Objective
Organ on Chip (OoC) technology, which models human tissues in vitro, is poised to refactor the drug discovery pipeline and alleviate the financial burden with the added benefit of reducing/ refining animal experimentation. The advent of non-destructive, biosensing modalities has placed data-driven approaches to identifying new therapeutics within reach, where highly parallelized instances of human organ models can be mined for AI and ML-augmented discovery. During our ERC CoG grant, we developed a novel technology which combines these two frontiers; by fabricating porous scaffolds from conducting polymer hydrogels, we were able to culture 3D organotypic models of human epithelial tissues, while conducting highly sensitive, non-destructive electrochemical monitoring of the tissues. During our previous IMBIBE PoC grant, we showed that our technology was compatible with a fluidic platform produced by an industry partner. However, in doing so, we identified a major pain point in the OoC ecosystem: the step discontinuity in the level of complexity, both of the tissue model and the typical OoC form factor, is too great to allow for integration into current industry workflows. This barrier to adoption is crippling and needs to be addressed by harmonising platform form factor with industry standards. Here, we propose pivoting our current technology to meet this need by radically altering our fabrication methodology, opting for hydrogel electrospinning, we can produce simplified OoC platforms, which represent the smallest possible adoption cost to our industry partners, while providing for highly scalable continuous monitoring of the tissues. Further, our proposal will facilitate the process of gradual evolution of tissue model and sensor complexity, without disrupting industrial workflow, to allow convergence between the state of the art in the pharmaceutical ecosystem and the bleeding edge technological advancements being made in the academic sector.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural scienceschemical sciencespolymer sciences
- natural sciencesbiological sciencesecologyecosystems
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
CB2 1TN Cambridge
United Kingdom