AGENT 19 / 11 · RETAIL & E-COMMERCE · LIFE SCIENCES & PHARMA R&D

Bio-Statistical Analysis Assistant

Aggregates trial outcome data as it accrues and continuously re-estimates statistical power — flagging early whether current enrollment can actually detect the expected effect.

READS FROMTrial protocol, interim outcome data

MCP SERVERLife Sciences Data Server

MODELRouted to reasoning-tier open model

HANDS OFF TOClinical Trial Patient Matcher (recruitment target)

RUN THE AGENT

Set your trial parameters, compute power

Adjust arm sizes, expected effect size and dropout and the agent recalculates statistical power and required enrollment instantly.

ASSUMPTIONS

Treatment arm size 150

Control arm size 150

Expected effect size (Cohen's d) 0.35

Significance threshold (α) 0.05

Expected dropout rate 15%

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Statistical power at current N

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Effective (harmonic) sample size

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Required N / arm for 80% power

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Total enrollment needed

Metric	Value

HOW IT WORKS

What the agent actually does

1. Pull trial parameters	Reads arm sizes, expected effect size and the pre-registered significance threshold from the trial protocol.
2. Compute power	Estimates the statistical power to detect the expected effect at the current enrollment, accounting for expected dropout.
3. Size the trial	Back-calculates the enrollment needed to hit a target power of 80% if current arms fall short.
4. Hand off	Feeds the enrollment target to the Clinical Trial Patient Matcher's recruitment goal, and structures interim outcome data for the biostatistics team as results come in.