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Updated: Aug 31, 2025

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Rapid tissue prototyping with micro-organospheres.

Zhaohui Wang1, Matteo Boretto2, Rosemary Millen2

  • 1Woo Center for Big Data and Precision Health, Pratt School of Engineering, Duke University, Durham, NC, USA.

Stem Cell Reports
|August 19, 2022
PubMed
Summary
This summary is machine-generated.

Micro-organospheres (MOSs) are rapid, 3D tissue models created using microfluidics. These models accurately predict drug responses, offering a high-throughput platform for precision medicine advancements.

Keywords:
CAR-TSARS-COV-2cytostaticcytotoxicdeep learningdemulsificationdrug resistantmicro-organospheresorganoidpatient derived organoid

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Area of Science:

  • Biotechnology
  • 3D Tissue Models
  • Microfluidics

Background:

  • In vitro tissue models are crucial for disease and drug response research.
  • Existing models like organoids have limitations in speed and scalability.

Purpose of the Study:

  • To develop a rapid, scalable, and accurate in vitro 3D tissue model.
  • To establish a high-throughput platform for therapeutic profiling and precision medicine.

Main Methods:

  • Emulsion microfluidics to generate micro-organospheres (MOSs) from patient tissues/cells.
  • Development of an automated imaging pipeline with machine learning for MOS analysis.
  • Quantitative assessment of nutrient dependence, pathogen-host interactions, and CAR-T therapy potency.

Main Results:

  • MOSs demonstrated retention of biological features and drug response profiles comparable to organoids.
  • The automated pipeline successfully addressed plating variations and distinguished cellular components.
  • Accurate differentiation of cytostatic vs. cytotoxic effects and identification of drug-resistant clones were achieved.

Conclusions:

  • MOSs represent a promising advancement in 3D in vitro tissue modeling.
  • The integrated imaging and machine learning pipeline enables robust, high-throughput drug response assessment.
  • This platform accelerates therapeutic profiling for precision medicine applications.