Predicting plasma concentration-time profiles of orally disintegrating tablets with delayed absorption under fed...

Orally disintegrating tablets (ODTs) offer substantial advantages for patients with swallowing difficulties; however, under fed conditions without water, ODTs frequently exhibit delayed absorption, complicating pharmacokinetic evaluation and Bioequivalence (BE) assessment. In particular, unpredictable prolongation of T_max necessitates excessively dense and prolonged blood sampling in BE studies, increasing ethical and economic burdens on study participants and sponsors. To address this challenge, we developed a novel framework to predict plasma concentration-time profiles with delayed absorption under this dosing condition. Absorption-delay functions were derived from published individual plasma concentration-time profiles of rivaroxaban ODTs using a numerically stable, matrix-based non-negative least-squares deconvolution method. These functions were applied by convolution to simulate without-water plasma concentration-time profiles using the corresponding individual-level with-water profiles. In addition, to overcome the limited availability of individual-level data, we developed a Gaussian process-based generative model that reconstructs realistic individual profiles using only reported means and standard deviations of plasma concentration data. The proposed framework accurately reproduced observed profiles of multiple rivaroxaban ODT formulations and demonstrated transferability to ODTs containing different active ingredients, including tolvaptan and sildenafil. Predicted T_max and C_max values were consistent with reported data. This framework provides a practical and quantitatively grounded basis for predicting delayed absorption of ODTs administered under fed conditions without water and for the rational design of sampling schedules in BE studies, enabling more effective, cost-efficient, and patient-friendly study designs.