Recent Developments in Microfluidic Platforms for Immunological Testing

Introduction

Drug and vaccine development is a lengthy and resourceintensive process with significant costs that can be reduced by effective preclinical testing. Microfluidic Organoid or Organ-ona- Chip systems are microfluidic models of tissues and with 3D architecture that allows mimicry of native tissue interactions in organs, with multiple connected organoid systems that can have inline sensors for monitoring and control of flow between chips are termed body-on-a-chip [1-3]. Development of an immunological component of body-on-chip is especially important for testing biopharmaceuticals that can have unpredictable effects such as uncontrolled cytokine release, preventing such leads from entering clinical trials prematurely [4]. Furthermore, a functioning immune system model will allow testing of small molecule drugs, biopharmaceuticals, vaccines as well as evaluate biocompatibility of implanted medical devices, and evaluate tissue interactions preceding organ transplantation. Incorporation of immune organs into circuits with liver-on-chip, heart-on-chip; can accelerate preclinical testing and become substrate for building models for disease pathophysiology. Furthermore, study of immune organson- a-chip generates insight that can make inroads for discovering regenerative therapies for immune deficiencies. Crosstalk between immune organs such as thymus, lymph node and bone marrow in body-on-a-chip systems will produce mimicry of organ-to-organ communication that benefits modeling systems where a complex immunological component is involved [4,5], including drug and device testing and other novel therapeutics where a cascade of immunological events are encountered.

Immune Organs on a Chip

Current immune testing has evolved rapidly, ranging from in silico prediction of epitopes to proteomic-based binding assays [6]. In cell-based systems, most assays involved coculture in membrane-separated compartments, but some advocate for true 3D architecture organoids [6,7]. Fortunately, the field benefits from the existence of proof-of-concept microfluidic organoid models for lymph node and bone marrow [1,2]. Including thymus gland is important for recapitulating a physiologically realistic model system because of pharmacokinetic volume effects due to the relative sizes of each organ compartment in the chip system [1] and because of thymus effects on T Cell pool size to accurately recreate in vivo conditions. Thymus can be grown in explant culture using the hanging drop method [8], the first attempt at thymic organoid culture used tantalum-coated carbon matrix scaffolds [9]. Attention has focused on growth and differentiaton of Thymic Epithelial Cells (TEC) because of their role in selection of T Cells [10,11]. Existing protocols for 3D organotypic culture of TEC employ a variety of scaffolds including foamed tantalum and recellularized extracellular matrix [9,12]. With further development of a 3D immune organoid systems, it will be possible to continue efforts characterizing the mechanical interactions of: TECs and T Cell precursors; interactions within a TEC layer; interactions between T Cells and endothelial cells; and interactons between T Cells encountering antigen-presenting-cells (APCs) [13,14]. DNA-probes can enhance the sensitivity of the system by measuring pico newton forces in short-lived interactions as well as characterization of cellsubstrate interactions [15]. Placement of cell-laden scaffolds into specific loci during the layout design of polydimethylsiloxane PDMS microchannels facilitates connection to a Body-on-Chip system [2,3].

Microfluidic Multisensor Monitoring on Immune Body on a Chip

To characterize and regulate a dynamic body-on-chip system it is important to be able to monitor concentrations of specific biomarkers of interest and chemical conditions in real-time [3,16]. With limited effluent from individual organoid systems, multisensor systems capable of detecting multiple analytes become a necessary component of body-on-a-chip systems. The mode of detection for multisensor systems range from electrobiochemical to arrays of cellular biosensors [17-19]. Successful monitoring of complex biological data generated by each organoid system can be aided by machine learning analysis [17,20,21] (Table 1).

Table 1:

Conclusion

The development of Body-on-a-Chip Networks of organoids matures rapidly. The recreation of 3D-architectures in vitro allows for physiologically realistic models for preclinical testing. Generation of preclinical pharmacokinetic and pharmacodynamic data can be accelerated while minimizing the use of animal models. Furthermore, these model systems offer potential for increasing basic understanding of the development and formation of the organs comprising the immune system.

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