Human-Relevant Applications
for Oncology Research
Explore how Pythia’s TME-Chip platform supports drug testing,
immuno-oncology studies, therapeutic penetration analysis,
biomarker discovery, and translational research in a dynamic 3D tumor microenvironment.
Therapy Response Evaluation
Evaluate drug efficacy and immune-mediated tumor killing in a dynamc 3D TME model
Context of Use
Assess the anti-tumor activity of immunotherapies, targeted therapies, ADCs, chemotherapies, and combination treatments within a physiologically relevant tumor microenvironment. Our platform enables measurement of tumor growth inhibition, immune cell-mediated cytotoxicity, and treatment-induced changes that may influence therapeutic outcomes.
Typical Applications
- Immunotherapy evaluation
- Combination therapy screening
- ADC efficacy assessment
- Cell therapy
Drug Penetration & Delivery
Visualize how therapeutics distribute and penetrate into 3D tumor tissue
Context of Use
Investigate the transport, distribution, and retention of therapeutic agents within complex tumor tissues. Our TME-Chip enables visualization of drug movement across stromal barriers and assessment of factors that may limit therapeutic exposure in solid tumors.
Typical Applications
- ADC penetration studies
- Antibody distribution analysis
- Nanoparticle delivery assessment
- Drug transport optimization
Tumor Microenvironment Biology
Study tumor-stroma-immume interactions in a human-relevant model
Context of Use
Recreate the cellular complexity of the tumor microenvironment to investigate interactions among tumor cells, fibroblasts, immune cells, and extracellular matrix components. Our platform supports mechanistic studies of cancer progression, immune suppression, and therapeutic resistance.
Typical Applications
- Tumor-immune interaction studies
- Cancer-associated fibroblast research
- Immune evasion mechanisms
- Resistance biology
Multi-Omics and Biomarker Discovery
Connect functional drug response with molecular signature
Context of Use
Integrate TME-Chip response data with multi-omics profiles to identify predictive biomarkers, uncover response mechanisms, and generate translational insights for drug development.
Typical Applications
- Biomarker discovery
- Multi-omics integration
- Response mechanism analysis
- AI-assisted predictive modeling
Patient-Derived Translational Testing
Support translational research using patient-derived tumor cells, organoids, or clinical samples
Context of Use
Typical Applications
- Patient-derived tumor models
- Clinical sample evaluation
- Biomarker validation
- Precision oncology research
Contact Us
Connect with Pythia Biotech to learn more about our products and services,
explore partnering opportunities, or discuss potential collaborations.
