MyChemobrain
Spring 2023-Fall 2023
Creating a simple and portable diagnostic tool for chemo brain by measuring executive function.
Clinical Problem Identification
About
Chemobrain or cancer-related cognitive dysfunction affects as many as 79% of cancer survivors who undergo chemotherapy, resulting in executive dysfunction. This executive dysfunction involves impairments in attention, inhibition, and processing speed, leading to changes in reaction time and accuracy. Notably, these changes significantly impact the quality of life, hindering the ability to return to work and increasing the risk of falls.
Despite advancements in cancer diagnosis and treatment, chemobrain has enduring effects in 35% of survivors (equivalent to 4.5 million US cancer survivors) and has even been linked to dementia. Consequently, cognitive changes arising from cancer and its treatment are among the most feared side effects. There is a pressing need for a diagnostic tool that is both sensitive and specific, as well as affordable and widely applicable in clinical settings.
Traditional cognitive testing falls short due to its length, long wait times, and the requirement for professional interpretation. Currently, there are no recommended tests specifically for chemobrain diagnosis, relying solely on patient reports. However, patient reports often lack accuracy as individuals may not disclose all treatment-related side effects, and patient-reported outcomes struggle to differentiate between related but distinct conditions, such as depression and anxiety.
The absence of tests to quantify cognitive function for chemo brain leaves researchers, clinicians, and health systems unaware of its true health impact. Efficient management strategies for chemo brain remain elusive without the ability to measure and diagnose cognitive function accurately. Quantifying chemobrain provides an opportunity for health systems to identify reaction response impairments, enabling the initiation of cognitive therapy, deprescription of psychoactive medications, and fall prevention through physical therapy. From a patient perspective, quantifying chemobrain offers validation and hope, potentially restoring trust in healthcare systems dedicated to meeting their needs.
I worked with Dr. McNeish, an Assistant Professor of Physical Medicine and Rehabilitation and Neurology at the University of Pittsburgh, a Current Pepper Scholar at Pittsburgh Pepper Center with 75% time protected for research, and an adjunct Assistant Professor of Neurology at the University of Vermont. He is a passionate physician scientist aiming to improve the lives of cancer survivors through innovation and science related to brain health.
Initial Design
We started the project with an old device called the ReacStick. It was developed in 2010 and was able to perform two modes of executive function. However, it was outdated and did not meet the current needs of the clinic.
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Short Battery Life
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Manual Data Collection
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Low Visibility of Lights
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Only Works in Horizontal Position
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Unreliable Readings
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Not Portable
During our initial ideation, we split up into two groups: one focused on making an updated and portable version of the current device, and one focused on making an app version of the device.
We believed that by translating the two tests to an app, we would allow for maximum ease of use and portability. I worked on developing the app. I started by working closely with Dr. McNeish to clearly identify components of the device that were most important to include. Then, I used Android Studio to create a mockup version of the app.
App Design
1. The app displays the instructions for the user.
2. The patient's name can be entered to link all the tests to their name for data collection.
3. The user is able to pause at the start screen until the phone is in position. Once the button is clicked, the app starts checking the accelerometer values.
4. Once the app recognizes that the device has started to fall, it will randomly decide to conduct a go trial or no-go trial.
Go Trial: The screen turns green and the patient must catch the device.
No-go Trial: The screen stays blank and the patient must let the device fall.
5. Once the test is complete, the app asks the user to log the results of the test which is collected on the cloud using Google Firebase.
6. The app prompts the user if they would like to run another trial or end the tests. If they select yes, it brings them back to the start screen.
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Device Use
This is how the app and device would be used. We used a selfie stick to hold and drop the phone. The patient is seated with their arm resting on a surface while the clinician conducting the assessment is standing with the device in hand.
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This is an example of a successful go trial. Here, the screen turned green and the patient successfully caught the device.
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This is an example of an unsuccessful no-go trial. Here, the patient caught the device even though the screen was not lit up green.
Further Development
In order to secure additional funding and continue the development of the device, I helped our mentor, Dr. McNeish apply to the PInCh competition through the Clinical Translational Science Institute. We were able to make it to the elevator pitch round but were unable to secure additional funding.
In addition, I presented our work at the UPMC Digital Health Summit where I was able to network with other digital health developers and learn more about how our invention could be brought to a health app standard.
Finally, I participated in a NSF Regional I-Corps program. This program is an immersive, entrepreneurial training program that facilitates the transformation of invention to impact. In just four weeks, I conducted customer discovery with thirty clinicians and mapped out the potential business model of our invention using the Business Model Canvas. This experience was invaluable in determining the future direction of our invention and helping define the customer segments we would be targeting.
