Building the world's most comprehensive dataset on human organoids.
Vale Biolabs generates standardized, multimodal data on human organoids to power preclinical prediction models. Starting with CNS.
The preclinical-to-clinical translation gap.
>90%
CNS clinical trial attrition rate
<5%
Translational concordance of standard preclinical models
Fragmented & non-standardized
Current state of public organoid datasets
Central nervous system therapeutics face attrition rates exceeding 90% in clinical development. A primary contributor is the limited translational validity of conventional preclinical models — rodent systems and 2D cell cultures fail to recapitulate the complexity of human neurobiology.
Human organoid models offer a more physiologically relevant alternative, but existing datasets remain fragmented across laboratories, generated under non-standardized protocols, and structured in ways that preclude robust machine learning applications.
1 Sun et al., Acta Pharm Sin B, 2022 · 2 Ineri et al., PLOS Biology, 2024
Multimodal organoid data, generated at scale.
We generate high-throughput, multimodal datasets from human organoids under rigorously standardized experimental protocols. Each data point integrates imaging, molecular, and functional readouts — captured in parallel and structured for downstream computational analysis.
Multimodal integration
Imaging (brightfield, fluorescence, confocal), transcriptomics, proteomics, and functional assays, acquired on matched samples with complete experimental metadata.
High-throughput infrastructure
Standardized pipelines enable consistent data generation at a scale required for training predictive models.
CNS-focused indication strategy
Initial efforts prioritize neurological and psychiatric disease models, where translational gaps are most pronounced.
Engagement models.
Currently available
Custom Studies
Commissioned organoid studies designed around your therapeutic program. We deliver multimodal datasets generated under standardized conditions, with full experimental documentation and analysis-ready structure.
Launching September 2026
Predictive Models
Compound-level predictive readouts derived from models trained on our proprietary multimodal organoid dataset. Initial release covers CNS indications.
Methodological differentiation.
- Scale. High-throughput infrastructure purpose-built for consistent organoid data generation.
- Multimodality. Integrated imaging, omics, and functional readouts on matched samples — not siloed measurements.
- Standardization. Protocols, metadata, and data structures designed for reproducibility and machine learning applicability.
- Human-relevant. Direct measurement in human-derived systems, eliminating cross-species extrapolation.
The next generation of preclinical prediction will be built on human-relevant data generated at sufficient scale, consistency, and resolution to support computational modeling.
Vale Biolabs is building that foundation.
Get in touch.
For inquiries regarding custom studies, predictive model access, or scientific collaboration, please reach out.
