(128c) Multi-Sensor Integration into Multi-Layer Organ-on-Chip | AIChE

(128c) Multi-Sensor Integration into Multi-Layer Organ-on-Chip


Brady, R. - Presenter, Northeastern University
Bindas, A. J., New Jersey Institute of Technology
Koppes, R., Northeastern University
Koppes, A., Northeastern University
Wheeler, E., Northeastern University
Organ-on-chips (OOCs) have the potential to serve as lab-scale biological and disease models, mitigating the need for animal modeling. The ability to utilize OOCs as in vitro platforms requires cost effectiveness, reliability, and high throughout system analysis. The challenges of collecting real time data represent a major shortcoming of many current OOC platforms. Traditionally, cellular characteristics have been analyzed via microscopy and other off-device instruments or assays. Current tests for viability or relevant biomarkers require off-chip handling and endpoint analysis. Integration of continuous and parallel data collection would increase the resolution of data collected and minimize sample handling. Several OOCs have been designed which measure mechanical, electrical, and chemical activities of OOCs. However, most systems integrate only a single sensing capacity. In order to provide a more complete analysis of tissue function or stasis, the ability to collect multiple continuous data sets is required. To this end, our previously reported ‘cut & assemble’ manufacturing technique was applied to integrate multiple biosensors into a tailorable OOC system1. This project aimed to develop a platform for the measurement of pH, O2, and fluorescent spectrometry for continuous monitoring of culture conditions.

A series of optical sensors were integrated for continuous monitoring of culture conditions. LEDs and photodiodes were integrated to detect pH and oxygen via phenol red and an oxygen sensitive dye (Figure 1). Commercial fiber optic components were used to conduct fluorescent spectrometry on the device. The pH and O2 sensors were designed to allow integration upstream and downstream of an OOC while the spectrometric components could be directly integrated into the OOC device. The system was tested with several standard solutions as well as biological systems to prove effective function. The system was able to effectively monitor culture conditions for up to 7 days based on a CACO2 monolayer model. The spectrometer was used to characterize barrier integrity via the diffusion of fluorescently tagged molecules.

The integration multiple sensor components into OOC devices represents the first step towards the development of a standard OOC platform for tissue and disease modeling. The system was designed to allow for integration of multiple sensors to customization allow for specific applications. Multiple fibers could be used to discretely measure culture conditions in varying geometric regions of the device. Further, the spectrometer could be combined with other fluorescent assays such as ELISA in order to provide inline molecular detection. The pH and O2 sensors could be integrated into a process control system to minimize variation in culture conditions and maintain stasis. In summary, the integration of these 3 microfluidic sensors would allow the collection of continuous high-resolution data, increasing the relevance of OOC models.

Figure 1: CAD visualization of integrated oxygen and pH sensors on OOC platform. All major components are shown with some device layers omitted for visual simplicity.

  1. Hosic S, Bindas AJ, Puzan ML, et al. Rapid Prototyping of Multilayer Microphysiological Systems. ACS Biomater Sci Eng. Published online May 20, 2020. doi:10.1021/acsbiomaterials.0c00190