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Multiparametric Assays for Accelerating Early Drug Discovery.

Alexander Herholt1, Sabrina Galinski1, Philipp E Geyer2

  • 1Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany.

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Drug discovery faces high failure rates due to efficacy and safety issues, especially in complex diseases. Innovative assays and mass spectrometry proteomics can improve profiling of drug candidates for better drug discovery and personalized medicine.

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Area of Science:

  • Biochemistry
  • Pharmacology
  • Biotechnology

Background:

  • Drug discovery campaigns suffer from high attrition rates, primarily due to efficacy and safety concerns of candidate drugs.
  • Genetically complex diseases exacerbate attrition due to limited understanding of drug actions on targets and pathways.
  • Elucidating complex cellular signaling networks requires innovative technologies for better drug profiling.

Purpose of the Study:

  • To discuss advancements in genetically encoded multiparametric assays and mass spectrometry (MS)-based proteomics.
  • To highlight the potential of these technologies in profiling multifactorial drug actions.
  • To promote improved drug discovery and personalized medicine.

Main Methods:

  • Genetically encoded multiparametric assays for profiling compound actions.
  • Mass spectrometry (MS)-based proteomics for target and pathway analysis.
  • Utilizing disease-relevant cellular systems to assess drug candidates.

Main Results:

  • Genetically encoded assays offer multiparametric profiling of drug candidates.
  • MS-based proteomics provides comprehensive analysis of target engagement and pathway modulation.
  • These toolkits enhance the understanding of drug actions in complex biological systems.

Conclusions:

  • Innovative technologies like genetically encoded assays and MS-based proteomics are crucial for overcoming drug discovery attrition.
  • These methods enable better profiling of drug candidates' effects on targets and pathways.
  • Advancements facilitate more effective drug discovery and the development of personalized medicine approaches.