(New York, NY) – November 4th, 2013 – Ai Cure Technologies, an artificial intelligence company providing advanced facial recognition solutions to monitor medication adherence, today announced it was awarded a highly competitive National Institutes of Health (NIH) innovation grant in the amount of $1 million by the National Institute on Drug Abuse (NIDA).
Ai Cure’s platform, AiView-HRTM, uses facial recognition software to automate the process of DOT (Directly Observed Therapy), confirming that a patient has ingested the right medication at the right time. Instead of relying on derivative measures to confirm adherence such as pill counts, text messages, or electronic pill bottles – that imply but do not confirm medication ingestion – AiView-HRTM accurately confirms in real time the patient’s identity, medication, and dosing. The monitoring and intervention platform was developed as a software solution to maximize flexibility and scalability, and to ensure high accuracy and reliability of data.
The NIDA grant will fund Phase II of a research study to demonstrate the efficacy and validity of Ai Cure’s platform to monitor and confirm medication adherence in a population being treated for opioid dependence with Suboxone® maintenance. The multi-site, parallel-arm, randomized trial will take place across four sites serving two large metropolitan areas. Patients assigned to the AiView-HRTMarm of the study will be compared to a control group who are not being monitored. All patients will receive treatment as usual (TAU). Preliminary data from Phase I suggest that patients using the Ai Cure platform will be significantly more adherent to treatment.
Opioid-dependent populations are particularly at risk for nonadherence, with over half suffering from AT Least one co-morbid psychiatric disorder. The presence of multiple barriers to treatment and the potential for misuse and diversion of Suboxone® also present their own set of challenges. Yet for those receiving treatment, full adherence has been shown to substantially decrease the risk of abusing other drugs, being incarcerated or engaging in high-risk behavior. It is estimated that the financial cost for untreated opioid dependency is $20 billion per year.
The digital health platform works in real time and leverages mobile platforms such as smartphones to confirm whether a patient has correctly taken their medication. Data from each dosing are automatically stored on a centralized dashboard and provide a continuous audit trail of patient adherence over time. Clinical trial coordinators or providers can access individual adherence trends in real time and use predictive algorithms to facilitate risk-based and tailored intervention.
The study is being performed in collaboration with the Cincinnati Addiction Research Center (CinARC) led by Dr. Eugene Somoza, MD, PhD.
Connect with Ai Cure Technologies:
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About Ai Cure Technologies
Ai Cure Technologies (www.aicure.com) is an NIH-funded artificial intelligence company that has developed facial recognition and computer vision software to automate the process of DOT (Directly Observed Treatment), confirming that the right patient has ingested the right medication at the right time. The monitoring and intervention platform has been developed as a software as a service to maximize flexibility and scalability. The company is the recipient of multiple National Institutes of Health (NIH) innovation grants and has been awarded in excess of $3.4 million in NIH funding.
About National Institute on Drug Abuse (NIDA)
The mission of the National Institute on Drug Abuse is to lead the Nation in bringing the power of science to bear on drug abuse and addiction. This charge has two critical components. The first is the strategic support and conduct of research across a broad range of disciplines. The second is ensuring the rapid and effective dissemination and use of the results of that research to significantly improve prevention and treatment and to inform policy as it relates to drug abuse and addiction. Research reported in this release was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number HHSN271201300036C. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.