AI IN HEALTHCARE
Transforming Lung Cancer Research with a Nationwide Bio-Data-Driven AI Platform
The APOLLO11 consortium builds a decentralized, multi-level biobank and real-world data repository to accelerate personalized treatment for lung cancer patients.
Executive Impact: Unlocking Precision Oncology
APOLLO11 addresses critical unmet needs in lung cancer research by leveraging Artificial Intelligence and real-world data.
0
Participating Centers
0
Active for Recruitment
0
Patients with Data (as of Feb 2025)
0
Immune Profiling Samples
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
APOLLO11 Comprehensive Research Workflow
Patient Enrollment & Consent (RWD, Images, Samples)
→
Local Biobank Collection (Blood, Tissue, Biopsies)
→
Data Harmonization & Central Annotation (Data Dictionary, REDCap)
→
Federated Learning & Synthetic Data Generation
→
Multi-omic Data Integration (Genomics, Radiomics, Clinical)
→
AI Model Development & Validation (Predictive Algorithms, XAI)
→
Clinical Implementation (Personalized Treatment)
2020
Patients Enrolled with Data Collected (as of Feb 2025)
| Feature | APOLLO11 | I3LUNG | MOSAIC |
|---|---|---|---|
| Scope & Infrastructure |
|
|
|
| Key Focus |
|
|
|
| Biobank Integration |
|
|
|
| Data Accessibility & Consent |
|
|
|
Calculate Your Potential ROI with AI Integration
Estimate the potential impact of an AI-driven research platform on your organization.
Estimated Annual Savings
Hours Reclaimed Annually
Our Strategic Implementation Roadmap
Our phased approach ensures a smooth and effective integration of advanced AI analytics into your research and clinical workflows.
Phase 1: Network & Infrastructure Setup
Establish the nationwide consortium, integrate REDCap for data collection, set up local biobanks, and deploy the federated learning platform in initial centers.
Phase 2: Data Collection & Harmonization
Initiate retrospective and prospective collection of RWD, medical images, and biological samples. Implement the data dictionary and ensure standardized data acquisition across all participating centers.
Phase 3: Multi-omic Analysis & Model Development
Conduct comprehensive analyses (genomics, transcriptomics, radiomics, metabolomics) on collected data. Develop and validate multi-modal AI predictive models with XAI frameworks.
Phase 4: Clinical Translation & Dissemination
Integrate validated AI models into clinical decision support systems. Disseminate findings through publications and collaborations, expanding the network's reach and impact.
Accelerate Your Precision Oncology Initiatives
Discover how a data-driven approach can revolutionize research and patient care in lung cancer. Book a consultation with our experts today.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat