Systems and Methods for Prognostic Covariate Adjustment in Logistic Regression for Randomized Controlled Trial Design

A non-transitory machine readable medium containing processor instructions for ROT design using prognostic covariate adjustment in logistic regression models, where execution of the instructions by a processor causes the processor to perform a process that comprises:

• generating a plurality of digital twin distributions for prospective trial participants;
• generating a plurality of digital twins based on the generated digital twin distributions;
• calculating prognostic scores for each participant based on their generated digital twins, wherein the prognostic score is an expectation of the digital twin distribution for a prospective trial participant;
• optimizing trial design based on the prognostic scores;
• fitting a logistic regression model to observed data comprising the digital twins of the participants, actual outcomes of each participant, and the prognostic scores;
• computing a set of regression coefficient estimates of the logistic regression model based on the prognostic scores, wherein the set of regression coefficients comprises a treatment indicator coefficient, and a prognostic score coefficient;
• and
• estimating treatment effects based on the fitted model.