In this study, we determined the pH and buffer capacity of human gastrointestinal (GI) fluids (aspirated from the stomach, duodenum, proximal jejunum, and mid/distal jejunum) as a function of time, from 37 healthy subjects after oral administration of an 800 mg immediate-release tablet of ibuprofen (reference listed drug; RLD) under typical prescribed bioequivalence (BE) study protocol conditions in both fasted and fed states (simulated by ingestion of a liquid meal). Simultaneously, motility was continuously monitored using water-perfused manometry. The time to appearance of phase III contractions (i.e., housekeeper wave) was monitored following administration of the ibuprofen tablet. Our results clearly demonstrated the dynamic change in pH as a function of time and, most significantly, the extremely low buffer capacity along the GI tract. The buffer capacity on average was 2.26 μmol/mL/ΔpH in fasted state (range: 0.26 and 6.32 μmol/mL/ΔpH) and 2.66 μmol/mL/ΔpH in fed state (range: 0.78 and 5.98 μmol/mL/ΔpH) throughout the entire upper GI tract (stomach, duodenum, and proximal and mid/distal jejunum). The implication of this very low buffer capacity of the human GI tract is profound for the oral delivery of both acidic and basic active pharmaceutical ingredients (APIs). An in vivo predictive dissolution method would require not only a bicarbonate buffer but also, more significantly, a low buffer capacity of dissolution media to reflect in vivo dissolution conditions.
The application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted outcomes. The aim of this study was to predict the systemic concentrations of ibuprofen after oral administration of an 800 mg immediate-release (IR) tablet to healthy subjects in fasted-state conditions. A mechanistic oral absorption model coupled with a two-compartmental pharmacokinetic (PK) model was built in Phoenix WinNonlinWinNonlin® software and in the GastroPlus™ simulator. It should be noted that all simulations were performed in an ideal framework as we were in possession of a plethora of in vivo data (e.g., motility, pH, luminal and systemic concentrations) in order to evaluate and optimize these models. All this work refers to the fact that important, yet crucial, gastrointestinal (GI) variables should be integrated into biopredictive dissolution testing (low buffer capacity media, considering phosphate versus bicarbonate buffer, hydrodynamics) to account for a valuable input for physiologically-based pharmacokinetic (PBPK) platform programs. While simulations can be performed and mechanistic insights can be gained from such simulations from current software, we need to move from correlations to predictions (IVIVC → IVIVP) and, moreover, we need to further determine the dynamics of the GI variables controlling the dosage form transit, disintegration, dissolution, absorption and metabolism along the human GI tract. Establishing the link between biopredictive in vitro dissolution testing and mechanistic oral absorption modeling (i.e., physiologically-based biopharmaceutics modeling (PBBM)) creates an opportunity to potentially request biowaivers in the near future for orally administered drug products, regardless of its classification according to the Biopharmaceutics Classification System (BCS).
General cognitive ability (GCA) is an individual difference dimension linked to important academic, occupational, and health-related outcomes and its development is strongly linked to differences in socioeconomic status (SES). Complex abilities of the human brain are realized through interconnections among distributed brain regions, but brain-wide connectivity patterns associated with GCA in youth, and the influence of SES on these connectivity patterns, are poorly understood. The present study examined functional connectomes from 5937 9- and 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) multi-site study. Using multivariate predictive modeling methods, we identified whole-brain functional connectivity patterns linked to GCA. In leave-one-site-out cross-validation, we found these connectivity patterns exhibited strong and statistically reliable generalization at 19 out of 19 held-out sites accounting for 18.0% of the variance in GCA scores (cross-validated partial η2). GCA-related connections were remarkably dispersed across brain networks: across 120 sets of connections linking pairs of large-scale networks, significantly elevated GCA-related connectivity was found in 110 of them, and differences in levels of GCA-related connectivity across brain networks were notably modest. Consistent with prior work, socioeconomic status was a strong predictor of GCA in this sample, and we found that distributed GCA-related brain connectivity patterns significantly statistically mediated this relationship (mean proportion mediated: 15.6%, p < 2 × 10−16). These results demonstrate that socioeconomic status and GCA are related to broad and diffuse differences in functional connectivity architecture during early adolescence, potentially suggesting a mechanism through which socioeconomic status influences cognitive development.
Over the past decade, formulation predictive dissolution (fPD) testing has gained increasing attention. Another mindset is pushed forward where scientists in our field are more confident to explore the in vivo behavior of an oral drug product by performing predictive in vitro dissolution studies. Similarly, there is an increasing interest in the application of modern computational fluid dynamics (CFD) frameworks and high-performance computing platforms to study the local processes underlying absorption within the gastrointestinal (GI) tract. In that way, CFD and computing platforms both can inform future PBPK-based in silico frameworks and determine the GI-motility-driven hydrodynamic impacts that should be incorporated into in vitro dissolution methods for in vivo relevance. Current compendial dissolution methods are not always reliable to predict the in vivo behavior, especially not for biopharmaceutics classification system (BCS) class 2/4 compounds suffering from a low aqueous solubility. Developing a predictive dissolution test will be more reliable, cost-effective and less time-consuming as long as the predictive power of the test is sufficiently strong. There is a need to develop a biorelevant, predictive dissolution method that can be applied by pharmaceutical drug companies to facilitate marketing access for generic and novel drug products. In 2014, Prof. Gordon L. Amidon and his team initiated a far-ranging research program designed to integrate (1) in vivo studies in humans in order to further improve the understanding of the intraluminal processing of oral dosage forms and dissolved drug along the gastrointestinal (GI) tract, (2) advancement of in vitro methodologies that incorporates higher levels of in vivo relevance and (3) computational experiments to study the local processes underlying dissolution, transport and absorption within the intestines performed with a new unique CFD based framework. Of particular importance is revealing the physiological variables determining the variability in in vivo dissolution and GI absorption from person to person in order to address (potential) in vivo BE failures. This paper provides an introduction to this multidisciplinary project, informs the reader about current achievements and outlines future directions.
The goal of this study was to create a mass transport model (MTM) model for gastric emptying and upper gastrointestinal (GI) appearance that can capture the in vivo concentration-time profiles of the nonabsorbable drug phenol red in solution in the stomach and upper small intestine by direct luminal measurement while simultaneously recording the contractile activity (motility) via manometry. We advanced from a one-compartmental design of the stomach to a much more appropriate, multi-compartmental 'mixing tank' gastric model that reflects drug distribution along the different regions of the stomach as a consequence of randomly dosing relative to the different contractile phases of the migrating motor complex (MMC). To capture the intraluminal phenol red concentrations in the different segments of the GI tract both in fasted and fed state conditions, it was essential to include a bypass flow compartment ('magenstrasse') to facilitate the transport of the phenol red solution directly to the duodenum (fasted state) or antrum (fed state). The fasted and fed state models were validated with external reference data from an independent aspiration study using another nonabsorbable marker (paromomycin). These results will be essential for the development and optimization of computational programs for GI simulation and absorption prediction, providing a realistic gastric physiologically-based pharmacokinetic (PBPK) model based on direct measurement of gastric concentrations of the drug in the stomach.
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