2025 Translational Science Pilot Projects
A Multilevel and Mixed Methods Examination of Pathways to Recovery
PI: Mayra Guerrero, PhD, Assistant Professor, Department of Psychology, UIC College of Liberal Arts and Sciences
Co-Is:
Robin Mermelstein, PhD, Distinguished Professor, Department of Psychology, Co-Director, Center for Clinical and Translational Science, UIC
Yamilé Molina, MS, MPH, PhD, Associate professor, Department of Community Health Sciences, UIC School of Public Health
Project Summary
Recovery from substance use disorders (SUDs) is shaped not just by personal choices, but by the environments and relationships that surround individuals. Too often, individuals face recovery without stable housing, meaningful social support, or nearby services. These gaps increase the risk of relapse and reduce opportunities to regain health and stability.
This project examines how factors like neighborhood conditions, social connections, and access to essential resources—known collectively as Recovery Capital—can support or hinder long-term recovery. By identifying how these challenges play our in real life through methods that analyze personal experiences, this research will uncover practical ways to strengthen recovery pathways.
The community intervention and policy recommendations that result from this project can lead to better recovery outcomes for individuals and stronger, healthier communities.
An in vitro liver cancer modeling platform to accelerate therapeutic discovery
PI: Lobna Elkhadragy, PhD, Research Assistant Professor, Department of Radiology, University of Illinois College of Medicine Chicago
Co-Is:
Ron Gaba, MD, Professor and Section Head, Department of Radiology, University of Illinois College of Medicine Chicago
Grace Guzman, MD, Associate Professor, Department of Pathology, University of Illinois College of Medicine Chicago
Project Summary
Liver cancer, particularly hepatocellular carcinoma (HCC), is one of the most aggressive and deadly forms of cancer. Despite advances in precision medicine, progress for HCC has been limited. Most current treatments take a “one-size-fits-all” approach, failing to reflect the real-life complexity and diversity of liver tumors—leaving many patients without effective options.
This project addresses a critical barrier in the search for better treatments: the lack of research models that accurately represent the genetic makeup of human liver cancer. By developing new, genetically-defined models of HCC, this work will give scientists and clinicians better tools to understand how the disease develops and how to treat it more effectively.
If successful, these more efficient approaches can speed the discovery of new treatments across multiple diseases.
Artificial Intelligence-driven prediction of chronic disease from frontal chest radiographs
PI: Brian Layden, MD, Professor, Department of Medicine, University of Illinois College of Medicine Chicago
Co-I:
Ayis Pyrros, MD, Neuroradiologist, Chair of Radiology Informatics Committee, UI Health
Project Summary
Many people at risk for Type 2 diabetes and heart disease go undiagnosed until the disease is advanced—especially in communities with limited access to routine care. This delay can lead to serious, preventable health complications.
This project uses artificial intelligence (AI) to analyze chest X-rays—images already taken for other reasons—to identify at-risk individuals sooner. The research team will train an AI model to recognize patterns that indicate a high risk for disease, then check its accuracy across different patient groups.
This technology could be used in hospitals and clinics to improve early detection, guide timely treatment, and prevent life-threatening outcomes. Ultimately, it has the potential to make healthcare smarter, more efficient, and more accessible—improving lives while easing the burden on the healthcare system.
Development of PLGA Acyclovir and Ganciclovir Microspheres for Sustained Delivery in the Treatment of Herpetic Uveitis
PI: Tejabhiram Yadavalli, PhD, Assistant Professor, Department of Ophthalmology and Visual Sciences, University of Illinois College of Medicine
Co-I:
Pooja Bhat, MD, Associate Professor, Department of Ophthalmology and Visual Science, University of Illinois College of Medicine Chicago
Project Summary
Eye infections caused by herpes viruses can lead to serious vision problems if not treated effectively. Currently, treatment often requires expensive, specially prepared antiviral medications that aren’t covered by insurance or Medicare. This creates major barriers for older adults and people with limited financial resources.
This project aims to change that by developing a new, affordable treatment that delivers antiviral medication slowly and steadily over time by using tiny, biodegradable particles called microspheres. Made from a safe, FDA-approved material, microspheres can carry drugs like acyclovir and ganciclovir directly into the eye, reducing the need for frequent dosing and lowering overall treatment costs.
If successful, this treatment could provide longer-lasting relief from herpes-induced eye infections, lower the risk of recurrence, and enhance patients’ quality of life by preserving better vision. In addition, its cost-effectiveness may make it eligible for coverage by insurance companies and Medicare, expanding access to care for many Americans.
Toward clinical-feasible mobile brain/body imaging
PI: Chang Liu, PhD, Assistant Professor, Department of Kinesiology and Nutrition, UIC College of Applied Health Sciences
Co-I:
Lucinda Williamson, PhD, Bridge to Faculty Postdoctoral Research Associate, Department of Biomedical Engineering, UIC Colleges of Engineering and Medicine
Project Summary
Mobility loss affects nearly one in three older adults in the U.S., especially those living with neurological conditions. Walking safely depends on how well the brain plans and adjusts movements in real time. This research team developed Mobile Brain-Body Imaging (MOBI), a tool that measures brain activity during walking using wearable sensors and EEG (electroencephalogram) technology, which can help detect early signs of mobility decline before it leads to serious health issues.
However, the current version of MOBI still has limitations. It does not perform well with certain hair types, requires expert technicians and requires significant amounts of time to collect and process data. Pilot funding will be used to design better electrodes using 3D printing, as well as improve signal quality and data processing.
In the long run, more efficient MOBI testing can aid studies on diseases that affect movement. Data processing tools will be made available to the public and added to EEGLAB, a popular research software platform. Ideally, these positive outcomes will promote the widespread use of EEG and its application as a clinical tool for various research purposes.
Tunable bioink for 3D bioprinting of human neural tissue: A platform for translating Alzheimer's disease pathology for potential therapeutics
PI: Mohammad Fazle Alam, PhD, Research Scientist, Bioprinting, Department of Biomedical Sciences, University of Illinois College of Medicine Rockford
Co-Is:
Xuejun Li, PhD, Professor, Department of Biomedical Sciences, University of Illinois College of Medicine Rockford
Gitika Thakur, PhD, Postdoctoral Research Associate, Department of Biomedical Sciences, University of Illinois College of Medicine Rockford
Project Summary
Alzheimer’s disease (AD) affects more than 7 million people in the U.S. and over 47 million worldwide, with numbers expected to rise as the population ages. It causes memory loss, cognitive decline, and dementia, gradually taking away a person’s independence. Despite decades of research, there is still no cure—current treatments only ease symptoms.
This project aims to change that by creating a highly realistic laboratory model of the Alzheimer’s-affected brain using cutting-edge 3D bioprinting technology. By mimicking the structure and behavior of human brain tissue, this model will allow scientists to study how Alzheimer’s develops and test promising new treatments in a more accurate and human-relevant way. A key goal is to design a flexible brain-like material that supports the growth of human neural tissue and reflects the biological changes seen in Alzheimer’s.
If successful, this project will establish a robust ex vivo model of Alzheimer’s disease and a platform for advanced therapeutic care to speed the development of new treatments.