Substance use disorder (SUD) is a major health problem with direct and indirect impact on healthcare and societal cost that is estimated at over $181 billion annually in the United States. Opioids are the second most abused substances and buprenorphine (BUP) is an effective and safe medication for opioid dependence. However, BUP remains a narcotic, and strict BUP compliance is critical for patients to obtain the best treatment outcome, prevent relapse, and avoid medication diversion. Compliance is commonly monitored by periodic and random urine tests at hospital visits. However, due to long intervals between each periodic urine drug test, high cost and intrusiveness of random drug testing of a patient, such a measure has not been sufficient to prevent the diversion of BUP for unintended use. Therefore random urine drug tests that are inexpensive, convenient to use, and provide real time test results to doctors while maintaining the privacy of the patients will boost medication compliance. While many methods have been developed for the urine tests and for electronic monitoring, few test technologies meet all of the above requirements, likely due to the fact that new POC devices are costly to develop and expensive to manufacture, particularly when the devices are new to the market. To overcome this limitation, Prof. Yi Lu's group at the University of Illinois has reported a discovery that allows repurposing the widely available and low-cost personal glucose meter (PGM) for detecting many non- glucose targets. The innovation lies in converting the binding of non-glucose target (e.g. BUP) by its antibody to releasing the enzyme invertase which can hydrolyze sucrose into glucose and then quantified by PGM. Through this SHIFT award, we propose to transform the patent-pending discovery into commercial products. Through licensing the technology and recruiting two key members of the Lu group, GlucoSentient, Inc. plans to develop low-cost, at-home urine tests for BUP, norbuprenorphine (norBUP), a major dealkylated metabolite of BUP using the PGM. By developing test strips that are compatible with existing PGMs, we will take advantage of over 30 years of PGM research and circumvent the costly hardware development process. The recent successful launch of FDA-approved smartphone-enabled PGMs will enable wireless transmission of reminders, test results, and data analysis through smartphone apps. The goal of the Phase I research is to demonstrate the feasibility of using a smartphone attached PGM to: (1) detect BUP and norBUP at 10 ng/mL in buffer solution and urine;(2) develop test strips for BUP and norBUP with a limit of detection of 10 ng/mL in buffer solution;and (3) assess the performance of tests strips in urine samples. Accomplishing these specific aims will pave the way for Phase II research in developing both product prototypes and the smartphone platform. Successful applications of the proposed product will have significant impact on boosting compliance for not only BUP treatment, but also treatment of other SUDs.
As an effective drug for treating opioid dependence, the second most prevalent substance use disorder, buprenorphine requires consistent compliance to be an effective treatment and avoid misuse. To improve the current methods for monitoring compliance, which occurs during hospital visits, we will develop a low-cost, at- home urine test for buprenorphine using a smartphone-enabled glucose meter. This is possible via a patent- pending technology that converts the presence of buprenorphine into a glucose signal. Combining this technology with existing smartphone-enabled glucose meters will enable the wireless transmission of reminders, urine test results, and remote data analysis in a user-friendly format. We expect this technology will boost medication compliance for treatment of not only opioid dependent patients, but also other substance use disorder patients, thus lowering healthcare costs and improving patient lives.
|Lan, Tian; Zhang, Jingjing; Lu, Yi (2016) Transforming the blood glucose meter into a general healthcare meter for in vitro diagnostics in mobile health. Biotechnol Adv 34:331-41|
|Lan, Tian; Xiang, Yu; Lu, Yi (2015) Detection of protein biomarker using a blood glucose meter. Methods Mol Biol 1256:99-109|