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Objective  Develop and validate particular, concrete, and abstract yet plausible in silico mechanistic explanations for large intra- and interindividual variability observed for eleven bioequivalence study participants. Do so in the face of considerable uncertainty about mechanisms.    Methods  We constructed an object-oriented, discrete event model called  subject  (we use small caps to distinguish computational objects from their biological counterparts). It maps abstractly to a dissolution test system and study subject to whom product was administered orally. A  subject  comprises four interconnected grid spaces and event mechanisms that map to different physiological features and processes.  Drugs  move within and between spaces. We followed an established, Iterative Refinement Protocol. Individualized mechanisms were made sufficiently complicated to achieve prespecified Similarity Criteria, but no more so. Within  subjects , the  dissolution  space is linked to both a product- subject  Interaction Space and the GI  tract . The GI  tract  and Interaction Space connect to  plasma , from which  drug  is eliminated.    Results  We discovered parameterizations that enabled the eleven  subject  simulation results to achieve the most stringent Similarity Criteria. Simulated profiles closely resembled those with normal, odd, and double peaks. We observed important subject-by-formulation interactions within  subjects .    Conclusion  We hypothesize that there were interactions within bioequivalence study participants corresponding to the subject-by-formulation interactions within  subjects . Further progress requires methods to transition currently abstract  subject  mechanisms iteratively and parsimoniously to be more physiologically realistic. As that objective is achieved, the approach presented is expected to become beneficial to drug development (e.g., controlled release) and to a reduction in the number of subjects needed per study plus faster regulatory review.

Individualized, discrete event, simulations provide insight into inter- and intra-subject variability of extended-release, drug products