{"database":"BioModels","file_versions":[],"scores":null,"additional":{"submitter":["Carmen Pin"],"curationStatus":["Non-curated"],"modellingApproach":["ordinary differential equation model"],"levelVersion":["*"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/MODEL2509110001"],"publication_pubmed":["42033153"],"isPrivate":["false"],"repository":["BioModels"],"omics_type":["Models"],"modelFormat":["MATLAB (Octave)"],"tokenised_name":["Pin2025 Intestinal Organoids Model"],"publication_year":["2026"],"submissionId":["MODEL2509110001"],"publication_authors":["Carmen Pin, Deepa Maheshvare M., Louis Gall, Andrew Hall, Muireann Coen, Ambra Bianco, Shimeng Liu, Kenneth Pryde"],"first_author":["Carmen Pin"],"publication":["42033153,\n                            Gastrointestinal (GI) toxicity is a common and potentially severe side effect of antiproliferative cancer therapies that often requires dose reduction or treatment interruption. Despite the clinical implications, there are currently no robust strategies for quantitative preclinical assessment of GI toxicity. We have developed a human small intestinal organoid (hSIO)-based mathematical modeling approach for the early prediction of GI toxicity of oral antiproliferative cancer treatments. Our approach integrates the exposure-toxicity relationship quantified in hSIOs into a human mathematical model of the epithelium that enables the simulation of the impact of crypt proliferation impairment on epithelial dynamics. We show that, for oral drugs, when the enterocyte free drug concentration is used as a surrogate for the crypt exposure, the extent of the epithelial injury correlates with reported clinical incidence and severity of diarrhea. In contrast, when relying on plasma exposure, the model failed to predict intestinal injury for two out of the six diarrheagenic drugs tested. Our modeling approach distinguished the toxicity profiles of CDK4/6 inhibitors, predicting minimal epithelial injury for ribociclib and substantial epithelial disruption for abemaciclib, consistent with its higher clinical incidence of diarrhea. Similarly, the toxicity quantified in hSIOs enabled accurate prediction of epithelial injury and diarrhea severity for four epithelial growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). This approach introduces new GI safety assessment and clinical dose selection paradigms to enable the simulation of patients' response based upon in vitro drug response modeling.. 5, 15.\n                            Systems Medicine, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK."],"submitter_mail":["carmenpinster@gmail.com"],"pubmed_abstract":["Gastrointestinal (GI) toxicity is a common and potentially severe side effect of antiproliferative cancer therapies that often requires dose reduction or treatment interruption. Despite the clinical implications, there are currently no robust strategies for quantitative preclinical assessment of GI toxicity. We have developed a human small intestinal organoid (hSIO)-based mathematical modeling approach for the early prediction of GI toxicity of oral antiproliferative cancer treatments. Our approach integrates the exposure-toxicity relationship quantified in hSIOs into a human mathematical model of the epithelium that enables the simulation of the impact of crypt proliferation impairment on epithelial dynamics. We show that, for oral drugs, when the enterocyte free drug concentration is used as a surrogate for the crypt exposure, the extent of the epithelial injury correlates with reported clinical incidence and severity of diarrhea. In contrast, when relying on plasma exposure, the model failed to predict intestinal injury for two out of the six diarrheagenic drugs tested. Our modeling approach distinguished the toxicity profiles of CDK4/6 inhibitors, predicting minimal epithelial injury for ribociclib and substantial epithelial disruption for abemaciclib, consistent with its higher clinical incidence of diarrhea. Similarly, the toxicity quantified in hSIOs enabled accurate prediction of epithelial injury and diarrhea severity for four epithelial growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). This approach introduces new GI safety assessment and clinical dose selection paradigms to enable the simulation of patients' response based upon in vitro drug response modeling."],"pubmed_title":["Intestinal Organoid-Based Mathematical Modeling Predicts Clinical Gastrointestinal Toxicity of Oral Oncology Drugs."],"pubmed_authors":["Pin Carmen C, Maheshvare M Deepa D, Gall Louis L, Hall Andrew A, Coen Muireann M, Bianco Ambra A, Liu Shimeng S, Pryde Kenneth K"],"additional_accession":[]},"is_claimable":false,"name":"Pin2025_Intestinal Organoids Model","description":"We have developed a human small intestinal organoid (hSIO)-based mathematical modelling approach for the early prediction of GI toxicity of oral antiproliferative cancer treatments. Our mathematical model comprises hSIOs proliferative cells that become non-proliferative and eventually undergo cell death. Negative feedback loops regulate the rate of transition between these states, enhancing proliferation during the organoid expansion phase and balancing cell death in the stationary phase. Furthermore, the stationary phase is eventually followed by organoid decay, if organoids are not split and medium refreshment is not performed, which we modelled by accounting for the toxic effect of accumulated cell-produced waste material. Regarding drug-induced toxicity, the model implements cycle arrest and cell death of proliferative cells associated with exposure of oncology drugs","dates":{"last_modification":"2026-05-01","publication":"2026-05-01","submission":"2025-09-11"},"accession":"MODEL2509110001","cross_references":{"pubmed":["42033153"],"biomodels__db":["MODEL2509110001"]}}