Evaluation of Perfusion Cell Culture Conditions in a Double-Layered Microphysiological System Using AI-Assisted Morphological Analysis

In recent years, microphysiological systems (MPS) using microfluidic technology as a new in vitro experimental system have shown promise as an alternative to animal experiments in the development of drugs, especially in the field of drug discovery, and some reports have indicated that MPS experiments have the potential to be a valuable tool to obtain outcomes comparable to those of animal experiments. We have commercialized the Fluid3D-X®, a double-layer microfluidic chip made of polyethylene terephthalate (PET), under the Japan Agency for Medical Research and Development (AMED) MPS development research project and have applied it to various organ models. When intestinal epithelial cells, Caco-2, were cultured using Fluid3D-X® and a peristaltic pump, villi-like structures were formed in the microchannels. Still, the degree of formation differed between the upstream and downstream sides. To examine the consideration points regarding the effects of the nutrient and oxygen supply by the chip material and the medium perfusion rate and direction on cells in the widely used double-layer microfluidic chip and to demonstrate the usefulness of a new imaging evaluation method using artificial intelligence technology as an assistive tool for the morphological evaluation of cells, the cell morphology in the channels was quantified and evaluated using the Nikon NIS.ai and microscopic observation. Villi-like structures were predominant upstream of the top channel, independent of the medium perfusion on the bottom channel, and those structures downstream developed with an increased flow rate. Additionally, compared to the Fluid3D-X®, the chip made of PDMS showed almost uniform villi-like sterilization in the channel. The result indicates that the environment within the microchannels differs because the amount of nutrients and oxygen supply varies depending on the medium’s perfusion and the material of the chips. As the amount of oxygen and nutrients required by different cell types differs, it is necessary to study the optimization of culture conditions according to the characteristics of the cells handled. It was also demonstrated that the AI-based image analysis method is helpful as a quantification method for the differences in cell morphology in the microchannel observed under a microscope.