Tumor Classification from Histology Imaging
Machine learning models for classifying tumor patterns from histology images are being prepared and evaluated before launch.
In progress · Launching soon
Open-source ecosystem for in vitro and microphysiological systemsTools
PhysioVerse maintains practical resources that help contributors, users, curators, developers, and institutions apply shared workflows.
Toolbox
Tool pages collect links, demos, user instructions, analysis workflows, and downloadable outputs. Four tools are currently available, and three machine learning tools are being prepared for launch.
Benchmark lung epithelial culture models against a fixed healthy human distal lung tissue reference using PCA centroid distance, Spearman correlation, and robustness summaries.
ReadyRun GLMQL-MAS biomarker ranking, generate top gene lists, and compare PCA using all genes versus top MAS-selected genes.
ReadySearch a focused classified study table with titles, DOI links, authors, emails, and main-variable filters for model system, species, tissue, cell type, application, and ECM.
In training / progressMap DOI-level organoid, organ-on-chip, and microphysiological systems data records across model systems, tissues, assays, data modalities, validation, and regulatory features.
In training / progressMachine learning models for classifying tumor patterns from histology images are being prepared and evaluated before launch.
In progress · Launching soonMachine learning workflows for analyzing cilia movement and video-based readouts are being prepared for future release.
In progress · Launching soonIntegrated machine learning workflows for multi-omic data interpretation and model comparison are being prepared and evaluated.
In progress · Launching soonStandards and manufacturing partners
Connect with the organizations advancing consensus standards, validation, and regenerative manufacturing across the PhysioVerse ecosystem.
The Microphysiological and Organoid Systems Standards Development Organization (MOSSDO) is a federally funded multi-stakeholder initiative focused specifically on establishing consensus-based standards for organoids, microphysiological systems (MPS), and body-on-a-chip technologies. MOSSDO develops frameworks for reproducibility, validation, and interoperability, enabling these platforms to be more reliably adopted across research, regulatory, and translational settings. In coordination with enabling ecosystem efforts such as PhysioVerse, MOSSDO provides the standards foundation that supports data integration, comparability, and broader field-wide adoption.
The Regenerative Manufacturing Innovation Consortium (RegMIC), founded in 2014, is a national initiative that brings together stakeholders from industry, academia, and government to advance the manufacturing, scale-up, and commercialization of regenerative technologies. Through cross-sector collaboration, RegMIC addresses key challenges in translation, including process development, regulatory alignment, and the establishment of best practices across cell, tissue, and advanced in vitro systems.