Editing Ai Clinical Trials (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Clinical trial phases''' — Phase I (safety, n=20-80), II (efficacy + safety, n=100-300), III (large-scale efficacy, n=1000+), IV (post-market surveillance).
* '''Randomized Controlled Trial (RCT)''' — The gold standard: patients randomly assigned to treatment or control; eliminates selection bias.
* '''Eligibility criteria''' — Inclusion/exclusion criteria defining who can participate; AI helps match patients to criteria automatically.
* '''Patient recruitment''' — The most common cause of trial failure and delay; AI identifies eligible patients from EHR data.
* '''Dropout / attrition''' — Patients withdrawing from trials; ML predicts which patients are at risk of dropout.
* '''Adaptive trial design''' — Trial design that allows pre-specified modifications (dose, sample size, arms) based on interim data.
* '''Basket trial''' — Tests a treatment in multiple diseases sharing a biomarker; requires sophisticated subgroup analysis.
* '''Umbrella trial''' — Tests multiple treatments in one disease, matched to patient biomarkers; AI matches patients to arms.
* '''Protocol deviation''' — Failure to follow trial protocol; NLP detects deviations in clinical notes.
* '''Electronic data capture (EDC)''' — Digital systems for recording trial data; AI detects data quality issues.
* '''Safety monitoring''' — Continuous surveillance for adverse events; ML detects safety signals before Data Safety Monitoring Board review.
* '''Surrogate endpoint''' — A measurable outcome used as a proxy for clinical outcomes; AI identifies new surrogate biomarkers.
* '''Historical data augmentation''' — Using historical control data to reduce the required control arm size (via Bayesian borrowing).
* '''Synthetic control arm''' — Using ML on historical data to construct a virtual control arm, reducing need for placebo patients.
* '''TrialSpark / Medidata / Veeva Vault''' — Commercial clinical trial AI platforms.
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