By Role · Clinical Trial CFO
From Reactive Trial Spend to Predictable Execution Economics
Maxis AI helps clinical trial CFOs reduce CDM costs 30%, save $200K–400K per trial, improve submission prep, and scale capacity.
$200K–400K
Cost savings per trial
30%
Cost savings vs. traditional CDM
3–6 Mo
NDA/BLA prep vs. 6–12 mo
Scalable
Capacity without proportional headcount
WHO IT IS
The Context
A Clinical Trial CFO overseeing development spend across active clinical programs faced a familiar financial constraint: trial budgets were increasingly affected by operational execution risk. Programming costs, CDM workloads, submission-preparation cycles, and vendor coordination created budget pressure across the portfolio. Finance teams could see spend after it occurred, but they lacked a reliable execution layer to reduce avoidable manual effort before costs escalated.
The challenge was not only cost tracking. It was improving the economics of clinical execution by reducing FSP dependency, lowering manual CDM burden, accelerating submission preparation, and scaling trial capacity without proportional headcount growth.
Challenges
Key barriers to Financial Oversight
FSP Cost Exposure
- Programming costs reached $180–220/hr
- 25–30% annual turnover impacted consistency
- Heavy reliance on external capacity
CDM Cost Pressure
- High manual effort in data management
- Traditional CDM averaged $850K per trial
- 12–15 FTEs often required
Submission-Readiness Burden
- NDA/BLA prep took 6–12 months
- Manual assembly consumed regulatory resources
- Delays increased financial uncertainty
Headcount-Linked Scaling
- Capacity growth required more people and vendors
- Scaling increased cost and complexity
- Limited predictability for finance teams
Operational solution
Maxis AI agentic workflows — under human oversight throughout
Biometrics Cost Control
- AI-assisted programming under expert supervision
- Reduced reliance on traditional FSP models
Outcome
$200K–400K cost savings per trial
CDM Efficiency Layer
- AI-assisted data cleaning and query resolution
- Teams focus on exceptions and clinical judgment
Outcome
30% cost savings vs. traditional CDM
Submission-Readiness Acceleration
- AI-assisted document compilation and eCTD workflows
- Regulatory teams focus on strategy and quality
Outcome
3–6 month NDA/BLA prep vs. 6–12 months
Maxis AI operates as a governed and supervised execution layer within existing systems throughout.
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Measured impact
Quantified outcomes after deploying Maxis AI's agentic workflows
| Metric | Before Maxis AI | After Maxis AI |
|---|---|---|
| Programming Cost | $180–220/hr FSP costs | $200K–400K savings per trial |
| CDM Cost | $850K per trial, 12–15 FTEs | 30% cost savings |
| Submission Preparation | 6–12 month NDA/BLA prep | 3–6 month prep |
| Execution Capacity | Scaling required more headcount | Scaled without proportional headcount growth |
| Financial Forecasting | Reactive, report-driven visibility | More predictable execution economics |
Outcome
Quantified Benefits
Finance leaders reduced costs, improved predictability, and scaled delivery more efficiently
Programming Cost: $200K–400K savings per trial
CDM Cost: 30% cost savings
Submission Preparation: 3–6 month prep
Execution Capacity: Scaled without proportional headcount growth
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