The objective of MC-Nano is to develop a functional multi-nanopore for continuous monitoring of metabolites in complex biological samples. Initially, the target was identified in patients with heart failure. However, the nanopore sensors have the potential to be applied to a diverse range of molecules. The plan was to assess their technical and commercial viability within the healthcare sector. To achieve this objective, both technical and commercial feasibility activities will be conducted. Specifically, MC-Nano envisioned the following four activities:
Activity 1: Development of a sodium biosensor to analyse the ionic composition of solutions and a wide range of relevant protein biomarkers: We validate the developed sodium biosensor, to analyse the ionic composition of solutions and a wide range of relevant protein biomarkers.
Activity 2: Development of a high- stability polymer membrane for urine interfaces, and integrate the nanopores into said membrane: we develop a high-stability polymer membrane for urine and blood interfaces, and integrate the nanopores into a block copolymer membrane.
Activity 3: Development of an algorithmic machine learning software to link and analyse data-output from nanopores in order to obtain valuable medical insights: we develop the algorithm and software to analyse data-output from nanopores so that it can obtain valuable medical insights. The algorithm was capable of identifying complex molecules, such as insulin, in blood, and other molecules in urine.
Activity 4: Exploring the commercial feasibility of the MC- Nano biological nanopore tool: we facilitate our knowledge transfer strategy. The commercial feasibility activities will be conducted to establish a clear pathway from the research towards innovation. This includes, conducting a freedom-to-operate (FTO) search to pave the way for technology commercialization and patenting, analysing market trends and competition within the diagnostic device sector, and collaborating with five academic entities and industry partners for MC-Nano's further development.
During this proof-of-concept, we identified continuous insulin detection in blood as a promising application. Insulin, a key metabolic regulator, directly impacts glycemic control, making its management crucial in diabetes (affecting ~10% of adults). Currently, diabetic patients rely on continuous glucose monitoring because home-diagnostic devices cannot directly detect insulin. While glucose and insulin levels often correlate, this relationship breaks down in various pathologies. Consequently, the lack of real-time, sensitive insulin detection technologies hinders continuous monitoring, despite its importance. Affordable, continuous insulin detection would transform health monitoring and personalize disease management.
Our work on nanopore-based insulin detection has yielded a nanopore capable of identifying insulin. To address interference from other blood proteins, we developed a machine learning approach to differentiate insulin blockades from those of contaminants. We have filed an IP for these results and are preparing them for publication. Regarding valorization, we've identified partners for a potentially spin off.
