Engineers at the Georgia Institute of Technology and Stanford University have created a small, autonomous device with a stretchable/flexible sensor that can be adhered to the skin to measure the changing size of tumors below. The non-invasive, battery-operated device is sensitive to one-hundredth of a millimeter (10 micrometers) and can beam results to a smartphone app wirelessly in real-time with the press of a button.

In practical terms, the researchers say, their device—dubbed FAST for “Flexible Autonomous Sensor measuring Tumors”—represents a wholly new, fast, inexpensive, hands-free, and accurate way to test the efficacy of cancer drugs. On a grander scale, it could lead to promising new directions in cancer treatment.

Each year researchers test thousands of potential cancer drugs on mice with subcutaneous tumors. Few make it to human patients, and the process for finding new therapies is slow because technologies for measuring tumor regression from drug treatment take weeks to read out a response. The inherent biological variation of tumors, the shortcomings of existing measuring approaches, and the relatively small sample sizes make drug screenings difficult and labor-intensive.

“In some cases, the tumors under observation must be measured by hand with calipers,” says Alex Abramson, first author of the study and a recent post-doc in the lab of Zhenan Bao at the Stanford School of Engineering and now an assistant professor at Georgia Tech. The use of metal pincer-like calipers to measure soft tissues is not ideal, and radiological approaches cannot deliver the sort of continuous data needed for real-time assessment. FAST can detect changes in tumor volume on the minute-timescale, while caliper and bioluminescence measurements often require weeks-long observation periods to read out changes in tumor size.

FAST’s sensor is composed of a flexible and stretchable skin-like polymer that includes an embedded layer of gold circuitry. This sensor is connected to a small electronic backpack designed by former post-docs and co-authors Yasser Khan and Naoji Matsuhisa. The device measures the strain on the membrane—how much it stretches or shrinks—and transmits that data to a smartphone. Using the FAST backpack, potential therapies that are linked to tumor size regression can quickly and confidently be excluded as ineffective or fast-tracked for further study.

The researchers say that the new device offers at least three significant advances. First, it provides continuous monitoring, as the sensor is physically connected to the mouse and remains in place over the entire experimental period. Second, the flexible sensor enshrouds the tumor and is therefore able to measure shape changes that are difficult to discern with other methods. Third, FAST is both autonomous and non-invasive. It is connected to the skin, not unlike a band-aid, battery operated and connected wirelessly. The mouse is free to move unencumbered by the device or wires, and scientists do not need to actively handle the mice following sensor placement. FAST packs are also reusable, cost just $60 or so to assemble and can be attached to the mouse in minutes.

The breakthrough is in FAST’s flexible electronic material. Coated on top of the skin-like polymer is a layer of gold, which, when stretched, develops small cracks that change the electrical conductivity of the material. Stretch the material and number of cracks increases, causing the electronic resistance in the sensor to increase as well. When the material contracts, the cracks come back into contact and conductivity improves.

Both Abramson and co-author Naoji Matsuhisa, an associate professor at the University of Tokyo, characterized how these crack propagation and exponential changes in conductivity can be mathematically equated with changes in dimension and volume.

One hurdle the researchers had to overcome was the concern that the sensor itself might compromise measurements by applying undue pressure to the tumor, effectively squeezing it. To circumvent that risk, they carefully matched the mechanical properties of the flexible material to skin itself to make the sensor as pliant and as supple as real skin.

“It is a deceptively simple design,” Abramson says, “But these inherent advantages should be very interesting to the pharmaceutical and oncological communities. FAST could significantly expedite, automate and lower the cost of the process of screening cancer therapies.”

Story by Andrew Myers

Citation: Abramson et al., Sci. Adv. 8, eabn6550 (2022)  DOI: 10.1126/sciadv.abn6550

Alex Abramson is now Assistant Professor of Chemical and Biomolecular Engineering at The Georgia Institute of Technology; Yasser Khan is Assistant Professor at the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California; Carmel T. Chan is a former Senior Scientific Manager at Stanford University; Alana Mermin-Bunnell is a student at Stanford University; Naoji Matsuhisa is Associate Professor in the Institute of Industrial Science Department of Informatics and Electronics at the University of Tokyo; Robyn Fong is a Life Science Research Professor in the Cardiothoracic Surgery Department at Stanford University; Rohan Shad is a former Postdoctoral Fellow at Stanford University School of Medicine; William Hiesinger is Assistant Professor of Cardiothoracic Surgery at Stanford University; Parag Mallick is Associate Professor of Radiology at Stanford University; Zhenan Bao is the K.K. Lee Professor in Chemical Engineering at Stanford University.

The research was supported in part by an NIH F32 fellowship (Grant 1F32EB029787) and the Stanford Wearable Electronics Initiative (eWEAR).

The eWEAR-TCCI awards for science writing is a project commissioned by the Wearable Electronics Initiative (eWEAR) at Stanford University and made possible by funding through eWEAR industrial affiliates program member Shanda Group and the Tianqiao and Chrissy Chen Institute (TCCI®).

Muneeb Zia is a research engineer in the Integrated 3D Systems Lab led by Professor Muhannad Bakir. His research focuses on developing microfabrication technologies for heterogeneous integration and in vivo biosensing applications. In the following Q&A, Zia briefly discusses his work in the IEN cleanroom and gives advice to current and future users.

How long have you been using the IEN Cleanroom?

I have been using the IEN Cleanroom for about 10 years.

What tools do you use when you are in the cleanroom and what are you doing?

Most of my current work involves the fabrication of high-density flexible electromyography (EMG) electrodes. To do this, I use a variety of tools including, but not limited to:

• Spin coaters
• Heidelberg MLA 150 Maskless Aligner
• Mask Aligner
• Vision RIE
• STS PECVD
• CHA Evaporator
• Unifilm Sputterer
• Plasma Therm ICP
• Dektak 150 Profilometer
• Hitachi S-4700 FE-SEM
• ADT 7100 Dicing Saw

So, if you run into me in the cleanroom, I am probably making some flexible EMG electrodes.

What is/has been your favorite project you have worked on in the IEN cleanroom?

My favorite project has been the fabrication of flexible EMG electrodes. These flexible high-density arrays were initially developed to record single motor unit activity from the tiny muscles controlling breathing and vocal behavior in songbirds. However, since these initial studies, we have further developed our devices’ capabilities and collaborated with a number of labs to create new electrode designs. These new designs can record from several different species and muscle groups, including from humans. The first successful human trial was also carried out by the Pruszynski Lab in Canada earlier this year.

We are now working to share this technology with the greater neuroscience community around the world. We are conducting remote workshops where we provide the electrode arrays developed in the IEN Cleanroom along with online instruction materials to users to collect high-resolution EMG data in their own labs. To date, labs from around the world including labs in Canada, the United Kingdom, Japan, China, Switzerland, Portugal, Denmark, and Finland have participated in the workshop. We plan to have more than 100 labs around the world use the electrodes by the end of the workshop.

What would you say to other people thinking about using a tool in the IEN cleanroom?

Getting trained on a new tool is very streamlined and simple, and there are a lot of training videos available to get you started. The trainers in the IEN Cleanroom are also very accessible and always willing to work with you. So, do not wait!

What is your favorite thing about the IEN Cleanroom?

My favorite thing about the IEN Cleanroom is the extremely supportive and helpful staff.

Aaron Stebner outlined an aggressive plan for artificial intelligence and manufacturing when he applied for a faculty position in 2019. In his cover letter, he promised “to establish the Georgia Institute of Technology as a world leader in additive manufacturing of solid materials (ceramics & metals) R&D, especially in the fusion of data sciences and AI to create new, world-leading technologies.”

Stebner thought it would take 10-15 years of incremental steps and funding to achieve the goal. He was wrong.

Thanks to a new $65 million grant from the U.S. Department of Commerce’s Economic Development Administration, announced by President Joe Biden, Stebner’s plan will begin to become a reality — and include the entire state of Georgia and all of its manufacturing sectors from agriculture to airplanes — two years after arriving on campus.

The largest of the nine projects within the larger Georgia AI Manufacturing (GA-AIM) technology corridor grant will allow Stebner and Georgia Tech to transform the Advanced Manufacturing Pilot Facility (AMPF) into the Artificial Intelligence Manufacturing Pilot Facility (AI-MPF). The 24,000 square-foot facility on 14th Street will more than double in size after Georgia Tech and statewide GA-AIM partners were selected as one of 21 Phase II awardees in the $1 billion Build Back Better Regional Challenge (BBB) competition, part of the Investing in America’s Communities initiative under the American Rescue Plan Act of 2021.

AMPF has been a shell waiting for a vision like Build Back Better to fill it out,” said Stebner, associate professor the George W. Woodruff School of Mechanical Engineering and the School of Materials Science and Engineering. “Now we will transform the facility into one of the nation’s first manufacturing labs designed for autonomy with the goal of helping the state and the nation to be world AI manufacturing leaders.”

Read the entire story on the College of Engineering website. 

Program Description

The Georgia Tech IEN is an Interdisciplinary Research Institute (IRI) comprised of faculty and students interested in using the most advanced facilities for fabrication, characterization, and cleanroom processes, to facilitate research in micro- and nano-scale materials, devices, and systems. Applications of this research span all disciplines in science and engineering with particular emphasis on biomedicine, electronics, optoelectronics and photonics, and energy applications. As there can be a learning curve associated with initial proof-of-concept development and testing using cleanroom tools, this seed grant program was developed to expedite the initiation of new graduate students and new research projects into productive activity. Successful proposals to this program will identify a new, currently-unfunded research idea that requires core facility access to generate preliminary data necessary to pursue other funding avenues.

Program Eligibility

This program is open to any current Georgia Tech or GTRI faculty member as project PI. The graduate student performing the research should be in the first 2 years of their graduate studies, and preference will be given to students who are new users of the IEN facilities. The student’s research advisor (project PI) does not need to be a current user of the IEN cleanroom/lab facilities. Current PI awardees cannot apply in consecutive funding periods. Please make sure that the student will be available to use the facility during the majority of the grant period.

Award Information

Each seed grant award will consist of free core facility access to the student identified in the proposal over a 12-month period (4 consecutive billing quarters) up to a maximum of $6600 in charges. This award amount is based on the current access rates and the academic cap on quarterly charges and equates to two free billing quarters spread over one year in order to provide maximum flexibility in access. This maximum amount is subject to change based on planned access rate adjustments. This maximum award amount is still in effect even if IEN non-cleanroom (lab) equipment, electron beam lithography (EBL), or tools in the Materials Characterization Facility (MCF) are required. Access to facilities other than IEN/MCF are not covered by the seed grant.

In addition, each student will be offered up to $500 in travel support to attend a scientific conference where they will present (oral or poster) the work resulting from this seed grant. This travel can be used during the award period or up to a period of 6 months following.

The number of awards for each proposal submission cycle will depend on the number and quality of the proposals.

Expectations

The seed grant will begin with a group kickoff meeting (mandatory for students) with IEN technical staff and will also include periodic check-in meetings as required. Members of the IEN processing staff will also be available to consult as needed during the project period. The designated student user is expected to only utilize the seed grant for core facility access while working with the PI on the proposed project. A short progress report is submitted at the mid-point of the project, and a longer report describing the research activities and outcomes is required at the completion of the award period. Students may also be requested to present a poster at the annual IEN User Day event.

Submission Schedule

This Seed Grant program is offered in two competitions each year with due dates this academic year on October 1, 2022 and April 1, 2023 for research activity that will begin on December 1, 2022 and June 1, 2023, respectively.

Proposal Requirements (2 pages max)

The proposal (submitted as a PDF file of no more than 2 pages) should do the following:

1. Provide a project title. List name of faculty PI and student at the top of the proposal.

2. Identify the research problem and specify the proposed methods.

3. Indicate the IEN research tools necessary to conduct the research. It is recommended that you obtain assistance with this component from members of the IEN or MCF technical staff.

4. Describe the relationship of this research to the PI’s other research activity and how it is distinct from and not an extension of ongoing work.

5. Identify the PI and the graduate student involved (including year of graduate work), and if there will be a mentoring relationship with the PI’s other students. Note if there are collaborative relationships with Georgia Tech faculty that bear on this research project.

6. Specify the potential for follow-on funding based on the results of this initial work.

Some helpful hints: Proposals should not excessively discuss the motivation and impact of the research. While this is helpful for understanding the importance of the work, please be brief. More important is a detailed description of what you propose to actually do (fabrication and/or characterization) in the core facilities so that this can be assessed for how feasible and realistic it is within the scope of IEN’s capabilities. We understand that this research is being undertaken by a beginning graduate student with limited experience who will likely require staff assistance. In addition, there may be multiple approaches

to the research problem. However, you should clearly describe at least the most promising approach in detail within the page limitations.

Submit the PDF file by the specified due date to Ms. Amy Duke (amy.duke@ien.gatech.edu).

Review Criteria

Proposals will initially be reviewed by IEN staff for technical feasibility within the time frame. Rating of proposals will be done by a review committee of Georgia Tech faculty, with final selection of awardees by IEN staff. Review criteria include novelty of the research, clarity of the proposed work, work that is technically achievable within the time constraints, and likelihood of positive outcomes (future funding).

For more information, please contact Dr. David Gottfried, dsgottfried@gatech.edu, (404) 955-9733.