PhD Student University of Southern California, United States
Introduction:: Mental health diseases account for 32% of years lived with disability and pose an estimated 2.5 trillion economic burden to the US. About 5% of US population will be impacted by the bipolar disorder. Bipolar disorder is associated with major mood swings with deep depressed states and emotional highs. Lithium therapy (Li+) is currently the primary and the most reliable treatment for bipolar disease and mood disorders. Lithium therapy has been reliable and effective, but it comes with a big challenge of a small therapeutic window of lithium, and acute toxicity of lithium. The effective and safe serum Li+ levels are 0.4 to 1.0 mM. Higher dosages (≥1.2 mM) pose a risk of acute toxicity. There is a high rate (15%–35%) of acute kidney damage in bipolar patients that receive lithium therapy.
Materials and Methods:: Sensor fabrication uses cotton yarn, and an in-house made carbon black conductive ink. A potentiometric sensing membrane that is selective to lithium is then added to the tip of the yarn. Sensors are characterized using impedance spectroscopy, potentiometry, and amperometric analysis of sensor capacitance. Validation is done in commercial biolfuids (serum, urine, and saliva).
Results, Conclusions, and Discussions:: Current paradigm of lithium testing requires the patient to visit the hospital, submit blood samples, and wait for sample analysis in the pathology lab. A companion diagnostic device capable of real-time monitoring of lithium levels in biofluids of the patient will revolutionize lithium therapy and enable a personalized dosage of this life-saving drug. This device enables frequent monitoring of Li+ in biofluids to detect toxic dosages, and substantially lower the acute toxicity and organ damage caused by Li+. This work shows a low-cost and compact potentiometric sensor bundle that can selectively measure Li+ in different biofluids (saliva, serum, sweat, urine) at the convenience of home, and inform the patient on a toxic or effective lithium dosage. Technical challenges for addressing selectivity issues, and sample volume will be discussed.
Acknowledgements (Optional): : We thank the Zumberge team building award and Powell research award to M. Mousavi.