FibroAI™ is our Deep Learning histology platform powered by ResNet and MobileNet architectures. It performs digital pathology on the tissues grown in the ColFi3D™ platform. Instead of just counting dead cells, the AI analyzes the histological shift by observing how the tissue’s structure normalizes when exposed to effective treatments. It provides quantitative, high-speed predictions of drug efficacy with over 95% accuracy, identifying subtle biological patterns that the human eye cannot detect.
Beyond Cell Counting
Conventional drug screening methods rely on:
- Cell viability assays
- Apoptosis markers
- Proliferation measurements
While useful, these approaches miss critical information about tissue-level organization and structural normalization.
FibroAI™ shifts the paradigm from cell death metrics to architectural restoration metrics.
Core Concept: Tissue Normalization
FibroAI™ introduces the concept of a Tissue Normalization Score.
Instead of asking:
Did the drug kill cancer cells?
We ask:
Did the drug restore tissue architecture toward a healthy state?
By quantifying structural alignment, vascular morphology, and matrix organization, FibroAI™ detects subtle therapeutic responses that often precede observable cell death.
What FibroAI™ Measures
Structural Pattern Recognition
- Fiber alignment and organization
- Cellular spatial distribution
- Matrix remodeling dynamics
Vascular Network Mapping
- Vessel density
- Branching morphology
- Network integrity
Architectural Complexity Analysis
- Multi-scale structural features
- Heterogeneity quantification
- Tumor microenvironment patterns
Why Architectural AI Matters
Drug response frequently emerges as subtle microstructural alterations within tissue architecture before widespread cell death becomes detectable. Changes in cellular organization, matrix remodeling, and vascular patterns can provide early signals of therapeutic activity that traditional viability assays may miss.
By analyzing tissue architecture rather than relying solely on cell death metrics, early responders can be identified more rapidly, nuanced drug effects can be captured, emerging toxicity patterns can be detected sooner, and the risk of false negatives can be reduced. This architectural approach enhances the predictive power of preclinical screening and supports more informed, data-driven clinical decision-making.
Applications
Precision Oncology
FibroAI™ generates a drug sensitivity profile for individual patient-derived tissues.
Physicians receive a ranked map of therapeutic response based on tissue normalization analysis.
Drug Discovery & R&D
Pharmaceutical teams can:
- Rank compounds by phenotypic response
- Identify failures before Phase I
- Improve translational prediction accuracy
- Reduce late-stage attrition
High-Throughput Phenotypic Screening
Combined with ColFi3D™, FibroAI™ supports scalable screening workflows across large compound libraries.
Integrated Platform Advantage
ColFi3D™ creates physiologically relevant 3D tissue models.
FibroAI™ decodes the biological intelligence embedded within those models.
Together, they form a closed-loop system:
Human-like tissue → AI-driven analysis → Predictive therapeutic insight
Competitive Differentiation
FibroAI™ is trained on proprietary ColFi3D™ tissue datasets, enabling it to recognize complex structural patterns specific to matrix-rich 3D environments. Rather than relying on isolated cell-based metrics, the platform focuses on tissue-level architectural features, capturing spatial organization, matrix remodeling, and vascular characteristics. It is purpose-built for physiologically relevant 3D systems and is adaptable across oncology and other microenvironment-driven diseases where tissue architecture plays a central role in disease progression and therapeutic response.
Vision
FibroAI™ transforms complex tissue data into actionable intelligence.
By quantifying how therapies reshape human tissue architecture, we aim to improve:
- Drug development success rates
- Personalized treatment decisions
- Translational reliability between lab and clinic
For research partnerships, pharmaceutical collaborations, or clinical integration inquiries, please contact Purely Grow.
