3D printing technology in low-cost diagnostic sensors for neurological disorders

Nguyen H. B. Ho

doi:10.7273/000004984

This thesis focuses on developing low-cost and reliable diagnostic tools for the detection and monitoring biomarkers and pharmaceuticals related to Parkinson’s disease. With an emphasis on the emerging manufacturing technology of 3D printing, this thesis describes the fabrication, optimization and use of 3D printed carbon-based electrodes and 3D printed ion-selective membranes (ISMs). Using 3D printing allows for the rapid fabrication of sensors that are inexpensive, selective, sensitive and mass producible. This thesis will discuss results related to the detection of PD-related biomarkers and pharmaceuticals employing 3D printed electrodes. In chapter 2, by using Fused-Deposition Modelling (FDM) 3D printing to fabricate carbon-based electrodes, we demonstrate the utility of a new rapid activation protocol which provides drastically improved responses when compared to inactivated electrodes. These FDM 3D printed electrodes were successfully used towards the detection of dopamine and L-Dopa. The sensors displayed excellent linearity between 1 mM and 500 nM for dopamine and 2 mM – 1.9 µM for L-dopa. The sensors respond quickly, are portable and extremely low-cost. Chapter 3 highlights a new fabrication protocol for ion-selective membranes. Instead of using poly(vinyl) chloride (PVC), 3D-printable resin was used. The 3D printed ion-selective membranes are fabricated using stereolithographic (SLA) 3D printing and resulted in rapid detection of benzalkonium chloride in ophthalmic solutions. Tested in eyedrop solutions, the electrodes were able to detect 98 ± 6 % of the benzalkonium chloride in the samples. Using a similar approach sensor were fabricated for the detection of acetylcholine, an important neurotransmitter directly related to PD disease. Linear calibrations with Nernstian responses of 55 mV/Decade across a range of 10 mM to 78 µM Ach+ were obtained along with excellent stability over long term run. With the innovation of 3D printed membrane for potentiometry, the results suggest a strong potential for using these in future applications ranging from quality control to point-of-care companion diagnostics. Lastly, in chapter 4, the use of 3D printing towards detecting i) hippuric acid, an emerging biomarker for PD and ii) 3-phenoxybenzoic acid, a metabolite from exposure to pesticides. Preliminary results shown in Chapter 4 using 3D printed potentiometric sensors shows slightly sub-Nernstian slopes of 50 and 47 mV/Decade for hippuric acid and 3-phenoxylbenzoic acid, respectively.

3D printing technology in low-cost diagnostic sensors for neurological disorders

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