• Therapeutic: Bacterial vaginosis (BV) is the most common vaginal infection worldwide (estimated to be worth 2.7 billion dollars in 2020 by Grandview Market Research) and is associated with important public health issues, such as preterm labor and the acquisition and transmission of sexually transmitted infections. Bacterial vaginosis is a type of vaginal inflammation caused by the overgrowth of bacteria naturally found in the vagina. Rates of BV are higher in underserved minority populations. Despite treatment options, cure rates remain low and high recurrence rates are widely reported. Drs. Sobel and Embil have developed a compound for this difficult to treat, unmet medical need. "As a physician whose practice has included a large number of BV patients over the years, I view this as a large advancement moving towards a curative treatment for this common, but challenging condition," said Dr. Sobel.  The unique (patent pending) combination therapy appears to improve efficacy of treatment and will be simple to use.  This novel BV therapy will decrease the risk for pre-term labor, acquiring sexually transmitted diseases (STDs), pelvic inflammatory disease, and infections after gynecological procedures. TC is assisting in identifying development milestones, appropriate funding mechanisms, and target markets for commercialization.

• AI for Sound Analysis: DeepWave uses artificial intelligence (AI) technology to deploy a sound analysis and enhancement platform. Designed as a scalable cloud service to provide sound analysis services, it was developed by Associate Professor of Computer Science, Ming Dong, Ph.D. With significant potential as a disruptive technology. Most of the relevant technology available in the market today focuses on high-end equipment, which is expensive, and often only available offline, limiting the ability to be used in live audio situations.  This novel technology will allow responders and others in noisy and potential dangerous environments to assess the situation and determine who exactly needs help and what type of assistance is needed. DeepWave was awarded MTRAC funding to support key development milestones to optimize the accuracy, speed and robustness of the underlying analytical models.  This work will be critical in positioning DeepWave as a next generation audio analysis technology solution, empowering various industries, such as call centers and emergency responders, to analyze audio information in a new manner. Technology Commercialization is currently working with the Team on creating and supporting a startup by assisting with team formation and business planning.

• Wayne Health Mobile Units: A multi skilled team from WSU developed & deployed Mobile Health Units specially-equipped vans with medical equipment around the metropolitan Detroit area. The program began as a rapidly deployed drive-through SARS-CoV-2 testing clinic that was housed in temporary canopy tent shelters at two fixed locations; one in Detroit and the other in Dearborn, Mich., during the first wave of the pandemic. As the local health department established its own large-scale drive-through testing site, the team pivoted toward a focus on patients from socially vulnerable areas who might lack transportation or otherwise be unable to access such services. "What stood out the most for us in this analysis is that the model challenges the existing paradigm of care and shows that we can reach vulnerable, difficult to reach members of the community by bringing services to them, using data to inform the process," said Phillip Levy, MD, MPH, Edward S. Thomas Endowed Professor in the Department of Emergency Medicine at Wayne State University. From April 2020 to March 2021, they evolved and expanded into offering other services, such as lipid testing and blood pressure measurement. Mobile health clinics benefit communities by making health care more affordable and accessible, which in turn improves patient outcomes. According to Mobile Health Map, for every 1 dollar spent on mobile health, 12 dollars are saved, resulting in a return on investment of 12:1. In emergencies, they save patients money by helping them avoid expensive emergency room visits. Primarily supporting underserved communities with poor health status and high use of emergency departments, each mobile clinic results in an average of 600 fewer emergency room visits each year. This translates to an average savings of one-fifth of the cost of care. Mobile also offers flexible, responsive care for isolated and vulnerable groups and newly displaced populations. The flexibility mobile clinics provide allows professionals to respond dynamically to a population's current and evolving health needs.

There are an estimated 2,000 mobile clinics located across the country, representing all states and the Washington, DC.  Services include primary care, preventive screening, disease management, behavioral health, dental care, pre-natal care, and pediatric care. Addressing the triple aim of patient outcomes, quality and cost, Mobile Health Map found:

• Mobile clinics are improving access to care with up to 6.5 million visits annually. Mobile clinics mainly serve the uninsured (60%) and the publicly insured (31%), and generally operate in low-income communities.
• Overall, mobile health clinics in the United States are getting more bang for their buck in providing quality care at a lower cost. The average return on Investment for mobile health is 12:1. That means for every 1 dollar spent, 12 dollars are saved.
• Mobile Clinics provide cost-effective prevention services that help people live long and healthy lives.  On average each mobile health clinic saves 65 quality adjusted life years every year of operation.  This means that each visit they save on average 1,600 hundred dollars due to this prevention.
• Mobile Clinics provide accessible care at a cheaper cost to the healthcare system than Emergency Department visits.  It is estimated that each mobile clinic results in 600 fewer Emergency Department visits every year.  This means that each visit to a mobile clinic saves on average 200 hundred dollars (approximately one fifth of an emergency visit).

• Factory Execution @ Speed of Thought (FE@ST) is an AI-enabled breakthrough solution featuring an automated self-adapting technology aimed at deploying a new generation of AI and automated industrial initiatives in both small and large scale industrial environments.  

Wayne State University Associate Professor of Industrial & Systems Engineering, Jeremy Rickli, Ph.D., is developing FE@ST, a hyper-scalable distributed AI-enabled solution featuring automated self-adapting capability, which provides near real-time insights on machine health/performance and ability to direct the users to the specific component(s) or subsystems attributing to performance erosion.

A major obstacle in introducing any proactive maintenance is the absence of effective technology to capture real-time performance data and capabilities to handle large volume datasets that could indicate when a machine or a factory system is likely to fail. Additional challenges associated with available enterprise manufacturing intelligence technologies are that they are very expensive and difficult to implement, requiring extensive training and dedicated resources to support data monitoring, perform data analysis and system maintenance. Ultimately, they do not provide accurate and timely information to effectively support preventive maintenance, provide process performance analytics, and production optimization.

The platform creates digital twins of the machine ecosystem within a framework that models performance indicators and interactions between machines. The technology creates its own accurate and high resolution (sub-second process events) machine performance datasets, delivers actionable-information at the maximum decision velocity (fast cycle time to action), and performs deep learning of complex operations, while a simple interface design allows virtually anyone to diagnose and pin-point the problem with minimal training or effort.

Preventive maintenance on machines in a manufacturing system is an essential element in modern factory operation. Equipment breakdowns is inevitable. However, smart preventive maintenance systems can reduce premature asset breakdowns, keep employees safe, and even save millions in costs. A study  shows around 82 percent of companies experiencing at least one unplanned downtime outages, costing companies 250,000 thousand per hour. And, according to a study from Buildings.com, it's estimated that running a piece of equipment to the point of failure costs up to 10 times as much as implementing a regular maintenance program would. This novel system will provide accurate and timely information to ultimately reduce the costs of factory maintenance and prevent equipment breakdowns.

FE@ST was awarded MTRAC funding to demonstrate the concept and feasibility of the technology platform. Achieving this objective addresses the competitive need for manufacturers to have instant access to machine performance anywhere in the world, reducing costly unplanned downtime to virtually zero. Technology Commercialization is currently working with the team on the formation of a startup.

• AI-enabled Augmented Reality (AR) Platform & Robotic Surgery: This family of innovations addresses the surgical bleeding problem for all types of surgical procedures a problem that results in potentially life-threatening complications and costs over 340 million dollars to the healthcare system each year. Bleeding is a major surgical complication. Although mortality rates of 0.1% are observed for surgical procedures, it may be 5% to 8% for elective vascular surgery, and increases to 20% in the presence of severe bleeding. When a bleed happens (especially with remotely controlled surgical robotic systems), the lens or surgical field can be completely obstructed with blood and the surgeon does not have many good options. Removing tools or suctioning can cause more damage. This system will detect bleeding and mark it for the surgeon on an AR display so even if he or she cannot see the source, they can locate and stop the bleeding which will reduce life threatening complications.  The AI-AR platform improves robotic surgical safety with advanced surgeon-user interfaces that improve visualization of the surgical field, enhance camera control, predict likely surgical bleeds and facilitate rapid repair of surgical bleeds. According to Grandview Research, the global surgical robots' market is expected to grow at a compound annual growth rate (CAGR) of 19.3% from 2022 to 2030 to over 20 billion dollars, owing to a global shortage of physicians and surgeons and increasing adoption of automated instruments for surgery. No research projections are available on the value of robotic software, whether developed by an equipment manufacturer or by a third party. The lead inventor, Abhilash Pandya, PhD, Professor and Undergraduate Program Director, Electrical and Computer Engineering said, "The WSU Technology Commercialization Office has provided the matching funds and has given us outstanding mentor support. We have had help submitting (and getting) a Small Business Technology Transfer (STTR) innovation grant from National Science Foundation (NSF), support to create patents (we now have 2 provisional patents approved and funded by the Technology Commercialization) and support in terms of mentors experienced in developing products for the market."