No abstract

Many highly effective chemotherapeutic agents can only be administered intravenously as their oral delivery is compromised by low gastro-intestinal solubility and permeability. ) is one such drug; however, recently synthesized lipophilic prodrugs offer a potential solution to the low oral bioavailability issue. Here we introduce a microfluidic-based intestine-on-a-chip (IOAC) model, which has the potential to provide new insight into the structure− permeability relationship for lipophilic prodrugs. More specifically, the IOAC model utilizes external mechanical cues that induce specific differentiation of an epithelial cell monolayer to provide a barrier function that exhibits an undulating morphology with microvilli expression on the cell surface; this is more biologically relevant than conventional Caco-2 Transwell models. IOAC permeability data for SN38 modified with fatty acid esters of different chain lengths and at different molecular positions correlate excellently with water−lipid partitioning data and have the potential to significantly advance their preclinical development. In addition to advancing mechanistic insight into the permeability of many challenging drug candidates, we envisage the IOAC model to also be applicable to nanoparticle and biological entities.

Current organ-on-a-chip (OoC) systems mimic important aspects of specific organ and tissue functions, however, many commercial and academic devices are either too simple for advanced assays or require a complicated...

An intestine-on-a-chip model was used for the first time to study the intestinal uptake of nanoparticulate oral drug carriers and their ability to overcome the mucus barrier.

Organ-on-a-Chip (OoC) systems bring together cell biology, engineering, and material science for creating systems that recapitulate the in vivo microenvironment of tissues and organs. The versatility of OoC systems enables in vitro models for studying physiological processes, drug development, and testing in both academia and industry. This paper evaluates current platforms from the academic end-user perspective, elaborating on usability, complexity, and robustness. We surveyed 187 peers in 35 countries and grouped the responses according to preliminary knowledge and the source of the OoC systems that are used. The survey clearly shows that current commercial OoC platforms provide a substantial level of robustness and usability—which is also indicated by an increasing adaptation of the pharmaceutical industry—but a lack of complexity can challenge their use as a predictive platform. Self-made systems, on the other hand, are less robust and standardized but provide the opportunity to develop customized and more complex models, which are often needed for human disease modeling. This perspective serves as a guide for researchers in the OoC field and encourages the development of next-generation OoCs.