AIMC Topic: Organoids
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Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis.
STAR protocols
Jan 31, 2025
Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductanc...
Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer.
Biochimica et biophysica acta. Molecular basis of disease
Jan 25, 2025
Drug resistance often stems from drug-tolerant persister (DTP) cells in cancer. These cells arise from various lineages and exhibit complex dynamics. However, effectively targeting DTP cells remains challenging. We used single-cell RNA sequencing (sc...
Next-Gen Therapeutics: Pioneering Drug Discovery with iPSCs, Genomics, AI, and Clinical Trials in a Dish.
Annual review of pharmacology and toxicology
Dec 17, 2024
In the high-stakes arena of drug discovery, the journey from bench to bedside is hindered by a daunting 92% failure rate, primarily due to unpredicted toxicities and inadequate therapeutic efficacy in clinical trials. The FDA Modernization Act 2.0 he...
A deep learning approach to predict differentiation outcomes in hypothalamic-pituitary organoids.
Communications biology
Dec 6, 2024
We use three-dimensional culture systems of human pluripotent stem cells for differentiation into pituitary organoids. Three-dimensional culture is inherently characterized by its ability to induce heterogeneous cell populations, making it difficult ...
ReBiA-Robotic Enabled Biological Automation: 3D Epithelial Tissue Production.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Sep 26, 2024
The Food and Drug Administration's recent decision to eliminate mandatory animal testing for drug approval marks a significant shift to alternative methods. Similarly, the European Parliament is advocating for a faster transition, reflecting public p...
Visualization of incrementally learned projection trajectories for longitudinal data.
Scientific reports
Jun 12, 2024
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualiz...
SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.
Cell genomics
May 31, 2024
Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-effi...
Image-based profiling and deep learning reveal morphological heterogeneity of colorectal cancer organoids.
Computers in biology and medicine
Mar 26, 2024
Patient-derived organoids have proven to be a highly relevant model for evaluating of disease mechanisms and drug efficacies, as they closely recapitulate in vivo physiology. Colorectal cancer organoids, specifically, exhibit a diverse range of morph...
OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion.
Communications biology
Mar 13, 2024
Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development and precision medicine applications. Epithelial fluid transport properties in PDOs can be measured th...
Revealing the clinical potential of high-resolution organoids.
Advanced drug delivery reviews
Feb 8, 2024
The symbiotic interplay of organoid technology and advanced imaging strategies yields innovative breakthroughs in research and clinical applications. Organoids, intricate three-dimensional cell cultures derived from pluripotent or adult stem/progenit...
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