3D tissue models with integrated sensor technology

In the development of new drugs as well as in the evaluation of biological, chemical or physical risks, 3D tissue models cultivated in the laboratory are becoming increasingly important compared to less realistic, but so far commonly used 2D cell layers. In addition to biological tissue models, which are far advanced in development, analytical measurement and analysis methods are required to make the response of cells to external stimuli measurable as quantitatively as possible. Up to now, this has usually required dissecting the tissue in order to access the deeper-lying cells. Researchers at Fraunhofer EMFT are working on a fundamentally new concept to enable non-invasive investigation of the reactions of artificially cultivated cells to external stimuli.

Cell-based assays in Petri dishes

In the TissueSense project, researchers at Fraunhofer EMFT are working on a fundamentally new concept: Instead of subsequently inserting sensory functions (electrodes, nanoprobes) into the model tissues or disassembling them for analysis after a specified exposure time, the 3D tissue model is assembled layer by layer from individual layers, similar to a building block principle. The individual tissue layers are first grown in 2D by culturing cell monolayers on thin, porous polymer supports with integrated signal transducers. Subsequently, the tissue layers are assembled layer by layer from these 2D constructs. Since the polymer supports have a porous structure, the individual cell layers come into contact with each other after assembly into a 3D construct and can exchange substances. Equipping the polymer supports with signal transducers allows chemical or physical information of each individual cell layer of the 3D tissue model to be derived non-invasively and in real time to the outside.

Especially for the screening of substance libraries on customized organ models, this opens up completely new perspectives with regard to the quality of the accessible biomedical information as well as for the economy and throughput of such test series.

The project has been funded since 01.07.2018 as part of Fraunhofer's internal Discover program, grant number 027600628.

 

 

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