An Integrated NONMEM-Based Framework for Ticagrelor Exposure–PRU Modeling and Patient-Level Outcome Prediction Assessment

Background/Objectives: Ticagrelor reduces ischemic events in acute coronary syndrome (ACS) but may increase bleeding in susceptible patients. We used a population PK and PK/PD model to describe ticagrelor exposure and platelet reactivity unit (PRU) dynamics and assessed whether model-predicted PRU improved prediction of subsequent outcomes in a patient-level analysis. Methods: We collated published evidence from 39 ticagrelor clinical studies (172 group-level datasets). The final population PK and indirect-response PK/PD models for ticagrelor, AR-C124910XX, and PRU were implemented in NONMEM with a two-compartment structure, three transit absorption compartments, and prespecified covariate relationships. Model-predicted PRU from recorded prescription exposure was linked to subsequent outcomes in a de-identified UK Biobank cohort using a prespecified 90-day landmark analysis. Cox models with clinical variables, recorded medication exposure, and model-predicted PRU were compared; a 30-day landmark analysis was used for sensitivity analysis. Results: The final model retained a two-compartment structure with three transit absorption compartments and quantified age, disease status, concomitant aspirin, and fasting effects on exposure. The indirect-response model linked combined parent-metabolite molar concentration to continuous PRU dynamics. In 731 UK Biobank participants, the 90-day ischemic, bleeding, and all-cause death analyses included 112, 48, and 129 events, respectively. Adding model-predicted PRU did not show stable incremental discrimination; all paired-bootstrap intervals for C-index and Brier-score increments crossed zero. Conclusions: We established a NONMEM-based framework linking ticagrelor dosing, exposure, and PRU dynamics to patient-level outcome prediction assessment. Although incremental predictive benefit was not established in the current cohort, the framework provides a basis for further evaluation using paired measured PK, PRU, and clinical outcome data before clinical application.