Linking the Gastrointestinal Behavior of Ibuprofen with the Systemic Exposure between and within Humans-Part 2: Fed State

布洛芬胃肠道行为与人体内外系统暴露的关联——第二部分:饱腹状态

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Abstract

Exploring the intraluminal behavior of an oral drug product in the human gastrointestinal (GI) tract remains challenging. Many in vivo techniques are available to investigate the impact of GI physiology on oral drug behavior in fasting state conditions. However, little is known about the intraluminal behavior of a drug in postprandial conditions. In a previous report, we described the mean solution and total concentrations of ibuprofen after oral administration of an immediate-release (IR) tablet in fed state conditions. In parallel, blood samples were taken to assess systemic concentrations. The purpose of this work was to statistically evaluate the impact of GI physiology (e.g., pH, contractile events) within and between individuals (intra and intersubject variability) for a total of 17 healthy subjects. In addition, a pharmacokinetic (PK) analysis was performed by noncompartmental analysis, and PK parameters were correlated with underlying physiological factors (pH, time to phase III contractions postdose) and study parameters (e.g., ingested amount of calories, coadministered water). Moreover, individual plasma profiles were deconvoluted to assess the fraction absorbed as a function of time, demonstrating the link between intraluminal and systemic behavior of the drug. The results demonstrated that the in vivo dissolution of ibuprofen depends on the present gastric pH and motility events at the time of administration. Both intraluminal factors were responsible for explaining 63% of plasma C(max) variability among all individuals. For the first time, an in-depth analysis was performed on a large data set derived from an aspiration/motility study, quantifying the impact of physiology on systemic behavior of an orally administered drug product in fed state conditions. The data obtained from this study will help us to develop an in vitro biorelevant dissolution approach and optimize in silico tools in order to predict the in vivo performance of orally administered drug products, especially in fed state conditions.

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