platforms utilized are discussed.

[1]  Jeffrey M. Perkel,et al.  The Internet of Things comes to the lab , 2017, Nature.

[2]  J. M. Taboada,et al.  Reversible Clustering of Gold Nanoparticles under Confinement , 2018, Angewandte Chemie.

[3]  Robert L. Woodward,et al.  Self-optimisation of the final stage in the synthesis of EGFR kinase inhibitor AZD9291 using an automated flow reactor , 2016 .

[4]  Klavs F Jensen,et al.  Reconfigurable system for automated optimization of diverse chemical reactions , 2018, Science.

[5]  Geoffrey S. F. Ling,et al.  Pharmacy on demand: New technologies to enable miniaturized and mobile drug manufacturing. , 2016, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

[6]  Richard N. Zare,et al.  Optimizing Chemical Reactions with Deep Reinforcement Learning , 2017, ACS central science.

[7]  Piotr Dittwald,et al.  Computer-Assisted Synthetic Planning: The End of the Beginning. , 2016, Angewandte Chemie.

[8]  Leroy Cronin,et al.  Towards dial-a-molecule by integrating continuous flow, analytics and self-optimisation. , 2016, Chemical Society reviews.

[9]  Magnus Rueping,et al.  Machine assisted reaction optimization: A self-optimizing reactor system for continuous-flow photochemical reactions , 2018, Tetrahedron.

[10]  Klavs F. Jensen,et al.  Photoredox Iridium–Nickel Dual-Catalyzed Decarboxylative Arylation Cross-Coupling: From Batch to Continuous Flow via Self-Optimizing Segmented Flow Reactor , 2018 .

[11]  Gurpur Rakesh D. Prabhu,et al.  The dawn of unmanned analytical laboratories , 2017 .

[12]  Magnus Rueping,et al.  Online monitoring and analysis for autonomous continuous flow self-optimizing reactor systems , 2016 .

[13]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[14]  Charlotte Truchet,et al.  Optimizing the Heck–Matsuda Reaction in Flow with a Constraint-Adapted Direct Search Algorithm , 2016 .

[15]  J. Panteleev,et al.  Recent applications of machine learning in medicinal chemistry. , 2018, Bioorganic & medicinal chemistry letters.

[16]  Kelly J Kilpin,et al.  Chemistry Central Journal themed issue: Dial-a-Molecule , 2015, Chemistry Central Journal.

[17]  John A. Nelder,et al.  Nelder-Mead algorithm , 2009, Scholarpedia.

[18]  Paul Richardson,et al.  A platform for automated nanomole-scale reaction screening and micromole-scale synthesis in flow , 2018, Science.

[19]  Arnold Neumaier,et al.  SNOBFIT -- Stable Noisy Optimization by Branch and Fit , 2008, TOMS.

[20]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[21]  T. Koloini,et al.  Effect of experimental error on the efficiency of different optimization methods for bioprocess media optimization , 2002, Bioprocess and biosystems engineering.

[22]  Martin Berggren,et al.  Hybrid differentiation strategies for simulation and analysis of applications in C++ , 2008, TOMS.

[23]  Jeffrey C. Lagarias,et al.  Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions , 1998, SIAM J. Optim..

[24]  Russ B Altman,et al.  Machine learning in chemoinformatics and drug discovery. , 2018, Drug discovery today.

[25]  Charlotte Truchet,et al.  An Autonomous Self-Optimizing Flow Reactor for the Synthesis of Natural Product Carpanone. , 2018, The Journal of organic chemistry.

[26]  J. Schrauwen,et al.  An open-source approach to automation in organic synthesis: The flow chemical formation of benzamides using an inline liquid-liquid extraction system and a homemade 3-axis autosampling/product-collection device , 2018, Tetrahedron.

[27]  Geoffrey R Akien,et al.  Enhanced process development using automated continuous reactors by self-optimisation algorithms and statistical empirical modelling , 2018, Tetrahedron.

[28]  M. Rubens,et al.  Precise Polymer Synthesis by Autonomous Self-Optimizing Flow Reactors. , 2019, Angewandte Chemie.

[29]  Steven V Ley,et al.  Continuous flow reaction monitoring using an on-line miniature mass spectrometer. , 2012, Rapid communications in mass spectrometry : RCM.

[30]  Marcus Grünewald,et al.  Roadmap for a Smart Factory: A Modular, Intelligent Concept for the Production of Specialty Chemicals. , 2018, Angewandte Chemie.

[31]  Yang Bai,et al.  OpenFlowChem – a platform for quick, robust and flexible automation and self-optimisation of flow chemistry , 2018 .

[32]  Klavs F Jensen,et al.  Feedback in Flow for Accelerated Reaction Development. , 2016, Accounts of chemical research.

[33]  Leroy Cronin,et al.  Organic synthesis in a modular robotic system driven by a chemical programming language , 2019, Science.

[34]  Richard Hansen,et al.  National Instruments LabVIEW: A Programming Environment for Laboratory Automation and Measurement , 2007 .

[35]  Claudio Battilocchio,et al.  A Novel Internet-Based Reaction Monitoring, Control and Autonomous Self-Optimization Platform for Chemical Synthesis , 2015 .

[36]  Alexei Lapkin,et al.  Self-optimisation and model-based design of experiments for developing a C–H activation flow process , 2017, Beilstein journal of organic chemistry.

[37]  Richard J Ingham,et al.  Integration of enabling methods for the automated flow preparation of piperazine-2-carboxamide , 2014, Beilstein journal of organic chemistry.

[38]  Sarah M. Kang,et al.  Pantropical climate interactions , 2019, Science.

[39]  Andreja Rojko,et al.  Industry 4.0 Concept: Background and Overview , 2017, Int. J. Interact. Mob. Technol..

[40]  Artur M. Schweidtmann,et al.  Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives , 2018, Chemical Engineering Journal.