ArticleDiscover applied sciences2025
3D Multi-Tissue microphysiological system for Anti-Cancer and cardiotoxicity drug screening with automated image analysis.
Article in Discover applied sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
9 authors.
Funding
Abstract
In vitro 3D tissue models within microfluidic-based microphysiological systems (MPS) provide controlled and reproducible platforms for quantification of isolated cellular processes in response to biochemical or biophysical stimulus. This study demonstrates the development of a 3D MPS with a dual-chamber, closed-capillary circuit microfluidic culture platform to study chemotherapy drug efficacy in vitro for aggressive malignancies such as breast cancer and glioblastoma. This novel microfluidic system was used to model HER2 + breast cancer (BCTM-SKBR3) co-cultured with cardiac (CTM-AC16) tissue for proof-of-concept chemotherapy-induced cardiotoxicity studies. To further demonstrate the versatility of this system, a glioblastoma tissue model with chemotherapy efficacy studies was included. Additionally, implementation of a Python-based automated image analysis script (AIAPS) facilitated quantification of cell size within the tissue models from 3D fluorescence z-stack images. The results demonstrate maintenance of lineage-specific biomarker expression, physiologically relevant cell morphology and structural organization, and detectable changes in cell sizes with chemotherapy treatment within the 3D tissue models. These results demonstrated the system's potential for use as a preclinical drug screening platform.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.