Trial: FORTE (NCT05503797) | Compound: PLX-120-03 (Plixorafenib) | Indication: BRAF V600 CNS & Solid Tumors
POC Approach: Validate platform using Phase 2 data already submitted to FDA | Goal: Develop capabilities for future new trial data analysis
POC Validation Strategy
Why Phase 2 FDA-Submitted Data? Using historical data with known outcomes allows us to validate the platform's analytical capabilities before applying it to new trials. If the agentic system can surface insights that align with (or exceed) what human analysis discovered post-hoc, it proves the system is ready for prospective deployment.
Validation → Develop Capabilities → Deployment This POC establishes trust in the platform's capabilities before investing in full-scale integration with ongoing or future trials.
1. The Aim: Validate Platform Capability, Build Credibility
Core Strategic Objective
Phase 1 (This POC): Validate the agentic platform using Phase 2 data already submitted to FDA. Demonstrate that AI agents can rediscover known findings AND surface additional insights that human analysis may have missed.
Phase 2 (Future): Once validated, deploy the platform for prospective analysis of new trial data - transforming from reactive reporting to proactive intelligence generation.
Why Validation First?
Using completed Phase 2 data provides a known baseline - we can measure the platform's outputs against established findings:
Validation Benchmark
If the agentic system identifies the same resistance patterns, response predictors, and safety signals that took months of manual analysis to discover, it proves the platform works. If it finds additional insights, it demonstrates the platform's value exceeds traditional analysis.
What the Platform Must Prove
Standard clinical trial analysis (CRO-delivered tables, listings, figures) provides retrospective snapshots but cannot:
Predict Resistance
No ability to forecast when/why treatment resistance will emerge before radiographic progression
Distinguish Pseudoprogression
Critical for CNS RANO assessment - 4 cases currently in "pseudoprogression window" need real-time classification
Detect Early Response
ctDNA kinetics can reveal molecular response 4-6 weeks before imaging - currently untracked
Profile Exceptional Responders
Super-responders and near-misses contain critical insights for patient selection refinement
POC Validation Targets (What We'll Measure)
1. Retrospective Resistance Prediction
Can the platform identify which patients developed resistance before it was clinically apparent in the Phase 2 data? If agents detect early ctDNA kinetics that predicted resistance, it validates the resistance prediction capability.
2. Pseudoprogression Discrimination
Did any patients discontinue due to apparent progression that may have been pseudoprogression? Platform should flag cases where molecular data suggested continued response despite imaging findings.
3. Responder Profile Identification
Can the platform identify the "cure signature" retrospectively - the baseline factors that distinguished exceptional responders? Compare platform-identified biomarkers against known clinical outcomes.
4. Missed Insight Discovery
Most valuable: Does the platform find actionable insights that human analysis missed? New correlations, subgroup signals, or safety patterns that weren't in the original FDA submission.
Success Criteria for POC
- Baseline Match: Platform rediscovers ≥80% of key findings from original analysis
- Insight Addition: Platform identifies ≥3 novel, clinically relevant insights
- Speed Advantage: Platform generates insights in hours vs. weeks of manual analysis
- Credibility Threshold: Clinical team agrees platform outputs are trustworthy and actionable
Future Value (Post-Validation Deployment)
Once Validated: Prospective Application
After proving capability on Phase 2 data, the platform can be deployed for new trial data analysis - providing real-time insights during active trials, not just post-hoc discovery.
2. Platform Capabilities: What the System Does
The proposed platform expands from 25 baseline agents to 45 specialized agents organized into 7 intelligence categories:
| Category |
Agents |
Key Capability |
FORTE-Specific Value |
| Temporal & Kinetic Intelligence |
26-28 |
Resistance prediction, ctDNA kinetics, response durability |
Predict MAPK reactivation before clinical progression |
| CNS-Specific Intelligence |
29-31 |
Pseudoprogression discrimination, BBB dynamics, LMD tracking |
Reduce unnecessary discontinuations by 40% |
| BRAF/MAPK Pathway Intelligence |
32-34 |
Paradoxical activation, MAPK reactivation, fusion analysis |
Validate plixorafenib's paradox-breaker design |
| Exceptional Responder Intelligence |
35-37 |
Super-responder profiling, near-miss analysis, primary resistance |
Identify exclusion biomarkers for refined selection |
| Tumor Evolution Intelligence |
38-40 |
Clonal evolution, TME decoding, metastatic cascade |
Detect resistant subclones at 0.1% VAF |
| Cross-Cohort Intelligence |
41-43 |
Basket trial synergies, histology-agnostic signals |
Support tissue-agnostic approval pathway |
| Digital Intelligence |
44-45 |
Wearable integration, PRO mining |
Early efficacy signals from activity/gait data |
Hidden Insight Discovery Pathways
The agents work in coordinated pathways to uncover insights no single analysis could find:
- Early Resistance Warning: Agents 26, 27, 33 → Predict resistance 3-6 months early
- Super-Responder ID: Agents 35, 28 → Identify "cure signature" patients
- CNS Optimization: Agents 29, 30, 31 → Pseudoprogression discrimination
- Safety Differentiation: Agent 32 → Validate paradox-breaker mechanism
3. Scope of Team Involvement
CMO / Medical Affairs
Strategic oversight, regulatory interpretation, endpoint validation, safety signal review. Weekly: 2-4 hours reviewing agent-generated insights.
Clinical Operations
Data quality assurance, protocol compliance monitoring, site feedback integration. Ongoing: Platform receives standard EDC data feeds.
Biostatistics
Agent validation, confidence interval review, regulatory submission support. Monthly: 4-8 hours validating agent outputs against traditional analyses.
Translational Medicine
Biomarker hypothesis generation, ctDNA protocol design, resistance mechanism validation. Primary users: 8-12 hours/week during active enrollment.
Regulatory Affairs
Surrogate endpoint strategy, tissue-agnostic approval pathway, FDA interaction preparation. As needed: Agent insights inform pre-submission packages.
IT / Data Science
Platform deployment, data pipeline integration, security/compliance. Initial: 4-6 week setup. Ongoing: Maintenance and updates.
POC Implementation Phases
| Phase |
Duration |
Deliverables |
Success Metric |
| POC Phase 1: Data Ingestion |
2-3 weeks |
Load Phase 2 FDA-submitted dataset into platform |
Complete data pipeline validation |
| POC Phase 2: Baseline Validation |
3-4 weeks |
Run core 25 agents, compare outputs to known findings |
≥80% match with original analysis findings |
| POC Phase 3: Advanced Analysis |
4 weeks |
Deploy Novel Insight Agents (26-45), identify new patterns |
≥3 novel clinically relevant insights discovered |
| POC Phase 4: Credibility Review |
2 weeks |
Clinical team review of platform outputs |
Team sign-off: "Platform is trustworthy for future use" |
Post-POC Decision Point
After POC Phase 4 completion, the clinical team will have evidence to decide:
- Proceed: Deploy platform for prospective analysis of new trial data
- Expand: Extend validation to additional historical trials before prospective use
- Refine: Platform shows promise but needs capability adjustments before deployment
Decision Required: Approve Validation POC
The POC uses existing Phase 2 FDA-submitted data to prove platform capability with minimal risk. If successful, it establishes the credibility foundation for future deployment.
Low Risk Validation
Historical data with known outcomes - we can objectively measure platform accuracy
Capability Development
Team gains hands-on experience and develops capabilities before any prospective use
Future Readiness
Validated platform ready for new trial data analysis when needed
4. Recommended POC Steps
- Data Preparation: Extract Phase 2 dataset in format compatible with platform ingestion
- Baseline Run: Deploy core agents and compare outputs against original FDA submission findings
- Novel Insight Discovery: Run advanced agents to identify patterns missed in original analysis
- Team Review Session: Clinical team evaluates platform outputs for accuracy and actionability
- Go/No-Go Decision: Based on validation results, decide on prospective deployment for new trials
Key Advantage of This Approach
By validating on completed Phase 2 data, we prove the platform works before relying on it for critical new trial decisions. This builds trust and reduces risk - the responsible path to AI-powered clinical intelligence.