In Vitro-In Vivo Correlation of Blood-Brain Barrier Permeability of Drugs: A Feasibility Study Towards Development of Prediction Methods for Brain Drug Concentration in Humans.

Purpose: In vitro human blood-brain barrier (BBB) models in combination with central nervous system-physiologically based pharmacokinetic (CNS-PBPK) modeling, hereafter referred to as the "BBB/PBPK" method, are expected to contribute to prediction of brain drug concentration profiles in humans. As part of our ongoing effort to develop a BBB/PBPK method, we tried to clarify the relationship of in vivo BBB permeability data to those in vitro obtained from a human immortalized cell-based tri-culture BBB model (hiBBB), which we have recently created.

Methods: The hiBBB models were developed and functionally characterized as previously described.

E7386, a Selective Inhibitor of the Interaction between β-Catenin and CBP, Exerts Antitumor Activity in Tumor Models with Activated Canonical Wnt Signaling.

The Wnt/β-catenin signaling pathway plays crucial roles in embryonic development and the development of multiple types of cancer, and its aberrant activation provides cancer cells with escape mechanisms from immune checkpoint inhibitors. E7386, an orally active selective inhibitor of the interaction between β-catenin and CREB binding protein, which is part of the Wnt/β-catenin signaling pathway, disrupts the Wnt/β-catenin signaling pathway in HEK293 and adenomatous polyposis coli ()-mutated human gastric cancer ECC10 cells. It also inhibited tumor growth in an ECC10 xenograft model and suppressed polyp formation in the intestinal tract of mice, in which mutation of activates the Wnt/β-catenin signaling pathway.

A Human Immortalized Cell-Based Blood-Brain Barrier Triculture Model: Development and Characterization as a Promising Tool for Drug-Brain Permeability Studies.

Brain microvascular endothelial cells (BMEC), together with astrocytes and pericytes, form the blood-brain barrier (BBB) that strictly restricts drug penetration into the brain. Therefore, in central nervous system drug development, the establishment of an human BBB model for use in studies estimating the human BBB permeability of drug candidates has long been awaited. The current study developed and characterized a human immortalized cell-based BBB triculture model, termed the "hiBBB" model.

In Silico Prediction of Major Clearance Pathways of Drugs among 9 Routes with Two-Step Support Vector Machines.

Purpose: The clearance pathways of drugs are critical elements for understanding the pharmacokinetics of drugs. We previously developed in silico systems to predict the five clearance pathway using a rectangular method and a support vector machine (SVM). In this study, we improved our classification system by increasing the number of clearance pathways available for our prediction (CYP1A2, CYP2C8, CYP2C19, and UDP-glucuronosyl transferases (UGTs)) and by accepting multiple major pathways.

In silico prediction of major drug clearance pathways by support vector machines with feature-selected descriptors.

We have previously established an in silico classification method ("CPathPred") to predict the major clearance pathways of drugs based on an empirical decision with only four physicochemical descriptors-charge, molecular weight, octanol-water distribution coefficient, and protein unbound fraction in plasma-using a rectangular method. In this study, we attempted to improve the prediction performance of the method by introducing a support vector machine (SVM) and increasing the number of descriptors. The data set consisted of 141 approved drugs whose major clearance pathways were classified into metabolism by CYP3A4, CYP2C9, or CYP2D6; organic anion transporting polypeptide-mediated hepatic uptake; or renal excretion.