Self-optimisation of the final stage in the synthesis of EGFR kinase inhibitor AZD9291 using an automated flow reactor

Holmes, Nicholas P.; Akien, Geoffrey R.; Blacker, A. John; Woodward, Robert L.; Meadows, Rebecca E.; Bourne, Richard A.

doi:10.1039/c6re00059b

Cited by 99 publications

(74 citation statements)

References 37 publications

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“…This optimization is still predominantly performed by the experimentalist in labor‐intensive batch reactions, typically allowing only a few experiments per day . Thanks to the rapid technological change combined with a much stronger interplay between chemical synthesis and the engineering disciplines, this drawback was recently overcome, as documented by reports on, e.g., self‐optimizing automated flow reactors, algorithm‐based optimum catalyst selection, or the discovery of new reactivities by an organic synthesis robot using machine learning . Importantly, all these studies utilize platforms that fully‐automatically collect a large amount of data in a short period of time with the general ambition to transform synthetic chemistry into a more data‐driven discipline ,…”

Section: Introductionmentioning

confidence: 99%

Kinetics Studies on a Multicomponent Knoevenagel−Michael Domino Reaction by an Automated Flow Reactor

Haas

Tallarek

2019

ChemistryOpen

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The optimization of complex chemical reaction systems is often a troublesome and time‐consuming process. The application of modern technologies, including automated reactors and analytics, opens the avenue for generating large data sets on chemical reaction processes in a short period of time. In this work, an automated flow reactor is used to present detailed kinetics and mechanistic studies about an amine‐catalyzed Knoevenagel−Michael domino reaction to yield tetrahydrochromene derivatives. High‐performance monoliths as catalyst supports and online coupled HPLC analysis allow for time‐efficient data generation. We show that the two‐step multicomponent domino reaction does not follow the kinetics of consecutive reaction steps proceeding independently from each other. Instead, the starting materials of both individual reactions compete for the active sites on the heterogeneous catalyst, which lowers the rate constants of both steps. This knowledge was used to implement a more efficient experimental setup which increased the turnover numbers of the catalyst, without adjusting common reaction parameters like temperature, reaction time, and concentrations.

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Section: Introductionmentioning

confidence: 99%

Kinetics Studies on a Multicomponent Knoevenagel−Michael Domino Reaction by an Automated Flow Reactor

Haas

Tallarek

2019

ChemistryOpen

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“…They were able to gather multistep kinetic information about an ucleophilic aromatic substitution (Scheme 15 A) [117] and showed self-optimization of different reactions with their systems (Scheme 15 B,C). [118] There is even emerging support for the notion of "artificial imagination" (Figure 6), which has the theoretical potential to enable the automated design of new molecular functions.F or example,l ast year, the Google AI AlphaGo won ag ame of Go against ap rofessional human player by utilizing human-like imagination. Thet eam used general machine learning techniques to create as ystem that learned on its own.…”

Section: Automating Reaction Optimization Molecular Design and Funcmentioning

confidence: 99%

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules

2018

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The eighteenth and nineteenth centuries marked a sweeping transition from manual to automated manufacturing on the macroscopic scale. This enabled an unmatched period of human innovation that helped drive the Industrial Revolution. The impact on society was transformative, ultimately yielding substantial improvements in living conditions and lifespan in many parts of the world. During the same time period, the first manual syntheses of organic molecules was achieved. Now, two centuries later, we are poised for an analogous transition from highly customized crafting of specific molecular targets by hand to the increasingly general and automated assembly of many different types of molecules with the push of a button. Automation of customized small molecule synthesis pathways is already enabling safer, more reproducible, and readily scalable production of specific targets, and general machines now exist for the synthesis of a wide range of different peptides, oligonucleotides, and oligosaccharides. Creating general machines that are similarly capable of making many different types of small molecules on-demand, akin to that which has been achieved on the macroscopic scale with 3D printers, has proven to be substantially more challenging. Yet important progress is being made toward this potentially transformative objective with two complementary approaches: (1) automation of customized synthesis routes to different targets via machines that enable use of many different reactions and starting materials, and (2) automation of generalized platforms that make many different targets using common coupling chemistry and building blocks. Continued progress in these exciting directions has the potential to shift the bottleneck in molecular innovation from synthesis to imagination, and thereby help drive a new industrial revolution on the molecular scale.

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“…78,[87][88][89][92][93][94] Realization of production scale API synthesis cannot be imagined without strict control of processes and final product quality. 25 These efforts are exemplified by the production of Artemisinin related APIs, where monitoring of the reaction stream after a photochemical transformation could reveal an eventual lamp failure.…”

Section: Successful Applicationsmentioning

confidence: 99%

The route from problem to solution in multistep continuous flow synthesis of pharmaceutical compounds

Bana

Örkényi

Lövei

et al. 2017

Bioorganic & Medicinal Chemistry

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a b s t r a c tRecent advances in the field of continuous flow chemistry allow the multistep preparation of complex molecules such as APIs (Active Pharmaceutical Ingredients) in a telescoped manner. Numerous examples of laboratory-scale applications are described, which are pointing towards novel manufacturing processes of pharmaceutical compounds, in accordance with recent regulatory, economical and quality guidances. The chemical and technical knowledge gained during these studies is considerable; nevertheless, connecting several individual chemical transformations and the attached analytics and purification holds hidden traps. In this review, we summarize innovative solutions for these challenges, in order to benefit chemists aiming to exploit flow chemistry systems for the synthesis of biologically active molecules.

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Self-optimisation of the final stage in the synthesis of EGFR kinase inhibitor AZD9291 using an automated flow reactor

Abstract: Self-optimising flow reactors combine online analysis with evolutionary feedback algorithms to rapidly achieve optimum conditions.

Cited by 99 publications

References 37 publications

Kinetics Studies on a Multicomponent Knoevenagel−Michael Domino Reaction by an Automated Flow Reactor

Kinetics Studies on a Multicomponent Knoevenagel−Michael Domino Reaction by an Automated Flow Reactor

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules

The route from problem to solution in multistep continuous flow synthesis of pharmaceutical compounds

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