Health | NYU Tandon School of Engineering


We make health care better, from check-up to check-out

Cancer on a chip technology

We create dynamic new materials


Professor of Chemical and Biomolecular Engineering Jin Montclare explores engineered proteins and other macromolecules for a range of health and environmental applications, from targeting human disorders and drug delivery, to tissue regeneration, and fabrication of nanomaterials for electronics. Her research has, for example, led to new ways of removing pesticides from crops, ferrying chemotherapeutic agents to cancer cells in synthesized macromolecules.

Recently Montclare and researchers at the Montclare Lab are finding new ways to manipulate hydrogels, 3D materials comprising stimuli-sensitive polymers perhaps best known for their ability to retain large amounts of fluid. With a focus on engineering even more versatility into hydrogels by making them “smart,” she and her students have found ways to control how and when they assemble and disassemble by altering such factors as temperature and pH. She also discovered how transition metal cations (positively charged ions) could confer static and dynamic mechanical strength on hydrogels, enabling them to carry a molecular payload and “know” when to release it.

Last year Montclare, along with Professor of Biomedical Engineering Daniel K. Sodickson, also a professor of radiology, and neuroscience and physiology at NYU Langone Health, were named Fellows of the prestigious National Academy of Inventors (NAI).

We build algorithms, responsible medical AI, and groundbreaking sensors

Data Science, AI, Robotics, Health

When a health issue arises, quick, accurate diagnoses are the best way to stave off bad effects down the line. Now, new technology is making that even easier.

Consider the use of algorithms and AI-powered medical technologies. Technology like smart insulin pumps can provide physicians with exact feedback for how often a diabetic patient needs insulin, and can adjust dosages on the fly to reflect their own individual needs. This kind of information, available to both doctors and patients, has been referred to as Bring Your Own Algorithm medicine — a way to help put power in patients’ hands. However, this technology may complicate patient-doctor relationships, as physicians may not understand the inner workings of the algorithm (and distrust their recommendations because of it) and patients may not understand why their doctor may suggest something other than what an algorithm suggests.

In a recent paper, a number of researchers, including Professor of Technology Management and Innovation Oded Nov, Institute Professor Maurizio Porfiri, and Assistant Professor of Biomedical Engineering John-Ross Rizzo, explored how the increased availability of algorithms makes this potential disconnect worse, and how to alleviate concerns. One way to tackle this issue involves the use of explainable systems, focusing on both user types (patients and clinicians). Much of the research on explainability and interpretability of black-box systems has included visualization of neural networks, analyzing machine learning systems, and training easily interpretable systems to approximate black-box systems. The intended audiences for these approaches are often computer scientists. More work is needed on how explanations should be provided to clinicians (users who do not understand the technology but are experts in the application domain) and patients (users lacking knowledge of technology and application domain). The researchers are exploring how proper scientific communication — not just blackbox calculations — can lead to better outcomes for patients and keep the doctor-patient relationship harmonious.

But while monitoring something like insulin levels is relatively straightforward, measuring something like dopamine levels is inexact. Dopamine molecule activity in the brain is associated with important functions such as motivation, motor control, reinforcement, and reward. Researchers and clinicians commonly monitor neurotransmitter activity in the brain through electrochemical microsensors made of carbon. However, due to their limited sensitivity, existing microsensors can detect only large changes in dopamine levels. They can also record from only one site in the brain at a time.

A team led by Associate Professor of Electrical and Computer Engineering Davood Shahrjerdi has found a new way of enhancing the performance of electrochemical micro-sensors. This discovery could lead to the detection of biomolecules, such as dopamine, at lower concentrations than is possible today.

Nano-graphitic carbon sensors
Nano-graphitic carbon sensors

To support the multi-site mapping of dopamine activities in the brain, the NYU Tandon research team recently developed planar micro-sensors using a carbon nanomaterial, called nano-graphitic carbon. The sensors are incredibly small — comparable to a neuron’s cell body — and the sensor performance can be adjusted by engineering the material structure of the nano-graphitic carbon.

Their research also found surprising evidence that the amplitude of the sensor output in response to dopamine molecules was increased by reducing the operation voltage. The investigators demonstrated sensors with record performance by combining the new voltage-dependent phenomenon with their approach of engineering the material structure. They’re now looking at monitoring other brain chemicals with similar sensors, mapping out much more of the brain’s functions than were previously possible.

We make treatments more targeted


Treating cancer means learning about cancer — how tumors begin, how they grow, and how they spread. For Associate Professor of Biomedical Engineering and Mechanical & Aerospace Engineering Weiqiang Chen, studying such a big problem requires starting small — the size of a chip. Chen, also a faculty member of the NYU Langone Laura and Isaac Perlmutter Cancer Center, has helped develop a method to study certain kinds of cancer in an engineered environment — a “cancer-on-a-chip” that can provide an easy way to study how aggressive cancers act under the normal conditions of the humans body, and provide a window to how cancers might be treated in the future.

The cancer-on-a-chip technology can mimic the specific tissue environment of a patient who is affected by a type of cancer, using the cancer cells from their own body. Then specific treatments can be tested on the chip, to ensure that they might be helpful in the body writ large. This removes some of the risk of treatment — making sure that the therapy will do more good than harm in a specific patient. They can also study the specific immune response that the body is likely to initiate, giving more data that a physician can use to suggest a treatment regimen. Chen is utilizing these artificial environments to study leukemia and glioblastoma, but other cancer treatments may be developed thanks to this technology.

But new treatments aren’t being found just in chips. A holy grail for orthopedic research is a method for not only creating artificial bone tissue that precisely matches the real thing, but does so in such microscopic detail that it includes tiny structures potentially important for stem cell differentiation, which is key to bone regeneration. Now, an NYU Team led by Professor of Chemical and Biomolecular Engineering Elisa Riedo demonstrated that it is possible to produce bone replicas on a scale meaningful for biomedical studies and applications, at an affordable cost.

These bone replicas support the growth of bone cells derived from a patient’s own stem cells, creating the possibility of pioneering new stem cell applications with broad research and therapeutic potential. This technology could revolutionize drug discovery and result in the development of better orthopedic implants and devices. The system they developed allows them to sculpt, in a biocompatible material, the exact structure of the bone tissue, with features smaller than the size of a single protein — a billion times smaller than a meter. This platform, called bio-thermal scanning probe lithography (bio-tSPL), takes a “photograph” of the bone tissue, and then uses the photograph to produce a bona-fide replica of it. Its time- and cost-effectiveness, as well as the cell compatibility and reusability of the bone replicas, make bio-tSPL an affordable platform for the production of surfaces that perfectly reproduce any biological tissue with unprecedented precision.

We make rehabilitation more accessible

Health, Wireless, AI, Data, Robotics

Stroke, the leading cause of motor disabilities, is putting tremendous pressure on healthcare infrastructures because of an imbalance between an aging society and available neurorehabilitation resources. Thus, there has been a surge in the production of novel rehabilitative technologies for accelerating recovery. Despite the successful development of such devices, lack of objective standards besides clinical investigations using subjective measures have led to controversial recommendations regarding several devices, including robots. The topic of robotic neurorehabilitation has attracted a great deal of interest because it can significantly reduce the load on healthcare systems and accelerate the rehabilitation process.

Telerobotic rehabilitation is the next natural extension of the current technology, causing even more of a buzz since patients can receive an immersive, personalized experience regardless of their geographical and accessibility limitations, and possibly at their homes. While the technology has not been used on a large scale yet, the COVID-19 crisis brought the need for telehealth services of all types into sharp focus.

da Vinci Surgical Robotic System

Now, Assistant Professor of Electrical & Computer Engineering and Mechanical & Aerospace Engineering S. Farokh Atashzar is deeply involved in solving this pressing and timely problem. Atashzar points out that telerobotic rehabilitation was not possible in the past, in part, because of concerns about the reliability and resiliency of the network and security of data transfers. Latency, jitter, and packet loss can not only deteriorate the fidelity of information rendering. Atashzar has proposed novel passivity-based and small-gain-based stabilizers to address the stability issue while maximizing the performance and transparency of force-motion coupling between remote therapists and their patients. The results could be robots fully capable of the complex medical procedures that are required for proper rehabilitation. Atashzar’s work relies on a number of advances, from robotics to wireless communications to groundbreaking new health technologies.

Tandon researchers are already taking advantage of these advances. Professor of Mechanical and Aerospace Engineering Vikram Kapila is creating robotic dialysis machines that can be operated by doctors remotely. The impetus for the work was the COVID-19 crisis, where dialysis patients had to share hospital space with people infected or exposed to the virus at all times. Rather than directly expose dialysis patients to infectious diseases, this technology allows medical personnel to perform the life-saving measure from outside the patients’ rooms, creating safer, healthier hospital conditions.

We make fresher air


AirOn was created by five friends who met at NYU’s Tandon School of Engineering. Alim Williams, Diallo Sambury, Kadeem Joseph, Ramon Parchment, and Shane Garraway came together to find a solution to create face masks that can protect against harmful bacteria in the air. The company’s AirFusion Mask is a breathable filtered mask that can be adjusted for comfort. It uses smart technology to allow the user to breathe fresh air and includes an N95 filter and a rechargeable turbine system that moves exhausted air from the nose and mouth