Advances in Organs-on-a-Chip Engineering

Dear Colleagues,

Advances in microfabrication, stem cell technology, tissue engineering, and mathematical modeling have created unprecedented in vitro models—organs-on-a-chip (OOC) systems—to predict risk and efficacy of drugs candidates, and accelerate their steps to the market. Another critical advantage of OOC is its potential to replace, reduce, and refine animal testing. Most recently, the FDA’s alternative methods working group have proposed OOC and microphyisological systems (MPSs) as official models to evaluate drug candidates for IND application and to build disease models. Currently, OOC and MPS have been defined as consisting of engineered miniaturized physiological environments to mimic tissue microenvironments. Micro-tissue units, e.g., self-assembled, differentiated, 3D-printed or tissue-engineered units, were constructed within this microchip and microenvironment, and were engineered to recapitulate the specified/targeted tissue or organ responses. OOC and MPS have been applied in drug evaluation, personalized medicine, disease modeling, space medicine, and many other fields. Highly automated and AI-based OOC systems, integrating cell culture, imaging, and data analysis, are of great interest to OOC researchers and potential users. This Special Issue aims to provide selected contributions on advances in the fabrication, characterization, and application of organs-on-a-chip systems.

Potential topics include, but are not limited to, the following:

• The development of materials for construction of tissue microenvironment;
• Organs-on-a-chip system design and fabrication;
• The development of novel in vitro tissue models;
• Drug evaluation using OOC or MPS;
• The development of in vitro disease models;
• Database for organoid and OOC research;
• AI-based OOC imaging and data analysis.

Dr. Zaozao Chen
Dr. Mingqiang Li
Guest Editors

Manuscript Submission Information

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• organs-on-a-chip
• microphysiological system
• microfluidics
• organoid
• drug screening
• disease modeling