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Phase 2 Delivered. No Biometrics Build. DB Lock in 3–4 Months.
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Outcomes
What we did
3–4 Months
DB lock vs 8–10 projected
4–6 Months
Submission accelerated
60–70%
Queries auto-resolved
0
Permanent hires required
About Company
A Series B oncology biotech company, moving from Phase 1 to a 12-site, multi-regional Phase 2, did not have the internal biometrics infrastructure to support the effort.
The company, based in San Diego, California, one of the most active biotech centers for oncology in the country, had robust Phase 1 results but lacked in-house data management and statistical programming capabilities.
Development of an in-house infrastructure would require 12 to 18 months, which the company could not afford. Additionally, a full-service CRO approach would require an unbalanced proportion of the available budget. The company needed to have execution capacity but not build a team or require a full-service CRO.
The company, based in San Diego, California, one of the most active biotech centers for oncology in the country, had robust Phase 1 results but lacked in-house data management and statistical programming capabilities.
Development of an in-house infrastructure would require 12 to 18 months, which the company could not afford. Additionally, a full-service CRO approach would require an unbalanced proportion of the available budget. The company needed to have execution capacity but not build a team or require a full-service CRO.
Challenges
Key Barriers
to Trial Execution
No Biometrics Infrastructure
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No data management or programming setup
No submission workflows in place
Built from scratch
Data Fragmentation
Data spread across 12 sites and systems
Data spread across 12 sites and systems
Limited data visibility
DB Lock Timeline Risk
8–10 month DB lock projection
Too slow for investor timelines
Regulatory risk
Compliance Requirement
ICH E6(R3) RBQM required
No governance or validation framework
Risk before study start
Core platform
Operational Solution
Maxis AI Agentic Workflows — Under Human Oversight Throughout
AI for Data Management
Unified data layer across 12 sites
No infrastructure build needed
15K–25K queries managed
AI for RBQM
ICH E6(R3)-compliant
RBQM operational from first patient in
60–70% queries auto-resolved
ICH E6(R3) compliant day 1
AI for Programming
Submission-ready datasets delivered
3–4 months vs 8–10 months
4–6 months earlier submission
Maxis AI operated as a governed and supervised execution layer within existing systems throughout.
Core platform
Measured Impact
Quantified Outcomes After Deploying Maxis AI’s Agentic Workflows
| Metric | Before Agentic AI | After Agentic AI |
|---|---|---|
| Database Readiness | No biometrics infrastructure; 8–10 month DB lock projected; 12 sites, no unified data view | Database lock in 3–4 months; submission advanced 4–6 months |
| Biometrics Capability | No DM or programming infrastructure; ICH E6(R3) RBQM not yet in place | 60–70% queries auto-resolved; RBQM operational from first patient in |
| Execution Visibility | Limited — no central data tracking across sites | Continuous — real-time view across all 12 sites |
| CRO Dependency | Full-service CRO would consume runway; no internal team to build on | Phase 2 delivered without permanent team build; investor milestone met |
| Execution Predictability | Variable — no historical baseline, high uncertainty | Improved — AI-driven risk signals and milestone tracking from day one |
Outcomes
Phase 2 delivered without a permanent biometrics team build — database lock achieved in 3–4 months versus the 8–10 month projection, advancing submission by 4–6 months.
DB lock in 3–4 months vs 8–10 projected
60–70% queries auto-resolved — no permanent data management hires needed
ICH E6(R3) audit-ready — investor milestone met on time
No infrastructure build — operated within sponsor systems from day one
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