By Role · Biostatistics
Biometrics Delivery Scaled Without Proportional FSP Dependency
Maxis AI helps biometrics teams cut programming time 50–70%, reduce SAP development time 85%, and save $200K–400K per trial.
50–70%
Programming time savings
85%
SAP development time reduction
70%
Manual programming effort reduced
$200K–400K
Cost savings per trial
WHO IT IS
The Context
A Head of Biometrics leading a US-based team was managing multiple concurrent trials while programming workload continued to expand across SDTM/ADaM mapping, TFL generation, validation, and SAP development.
Programmers were spending most of their time on repetitive mapping and output-generation tasks instead of higher-value statistical review, complex analysis, and study design support.
With FSP programmer rates at $180–220/hr and 25–30% annual turnover creating quality variability, the team needed to expand biometrics execution capacity without adding proportional external dependency.
The challenge was not only speed. It maintained consistent, validated, submission-ready programming output under expert oversight.
Challenges
Key barriers to Biometrics Execution
Programming Backlogs
- 80% time on SDTM/ADaM and TFL tasks
- Manual TFL generation slowed delivery
Slow SAP Development
- SAP cycles took 4–8 weeks
- Limited bandwidth for higher-value statistical work
High FSP Dependency
- FSP costs reached $180–220/hr
- Turnover created quality variability
Validation & Compliance Pressure
- Manual validation increased rework risk
- CDISC, FDA, and EMA compliance had to be maintained
Operational solution
Maxis AI agentic workflows — under human oversight throughout
AI Statistical Programming
- AI assisted SDTM/ADaM + TFL automation
- Expert-supervised workflows
Outcome
50–70% programming time savings
AI-Accelerated SAP Development
- SAPs generated in days, not weeks
- SAS, R, and Python supported
Outcome
85% SAP development time reduction
FSP Cost Reduction
- Reduced reliance on external programming resources
- More capacity for higher-value statistical work
Outcome
$200K–400K saved
Maxis AI operates as a governed and supervised execution layer within existing systems throughout.
See it in your biometrics delivery model
Curious how this could work for your biometrics team?
We'll review your biometrics delivery model, identify execution bottlenecks, and show where governed AI can improve throughput in a 30-minute working session.
Measured impact
Quantified outcomes after deploying Maxis AI's agentic workflows
| Metric | Before Maxis AI | After Maxis AI |
|---|---|---|
| Programming | 80% of time spent on repetitive SDTM/ADaM mapping | 50–70% time savings |
| SAP Development | 4–8 week cycles | 85% reduction; generated in days |
| Manual Effort | Mapping, TFLs, and validation consumed capacity | 70% reduction |
| FSP Costs | $180–220/hr with turnover risk | $200K–400K savings per trial |
| Quality & Validation | Manual validation slowed readiness | Continuous compliance-focused validation |
Outcome
Quantified Benefits
The biometrics team expanded capacity, accelerated SAP development, and reduced FSP dependency while maintaining validated, audit-ready delivery
Programming: 50–70% time savings
SAP Development: 85% reduction; generated in days
Manual Effort: 70% reduction
FSP Costs: $200K–400K savings per trial
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