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Updated: Feb 3, 2026

3D Microtissues for Injectable Regenerative Therapy and High-throughput Drug Screening
Published on: October 4, 2017
Human 3D Gastrointestinal Microtissue Barrier Function As a Predictor of Drug-Induced Diarrhea
Matthew F Peters1, Tim Landry2, Carmen Pin3
1Oncology Safety, Drug Safety and Metabolism, IMED Biotech Unit, AstraZeneca, Waltham, MA 02451.
This study introduces a novel human 3D gastrointestinal (GI) microtissue assay that accurately predicts drug-induced diarrhea. This advanced in vitro model offers improved preclinical safety assessment for new drug development.
Area of Science:
- Biomedical Engineering
- Toxicology
- Stem Cell Biology
Background:
- Drug-induced gastrointestinal toxicities (GITs) are common clinical side effects.
- Current in vitro assays lack predictive accuracy for GITs.
- Advancements in stem cell culture enable the creation of in vivo-like intestinal microtissues.
Purpose of the Study:
- To evaluate human GI microtissues for predicting drug-induced diarrhea.
- To assess the utility of transepithelial electrical resistance (TEER) as a measure of intestinal barrier function in microtissues.
- To establish a validated in vitro assay for preclinical drug safety screening.
Main Methods:
- Human GI microtissues were cultured in transwell plates for drug treatment.
- Transepithelial electrical resistance (TEER) was measured to assess intestinal barrier integrity.
- A validation set of drugs was tested, and TEER inhibition was correlated with clinical diarrhea incidence.
Main Results:
- The GI microtissue TEER assay accurately predicted diarrhea for a set of known drugs.
- The assay demonstrated high predictive power for drugs with unexpected diarrhea liabilities in animal studies.
- A mathematical model was developed to describe barrier damage and recovery dynamics.
Conclusions:
- Human 3D GI microtissues with TEER measurement represent the first validated in vitro assay for predicting diarrhea-inducing drugs.
- This assay can enhance preclinical drug development by improving lead optimization and dose schedule exploration.
- The model provides a valuable tool for identifying potential GITs early in the drug discovery process.
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