Publications
Browse peer-reviewed literature, posters, webinars, blog articles, and more showing how we and others are using RepliGut Systems to support discovery.
2025
Pike, Colleen M.; Levi, James A.; Boone, Lauren A.; Peddibhotla, Swetha; Johnson, Jacob; Zwarycz, Bailey; Bunger, Maureen K.; Thelin, William; Boazak, Elizabeth M.
High-throughput assay for predicting diarrhea risk using a 2D human intestinal stem cell-derived model Journal Article
In: Toxicology In Vitro, vol. 106, pp. 106040, 2025, ISSN: 0887-2333.
Abstract | Links | BibTeX | Tags: Adverse events, Diarrhea, Epithelium, High throughput, In vitro model, Intestine
@article{pike_high-throughput_2025,
title = {High-throughput assay for predicting diarrhea risk using a 2D human intestinal stem cell-derived model},
author = {Colleen M. Pike and James A. Levi and Lauren A. Boone and Swetha Peddibhotla and Jacob Johnson and Bailey Zwarycz and Maureen K. Bunger and William Thelin and Elizabeth M. Boazak},
url = {https://www.sciencedirect.com/science/article/pii/S0887233325000347},
doi = {10.1016/j.tiv.2025.106040},
issn = {0887-2333},
year = {2025},
date = {2025-06-01},
urldate = {2025-06-01},
journal = {Toxicology In Vitro},
volume = {106},
pages = {106040},
abstract = {Gastrointestinal toxicities (GITs) in clinical trials often lead to dose-limitations that reduce drug efficacy and delay treatment optimization. Preclinical animal models do not accurately replicate human physiology, leaving few options for early detection of GITs, such as diarrhea, before human studies. Chemotherapeutic agents, known to cause clinical diarrhea, frequently target mitotic cells. Therefore, we hypothesized a model utilizing proliferative cell populations derived from human intestinal crypts would predict clinical diarrhea occurrence with high accuracy. Here, we describe the development of a diarrhea prediction assay utilizing RepliGut® Planar, a primary intestinal stem cell-derived platform. To evaluate the ability of this model to predict clinical diarrhea risk, we assessed toxicity of 30 marketed drugs by measuring cell proliferation (EdU incorporation), cell abundance (nuclei quantification), and barrier formation (TEER) in cells derived from three human donors. Dose response curves were generated for each drug, and the IC15 to Cmax ratio was used to identify a threshold for assay positivity. This model accurately predicted diarrhea potential, achieving an accuracy of 91 % for proliferation, 90 % for abundance, and 88 % for barrier formation. In vitro toxicity screening using primary proliferative cells may reduce clinical diarrhea and ultimately lead to safer and more effective treatments for patients.},
keywords = {Adverse events, Diarrhea, Epithelium, High throughput, In vitro model, Intestine},
pubstate = {published},
tppubtype = {article}
}
Gastrointestinal toxicities (GITs) in clinical trials often lead to dose-limitations that reduce drug efficacy and delay treatment optimization. Preclinical animal models do not accurately replicate human physiology, leaving few options for early detection of GITs, such as diarrhea, before human studies. Chemotherapeutic agents, known to cause clinical diarrhea, frequently target mitotic cells. Therefore, we hypothesized a model utilizing proliferative cell populations derived from human intestinal crypts would predict clinical diarrhea occurrence with high accuracy. Here, we describe the development of a diarrhea prediction assay utilizing RepliGut® Planar, a primary intestinal stem cell-derived platform. To evaluate the ability of this model to predict clinical diarrhea risk, we assessed toxicity of 30 marketed drugs by measuring cell proliferation (EdU incorporation), cell abundance (nuclei quantification), and barrier formation (TEER) in cells derived from three human donors. Dose response curves were generated for each drug, and the IC15 to Cmax ratio was used to identify a threshold for assay positivity. This model accurately predicted diarrhea potential, achieving an accuracy of 91 % for proliferation, 90 % for abundance, and 88 % for barrier formation. In vitro toxicity screening using primary proliferative cells may reduce clinical diarrhea and ultimately lead to safer and more effective treatments for patients.
2018
Gunasekara, Dulan B.; Speer, Jennifer; Wang, Yuli; Nguyen, Daniel L.; Reed, Mark I.; Smiddy, Nicole M.; Parker, Joel S.; Fallon, John K.; Smith, Philip C.; Sims, Christopher E.; Magness, Scott T.; Allbritton, Nancy L.
A monolayer of primary colonic epithelium generated on a scaffold with a gradient of stiffness for drug transport studies Journal Article
In: vol. 90, no. 22, pp. 13331, 2018, (Publisher: NIH Public Access).
Abstract | Links | BibTeX | Tags: Atenolol, Biological Transport, Caco-2 Cells, Colon, Epithelium, Humans, Propranolol, Riboflavin, Tissue Engineering
@article{gunasekara_monolayer_2018,
title = {A monolayer of primary colonic epithelium generated on a scaffold with a gradient of stiffness for drug transport studies},
author = {Dulan B. Gunasekara and Jennifer Speer and Yuli Wang and Daniel L. Nguyen and Mark I. Reed and Nicole M. Smiddy and Joel S. Parker and John K. Fallon and Philip C. Smith and Christopher E. Sims and Scott T. Magness and Nancy L. Allbritton},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339567/},
doi = {10.1021/acs.analchem.8b02845},
year = {2018},
date = {2018-11-11},
urldate = {2018-11-11},
volume = {90},
number = {22},
pages = {13331},
abstract = {Animal models are frequently used for in vitro physiologic and drug transport studies of the colon, but there exists significant pressure to improve assay throughput as well as achieve tighter control of experimental variables than can be achieved with ...},
note = {Publisher: NIH Public Access},
keywords = {Atenolol, Biological Transport, Caco-2 Cells, Colon, Epithelium, Humans, Propranolol, Riboflavin, Tissue Engineering},
pubstate = {published},
tppubtype = {article}
}
Animal models are frequently used for in vitro physiologic and drug transport studies of the colon, but there exists significant pressure to improve assay throughput as well as achieve tighter control of experimental variables than can be achieved with ...