Perfluoropolyether-Based Gut-Liver-on-a-Chip for the Evaluation of First-Pass Metabolism and Oral Bioavailability of Drugs.

In the evolving field of drug discovery and development, multiorgans-on-a-chip and microphysiological systems are gaining popularity owing to their ability to emulate in vivo biological environments. Among the various gut-liver-on-a-chip systems for studying oral drug absorption, the chip developed in this study stands out with two distinct features: incorporation of perfluoropolyether (PFPE) to effectively mitigate drug sorption and a unique enterohepatic single-passage system, which simplifies the analysis of first-pass metabolism and oral bioavailability. By introducing a bolus drug injection into the liver compartment, hepatic extraction alone could be evaluated, further enhancing our estimation of intestinal availability. In a study on midazolam (MDZ), PFPE-based chips showed more than 20-times the appearance of intact MDZ in the liver compartment effluent compared to PDMS-based counterparts. Notably, saturation of hepatic metabolism at higher concentrations was confirmed by observations when the dose was reduced from 200 µM to 10 µM. This result was further emphasized when the metabolism was significantly inhibited by the coadministration of ketoconazole. Our chip, which is designed to minimize the dead volume between the gut and liver compartments, is adept at sensitively observing the saturation of metabolism and the effect of inhibitors. Using genome-edited CYP3A4/UGT1A1-expressing Caco-2 cells, the estimates for intestinal and hepatic availabilities were 0.96 and 0.82, respectively; these values are higher than the known human in vivo values. Although the metabolic activity in each compartment can be further improved, this gut-liver-on-a-chip can not only be used to evaluate oral bioavailability but also to carry out individual assessment of both intestinal and hepatic availability.

Application of machine learning techniques in population pharmacokinetics/pharmacodynamics modeling.

Population pharmacokinetics/pharmacodynamics (pop-PK/PD) consolidates pharmacokinetic and pharmacodynamic data from many subjects to understand inter- and intra-individual variability due to patient backgrounds, including disease state and genetics. The typical workflow in pop-PK/PD analysis involves the determination of the structure model, selection of the error model, analysis based on the base model, covariate modeling, and validation of the final model. Machine learning is gaining considerable attention in the medical and various fields because, in contrast to traditional modeling, which often assumes linear or predefined relationships, machine learning modeling learns directly from data and accommodates complex patterns. Machine learning has demonstrated excellent capabilities for prescreening covariates and developing predictive models. This review introduces various applications of machine learning techniques in pop-PK/PD research.

Programmed immobilization of living cells using independent click pairs.

Therapeutic devices incorporating living cells or tissues have been intensively investigated for applications in tissue engineering and regenerative medicine. Because many biological processes are governed by spatially dependent signals, programmable immobilization of materials is crucial for manipulating multiple types of cells. In this study, click chemistry substrates were introduced onto the surfaces of cells and cover glass, and the cells were fixed on the cover glass via covalent bonds for selective cell deposition. Azide group (Az)-labeled living cells were prepared by metabolic labeling with azido sugars. Following the introduction of Az, TCO (trans-cyclooctene) was metabolically labeled into the living cells by reacting with TCO-DBCO (dibenzocyclooctyne). Az and TCO in the cells were detected using DBCO-FAM (fluorescein)and tetrazine-Cy3, respectively. The mixture of Az-labeled green fluorescent protein HeLa cells and TCO-labeled red fluorescent protein HeLa cells was reacted in a culture dish in which three different cover glasses, DBCO-, tetrazine-, or methyl-coated, were added. Az- or TCO-labeled cells could be immobilized in a functional group-dependent manner. Next, tetrazine-labeled cells were incubated on TCO- or Az-labeled cell layers instead of cover glass. Functional group-dependent immobilization was also achieved in the cell layer. Introducing substrates for the click reaction could achieve cell-selective immobilization on different patterned glass surfaces, as well as cell-cell immobilization.