Binary

Exposure–response analysis for binary endpoints (e.g., response vs. no response) aims to evaluate how drug exposure affects the probability of a clinical outcome. This process includes several key steps:

• Exploratory Data Analysis (EDA): Understanding the distribution of exposure and response across subgroups.

• Base Model Development: Building a model that describes the probability of response as a function of exposure.

• Covariate Search: Identifying patient factors that influence response probability.

• Model Diagnostics: Assessing the fit and predictive performance of the model including visual predictive check and sensitivity analysis (evaluating the robustness of model predictions to changes in covariates).

• Forward Simulations: Simulating response probabilities under various dosing or covariate scenarios.

This structured approach supports informed decision-making in dose selection and patient subgroup evaluation.