Drug Discovery, Pharmaceuticals & Cannabis Testing
Compound library generation using fl ow chemistry Andrew Mansfi eld, Flow Chemistry Leader, Syrris, Part of the AGI Group, UK
The use of fl ow chemistry to generate compound libraries for screening against a biological target enables faster exploration of potential drug candidates, accelerating early drug discovery projects. Modern, modular fl ow chemistry platforms offer many benefi ts over traditional batch processes, increasing the scope of reactions that can be performed while improving both reproducibility and cost compared to the equivalent manual synthesis. This article discusses the advantages of using fl ow chemistry for library generation – from streamlined workfl ows that enhance effi ciency to the automation of complex syntheses – and describes how the technology can be complemented by under-used techniques such as photochemistry and electrochemistry. It also explores how machine learning or AI-based automation could potentially be coupled with fl ow chemistry to change the drug discovery landscape of the future.
The benefi ts of fl ow chemistry have seen this enabling technology applied to a growing number of applications over recent years. One such application is early phase drug discovery, where it is being used to generate libraries of compounds for screening against a biological target of interest, allowing the faster exploration of potential drug candidates. The use of fl ow chemistry for compound library generation has many benefi ts over traditional batch protocols, offering improved reproducibility and cost compared to equivalent manual syntheses. Even when compared to automated batch processes, fl ow chemistry approaches increase the scope of reactions that can be performed, and enable several operations to be telescoped together, allowing more effi cient processing for further cost reductions.
Challenges with traditional batch methods
Organic synthesis is currently dominated by batch processes, with iterative generation of compounds over multiple steps. Each step involves synthesis in a round-bottomed fl ask or batch reactor of some sort (96-well plates are often adopted for batch library synthesis), then subsequent isolation and purifi cation before the next step is carried out (Figure 1). This process is a mainstay of compound library generation in drug discovery, partly due to the complexity of the syntheses being performed.
More recently, automation of batch reactions – using liquid handlers and automated purifi cation platforms – has aided the development of parallel / combinatorial library generation by allowing miniaturisation of reactions. However, library synthesis through these techniques is limited as reaction scales are decreased. The scope of chemistry available often delivers low yielding and unreliable reactions, requiring extensive re-optimisation during subsequent resynthesis and scale-up. In addition, the time- consuming purifi cation needed after each reaction step wastes resources and delays the delivery of the fi nal compounds, resulting in signifi cant time delays between design of the experiment and obtaining the results. This limits the number of compounds that can be advanced into clinical studies and, ultimately, has a huge impact on the timelines and success rates of the drug discovery process.
optimisation. Users can simply synthesise exploratory compounds on a small scale for screening, then resynthesise larger amounts using the same methodology later.
Figure 2: A multistep synthesis approach using fl ow chemistry techniques. Automating fl ow chemistry
The ability to automate any chemical process not only frees up chemists to perform other tasks, but also provides more precise control of reagent additions, mixing rates, temperatures and pressures – as well as robust data logging and recording – helping to improve overall process reproducibility and, therefore, performance. This strategy lends itself well to fl ow chemistry approaches, allowing the full automation of experiments with increasing complexity. Using modular fl ow chemistry systems, chemists can control various devices in concert to perform multiple operations as part of a continuous process. These modular platforms can also combine heated or cooled fl ow reactors with access to previously restricted or underused activation methods, such as photochemistry and electrochemistry. Furthermore, state-of-the-art fl ow chemistry platforms can couple synthesis with in-line purifi cation and analysis – to work-up and identify what’s been made – to create platforms capable of further shortening the medicinal chemistry discovery process [1,2]. This modular approach makes it possible to combine multiple techniques to synthesise molecules over several reaction steps as part of a truly continuous process (Figure 3), then simply reconfi gure the system as required [3].
Figure 1: Synthetic workfl ow using traditional batch techniques. Figure 3: Multistep synthesis approach using fl ow chemistry techniques. Flow chemistry methods for library generation
Flow chemistry platforms are increasingly being used to help address these challenges with library generation. This approach increases the available chemical space and range of chemistries suitable for automation, as well as improving the effi ciency, safety, and environmental impact of workfl ows. The core benefi t of fl ow chemistry is that it enables researchers to perform chemistries in series, integrating downstream processes to reduce work-up and isolation steps in a single experiment (Figure 2). It can reduce both the time and costs associated with library generation, offering fast process optimisation and the straightforward preparation of diverse compound series to increase the scope of early stages of drug discovery programs, providing valuable additional information that could increases the chances of success. It also offers a direct route to scaling-up synthesis of hit or lead compounds without the need for re-
Flow automation for reaction optimisation
Automated experimentation can be used to rapidly optimise reaction conditions and evaluate novel methodologies, running a series of experiments to explore a full range of reaction parameters (Figure 4) [1]. Researchers can quickly screen continuous parameters such as residence time, reaction stoichiometry, reaction temperature and pressure. Automated reagent injectors can also be employed to explore discontinuous reaction parameters, such as reagent, catalyst or enzyme screening. With the correct control software, it is also possible to import fi les from Design of Experiment (DoE) software, making the process even more effi cient. Once the optimum reaction conditions for a process have been identifi ed, these can be used to synthesise a library of compounds, or to process larger quantities of material for downstream development.
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