2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Multistep automated synthesis of pharmaceuticals

      , , , ,
      Trends in Chemistry
      Elsevier BV

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references86

          • Record: found
          • Abstract: found
          • Article: not found

          A mobile robotic chemist

          Technologies such as batteries, biomaterials and heterogeneous catalysts have functions that are defined by mixtures of molecular and mesoscale components. As yet, this multi-length-scale complexity cannot be fully captured by atomistic simulations, and the design of such materials from first principles is still rare1-5. Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches6-14 but their widespread adoption in materials research is challenging because of the diversity of sample types, operations, instruments and measurements required. Here we use a mobile robot to search for improved photocatalysts for hydrogen production from water15. The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm16-18. This autonomous search identified photocatalyst mixtures that were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous19,20 free-roaming robot21-24, automating the researcher rather than the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A robotic platform for flow synthesis of organic compounds informed by AI planning

            The synthesis of complex organic molecules requires several stages, from ideation to execution, that require time and effort investment from expert chemists. Here, we report a step toward a paradigm of chemical synthesis that relieves chemists from routine tasks, combining artificial intelligence–driven synthesis planning and a robotically controlled experimental platform. Synthetic routes are proposed through generalization of millions of published chemical reactions and validated in silico to maximize their likelihood of success. Additional implementation details are determined by expert chemists and recorded in reusable recipe files, which are executed by a modular continuous-flow platform that is automatically reconfigured by a robotic arm to set up the required unit operations and carry out the reaction. This strategy for computer-augmented chemical synthesis is demonstrated for 15 drug or drug-like substances.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Deciding whether to go with the flow: evaluating the merits of flow reactors for synthesis.

              The fine chemicals and pharmaceutical industries are transforming how their products are manufactured, where economically favorable, from traditional batchwise processes to continuous flow. This evolution is impacting synthetic chemistry on all scales-from the laboratory to full production. This Review discusses the relative merits of batch and micro flow reactors for performing synthetic chemistry in the laboratory.
                Bookmark

                Author and article information

                Contributors
                Journal
                Trends in Chemistry
                Trends in Chemistry
                Elsevier BV
                25895974
                June 2023
                June 2023
                : 5
                : 6
                : 432-445
                Article
                10.1016/j.trechm.2023.03.008
                c55e023d-7578-4c3a-bb74-6b398233fd76
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://www.elsevier.com/open-access/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

                History

                Comments

                Comment on this article