Lessons from Translational Research with Dr. Timothy Koh
Part of the "Making Science Matter" series
Introduction
Turning lab discoveries into treatments that improve patients’ lives is not easy. UIC professor Timothy Koh’s 2021 Center for Clinical and Translational Science pilot project tackled chronic diabetic foot ulcers—wounds that can lead to amputation or death. His work has revealed important lessons about sustainable collaborations and designing research that reflects the complexities of the real world.
Lesson #1: Bench research must be clinically relevant
Basic wound-healing studies are often criticized for lacking clinical impact. By engaging with clinicians and patients, researchers gain insights can increase the real-world relevance of their hypotheses. Observing conditions in the clinic rather than in mouse models often changes the questions being asked.
“One of my first grants failed; they said I would benefit from having a clinical collaborator,” said Koh. “Having this clinical connection helps focus on research that might impact what happens in the clinic. It motivates you to have the end goal of intervention.”
For Koh, this clinical partnership shaped future research directions. He began examining how obesity affects healing after noting that his collaborator primarily treated patients with Type 2 Diabetes, a common comorbidity.
Takeaway:
Seek clinical partners and spend time in their environment. Doing so grounds research in patient needs, sharpens questions, and increases the likelihood of meaningful translation.
Lesson #2: Identifying and sustaining collaborations with clinicians requires tenacity
While identifying a clinical collaborator is pivotal to forming impactful hypotheses, sustaining these partnerships is challenging. Clinicians juggle patient care, teaching, and speaking engagements, leaving limited time for research.
“Clinicians are often making time to collaborate in their spare time, which is understandable. But it can be difficult to grab their attention and keep it focused on the project long-term,” said Koh.
Institutional support can help by protecting clinician time for research and facilitating bench-to-clinic connections.
Geography also adds barriers: retrieving samples and maintaining communication is harder at a distance.
“It makes a difference when a lab staff member can drop in and chat with the other team as opposed to persistent calls and emails,” Koh noted.
Takeaway:
Bridge cultural and logistical gaps early. Dedicated time, consistent communication, and embedding researchers in clinical spaces strengthen collaborations and enable translational progress.
Lesson #3: Mice live in labs, but patients live in the real world
Bench models often fail to capture the realities patients face. Comorbidities such as type 2 diabetes, obesity, and stress radically alter wound healing but are rarely reflected in lab studies. Biological mechanisms also interact with social determinants like access to care and socioeconomic status, further complicating outcomes.
“In the lab, we’re focused on isolating and manipulating one thing to see how it affects the healing process,” said Koh. “When I went to the clinic, my first big takeaway was you’re not looking at a wound that doesn’t heal in a healthy person. You’re looking at a wound that doesn’t heal in a very unhealthy person.”
This perspective led Koh to examine what is truly conserved between mouse and human systems. In the case of inflammatory responses, there are common aspects but also things that appear to be species-specific. To make his work more effective, Koh chooses to focus on those commonalities.
Takeaway:
Translational science demands models that mirror real-world patient complexity. By prioritizing the factors most relevant to human populations, basic researchers can generate findings with more clinical value.
Lesson #4: Leverage technology to address complexity
Traditional methods often oversimplify biological processes and overlook cellular heterogeneity, limiting insight into why patients respond differently to treatments.
“Machine learning and AI are moving us toward an era of methods where you can better account for as many factors as you can,” said Koh.
Emerging tools such as single-cell technologies and bioinformatics enable researchers to capture this complexity, making findings more individualized and clinically relevant.
“I think it’s exciting that we are getting to the point where we can generate the data to develop models that account for all these things and predict how they work together to influence the healing response,” Koh explained.
Takeaway:
Translational science requires embracing—not avoiding—the complexity of biology and society. By applying advanced technologies, researchers can build predictive models that sharpen precision and move interventions closer to individualized patient care.