Inspired by Star Trek: A Technology-Driven Approach to Personalized Medicine

The following article was part of a Star-Ledger and NJ.com op-ed series on engineering fields that will change the world by Rutgers School of Engineering faculty.

By Umer Hassan

Real world innovations–from submarines to self-driving cars–come straight from imaginary worlds of science fiction. Think Star Trek’s handheld tricorder, a medical diagnostic device that made its first appearance in the original TV series. This sci-fi precursor is now changing the face of personalized medicine by taking the tricorder concept to the next level.

Today, diabetics can anticipate a biosensor able to monitor their glucose levels through perspiration. An electrical graphene biosensor implant could detect genetic mutations as they happen, while UK researchers are developing a wearable biosensor that will collect data and assess the efficacy of rehab equipment and exercise.

Other biosensors will be able to quickly and inexpensively detect costly and potentially fatal medical conditions such as sepsis and AIDS. Together with Rutgers University colleagues, clinical and industry partners, my lab has been working to solve these global health challenges with new tools that focus on a highly personalized approach to medicine. Since the COVID-19 pandemic began, we are also hoping to apply this technology to fight against the coronavirus.

Sepsis–the body’s life-threatening response to infection–is not only deadly, it is the most expensive inpatient medical condition in the United States, with patients who develop sepsis often spending days in intensive care units at a cost of $10,000 a day–or more. Recognizing that sepsis is responsible for as many as six million largely preventable deaths a year, the World Health Organization has identified the prevention, diagnosis, and management of sepsis as a pressing global health priority.

By applying electrical and computer engineering skills to identify new biomarkers and devise machine-learning algorithms, or artificial intelligence systems, we hope to dramatically improve clinicians’ abilities to diagnose, predict–and ultimately manage–sepsis. Simply reacting to diseases is no longer enough–we need to predict them in order to treat patients in a much smarter way.

To this end, we are building an inexpensive medical device that even minimally trained health care providers can use to accurately diagnosis sepsis. This automated device would cost less than $10 a test and be simple to operate not only in resource-limited settings, but anywhere where a rapidly confirmed diagnosis of sepsis is needed.

In sub-Saharan Africa, where only one person in eight is even tested for HIV, many people infected with HIV go undetected until they develop severe complications from the disease. Those who are tested should be tested much earlier to receive access to therapeutics for their personalized care.

A related area of development includes cheap, disposable biosensors that will be as easy and convenient to use as a home pregnancy strip test to detect infections with people living with HIV/AIDS in underdeveloped sub-Saharan African nations. A secondary goal is to develop sensors able to monitor a patient’s response to the antiretroviral therapy they receive.

The positive health and economic impact of such sensors would be felt not only in underdeveloped nations, but also in the United States by reducing the cost of a single HIV test from hundreds of dollars to as little as $10.

My lab has also made the fight against COVID-19 an urgent research priority and a natural extension of our existing work. We are seeking to develop a sensor that could measure the ability of white blood cells to kill the virus in high-risk human patients. This could lead to new therapeutic interventions, and could help develop a rapid, easy-to-use widespread stratification test.

In terms of predicting health outcomes and personalizing therapeutic approaches economically, we are also collaborating with Robert Wood Johnson Medical Hospital to do just that by combining sensor data and electronic medical records data.

Advancing personalized medicine and health monitoring is also a key concern of my Rutgers School of Engineering colleague, electrical and computer engineering associate professor Mehdi Javanmard. His lab has been developing a “lab on a chip” with the potential to monitor everything from health to germs to pollutants.

His team’s innovative biosensor could be used in hand-held devices–akin to that old Star Trek tricorder–or wearable devices that measure biomarkers to track your health and exposure to harmful bacteria, viruses, and pollutants.

While a single biomarker is measured in home pregnancy tests, multiple biomarkers need to be tracked simultaneously to diagnose and manage complex health conditions such as heart disease, cancer, and inflammatory diseases. The lab on a chip is designed to meet that challenge. Additionally, within the next three to five years, a lab on a chip could quickly analyze a sample of what–if any–harmful bacteria are on a doorknob of a bathroom; test a salad for the presence of E. coli or Salmonella bacteria; or even quickly test for the flu.

In time, a future version of the smartphone will be the true tricorder of tomorrow. Smartphone based health sensors will ultimately transform the smartphone into an intelligent, all-in-one monitoring and diagnostic device.

Umer Hassan, an assistant professor of electrical and computer engineering at Rutgers University School of Engineering, holds a joint appointment at Rutgers Global Health Institute.