The multicellular tumor spheroid model for high-throughput cancer drug discovery

Daniel V LaBarbera1, Brian G Reid, Byong Hoon Yoo

  • 1The University of Colorado Denver, The Skaggs School of Pharmacy and Pharmaceutical Sciences the University of Colorado AMC, The Department of Pharmaceutical Sciences, 12850 East Montview Blvd Aurora Colorado C238, USA. Daniel.LaBarbera@ucdenver.edu

Abstract

Insights

Three-dimensional (3D) multicellular tumor spheroid (MCTS) models offer improved prediction of in vivo efficacy for cancer drug discovery. Overcoming challenges in MCTS culture, data collection, and analysis is key to advancing high-throughput screening (HTS).

Area of Science:

  • Oncology
  • Drug Discovery
  • Biotechnology

Background:

  • Traditional 2D cell-based assays have limitations in predicting in vivo cancer drug efficacy.
  • This has led to high costs and low success rates in translating new cancer drugs.
  • Advances in 3D cell culture models offer a promising alternative.

Purpose of the Study:

  • To review the utility of multicellular tumor spheroids (MCTS) for high-throughput screening (HTS) in cancer drug discovery.
  • To discuss current technologies for MCTS culture and detection methods for assay development.
  • To highlight challenges and future directions for MCTS-based drug screening.

Main Methods:

  • Focus on multicellular tumor spheroid (MCTS) models for HTS drug discovery.
  • Review of current technologies for uniform MCTS culture.
  • Discussion of detection methods for assay development and drug screening.

Main Results:

  • MCTS models show potential to bridge the gap between 2D assays and in vivo studies.
  • Current technologies enable uniform MCTS culture suitable for HTS.
  • Various detection methods can be employed for assay development and drug screening.

Conclusions:

  • Hurdles in MCTS growth, data collection, and analysis need to be addressed for robust HTS.
  • Integrating fluorescent readouts, high-content imaging, and systems biology approaches is recommended.
  • MCTS models, when optimized, can improve the predictive power of preclinical cancer drug discovery.

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