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MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery.

Cara E BrocklehurstEva AltmannCorentin BonHolly DavisDavid DunstanPeter ErtlCarol Ginsburg-MoraffJonathan GrobDaniel J GoslingGuillaume LapointeAlexander N MarzialeHeinrich MuesMarco PalmieriSophie RacineRichard I RobinsonClayton SpringerKian L TanWilliam UlmerRené Wyler
Published in: Journal of medicinal chemistry (2024)
We herein describe the development and application of a modular technology platform which incorporates recent advances in plate-based microscale chemistry, automated purification, in situ quantification, and robotic liquid handling to enable rapid access to high-quality chemical matter already formatted for assays. In using microscale chemistry and thus consuming minimal chemical matter, the platform is not only efficient but also follows green chemistry principles. By reorienting existing high-throughput assay technology, the platform can generate a full package of relevant data on each set of compounds in every learning cycle. The multiparameter exploration of chemical and property space is hereby driven by active learning models. The enhanced compound optimization process is generating knowledge for drug discovery projects in a time frame never before possible.
Keyphrases
  • drug discovery
  • high throughput
  • single cell
  • healthcare
  • machine learning
  • minimally invasive
  • big data
  • deep learning
  • ionic liquid
  • robot assisted
  • sensitive detection