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.

BackgroundIron deficiency anemia (IDA) is a common extra-intestinal manifestation of celiac disease (CD). Little is known about the frequency with which primary care physicians (PCPs) test for CD in patients with IDA. We aimed to describe how PCPs approach testing for CD in asymptomatic patients with IDA.MethodsWe electronically distributed a survey to PCPs who are members of the American College of Physicians. Respondents were asked whether they would test for CD (serologic testing, refer for esophagogastroduodenoscopy [EGD], or refer to GI) in hypothetical patients with new IDA, including: (1) a young Caucasian man, (2) a premenopausal Caucasian woman, (3) an elderly Caucasian man, and (4) a young African American man. These scenarios were chosen to assess for differences in testing for CD based on age, gender, and race. Multivariable logistic regression was used to identify independent predictors of testing.ResultsTesting for CD varied significantly according to patient characteristics, with young Caucasian men being the most frequently tested (61% of respondents reporting they would perform serologic testing in this subgroup (p<0.001)). Contrary to guideline recommendations, 80% of respondents reported they would definitely or probably start a patient with positive serologies for CD on a gluten free diet prior to confirmatory upper endoscopy.ConclusionsPCPs are under-testing for CD in patients with IDA, regardless of age, gender, race, or post-menopausal status. The majority of PCPs surveyed reported they do not strictly adhere to established guidelines regarding a confirmatory duodenal biopsy in a patient with positive serology for CD.

Background Adenoma detection rate (ADR) and sessile serrated polyp detection rate (SSPDR) data in surveillance colonoscopy are limited. Aims Our aim was to determine surveillance ADR and SSPDR and identify associated predictors. Methods A retrospective review of subjects who underwent surveillance colonoscopy for adenoma and/or SSP at an academic center was performed. The following exclusion criteria were applied: prior colonoscopy ≤ 3 years, incomplete examination, or another indication for colonoscopy. Patient, endoscopist, and procedure characteristics were collected. Predictors were identified using multivariable logistic regression. Results Of 3807 colonoscopies, 2416 met inclusion criteria. Surveillance ADR was 49% and, SSPDR was 8%. Higher ADR was associated with: age per year (OR 1.03; 95% CI 1.02–1.04), male gender (OR 1.55; 95% CI 1.29–1.88), BMI per kg/m2 (OR 1.02; 95% CI 1.01–1.04), withdrawal time per minute (OR 1.09; 95% CI 1.07–1.10), and endoscopists’ screening ADR (OR 1.01; 95% CI 1.00–1.03). Years since training (OR 0.99; 95% CI 0.98–0.99) was associated with lower ADR. Family history of CRC (OR 1.58; 95% CI 1.02–2.27) and endoscopists’ screening ADR (OR 1.40; 95% CI 1.15–1.74) were associated with higher SSPDR. African-American race (OR 0.36; 95% CI 0.10–0.75) and diabetes (OR 0.41; 95% CI 0.21–0.76) were associated with lower SSPDR. Conclusions For surveillance colonoscopy, nearly half of patients had an adenoma and one in twelve had an SSP. In addition to established factors, BMI, endoscopists’ screening ADR, and years since training were associated with ADR, whereas African-American race and diabetes were inversely associated with SSPDR. Further studies are needed prior to integrating surveillance ADR and SSPDR into quality metrics.

The goal of this project was to explore and to statistically evaluate the responsible gastrointestinal (GI) factors that are significant factors in explaining the systemic exposure of ibuprofen, between and within human subjects. In a previous study, we determined the solution and total concentrations of ibuprofen as a function of time in aspirated GI fluids, after oral administration of an 800 mg IR tablet (reference standard) of ibuprofen to 20 healthy volunteers in fasted state conditions. In addition, we determined luminal pH and motility pressure recordings that were simultaneously monitored along the GI tract. Blood samples were taken to determine ibuprofen plasma levels. In this work, an in-depth statistical and pharmacokinetic analysis was performed to explain which underlying GI variables are determining the systemic concentrations of ibuprofen between (inter-) and within (intra-) subjects. In addition, the obtained plasma profiles were deconvoluted to link the fraction absorbed with the fraction dissolved. Multiple linear regressions were performed to explain and quantitatively express the impact of underlying GI physiology on systemic exposure of the drug (in terms of plasma C max /AUC and plasma T max ). The exploratory analysis of the correlation between plasma C max /AUC and the time to the first phase III contractions postdose (TMMC-III) explains ∼40% of the variability in plasma C max for all fasted state subjects. We have experimentally shown that the in vivo intestinal dissolution of ibuprofen is dependent upon physiological variables like, in this case, pH and postdose phase III contractions. For the first time, this work presents a thorough statistical analysis explaining how the GI behavior of an ionized drug can explain the systemic exposure of the drug based on the individual profiles of participating subjects. This creates a scientifically based and rational framework that emphasizes the importance of including pH and motility in a predictive in vivo dissolution methodology to continued...