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      Automating drug discovery

      Nature Reviews Drug Discovery
      Springer Nature

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          Abstract

          Small-molecule drug discovery can be viewed as a challenging multidimensional problem in which various characteristics of compounds - including efficacy, pharmacokinetics and safety - need to be optimized in parallel to provide drug candidates. Recent advances in areas such as microfluidics-assisted chemical synthesis and biological testing, as well as artificial intelligence systems that improve a design hypothesis through feedback analysis, are now providing a basis for the introduction of greater automation into aspects of this process. This could potentially accelerate time frames for compound discovery and optimization and enable more effective searches of chemical space. However, such approaches also raise considerable conceptual, technical and organizational challenges, as well as scepticism about the current hype around them. This article aims to identify the approaches and technologies that could be implemented robustly by medicinal chemists in the near future and to critically analyse the opportunities and challenges for their more widespread application.

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          Most cited references190

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          Microfluidics: Fluid physics at the nanoliter scale

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            The medicinal chemist's toolbox: an analysis of reactions used in the pursuit of drug candidates.

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              The influence of drug-like concepts on decision-making in medicinal chemistry.

              The application of guidelines linked to the concept of drug-likeness, such as the 'rule of five', has gained wide acceptance as an approach to reduce attrition in drug discovery and development. However, despite this acceptance, analysis of recent trends reveals that the physical properties of molecules that are currently being synthesized in leading drug discovery companies differ significantly from those of recently discovered oral drugs and compounds in clinical development. The consequences of the marked increase in lipophilicity--the most important drug-like physical property--include a greater likelihood of lack of selectivity and attrition in drug development. Tackling the threat of compound-related toxicological attrition needs to move to the mainstream of medicinal chemistry decision-making.
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                Author and article information

                Journal
                Nature Reviews Drug Discovery
                Nat Rev Drug Discov
                Springer Nature
                1474-1776
                1474-1784
                December 15 2017
                December 15 2017
                :
                :
                Article
                10.1038/nrd.2017.232
                29242609
                094ce7c3-5749-46b2-ad6e-9f6feefa6ae5
                © 2017
                History

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