Medicine and clinical research
Test hundreds of trial designs before enrollment.
Antinuous simulates many trial designs and power scenarios at once and screens literature for systematic reviews with a log of each decision. Each number links to its study or the code that produced it.
Use cases
Simulate trial designs before enrollment
Comparing many designs means rerunning the power calculation for each set of assumptions.
You ask
Simulate 500 two-arm trial designs across effect sizes from 0.3 to 0.5, dropout from 5% to 20% and three allocation ratios, and tell me how many patients per arm each needs for 80% and 90% power.
What it does
- Pulls effect sizes and dropout rates from comparable published trials.
- Installs statistics packages and writes the simulation in the code workspace.
- Runs each design option and charts power (the chance of detecting a real effect) against sample size.
- Writes the assumptions and results into an analysis notebook.
You get
A notebook with power curves and the code that produced them.
Power (%)Patients per arm
Effect size 0.3
Effect size 0.4
Effect size 0.5
Power for a two-arm trial at three effect sizes (two-sided test at 5%).
Who it's for
Clinical researchersRun systematic reviews with a full screening log.
BiostatisticiansSimulate trial designs and power in a reproducible notebook.
Drug safety scientistsSee new safety reports and papers flagged as they appear.
Medical affairs teamsCompare a draft protocol with similar past trials.
Works with
PubMed
ClinicalTrials.gov
ChEMBL
PubChem
Slack
Google Slides