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Last winter, Trachette Jackson, a professor in the Department of Mathematics, could hardly bear the suspense. In December 2019, she’d learned that her research was in the running to receive a grant from the National Institutes of Health (NIH). “Waiting two months to find out if the award would be officially funded was agonizing,” she says.

But in February, while working at her office in East Hall, the email Jackson hoped to receive finally arrived: I’m extremely pleased to let you know… She was beyond words. “The type of interdisciplinary research I do can easily fall through the cracks between funding agencies,” Jackson explains. “It was nice to have this type of validation.”

The relationship between mathematics, computation, and cancer may not be immediately apparent, but Jackson has been working to build it for more than 20 years. With her colleagues at the University of Chicago and Michigan Medicine, Jackson creates mathematical models for a treatment approach known as targeted molecular therapeutics, a kind of personalized medical therapy that hones in on the forces that drive the way different kinds of cancer develop in different people.

“Mathematical modeling has been involved in studying every aspect of tumor growth for decades, but now we know so much more about molecular drivers that are specific to cancer cells and different from normal cells,” Jackson says. “We can use those molecular targets as a guide and use modeling to pinpoint, with laser focus, our therapeutic attack.”

It may seem that mathematical research—creating equations, setting their parameters, entering them into computer programs, and analyzing their outcomes in graphs—is a long way from treating patients in a hospital. But Jackson says that, at the heart of it, her work harnesses the power of math and computation to help people.

“Historically, treatment decisions have relied on clinical studies that statistically compare different options among large groups of patients who have similar pathologies, regardless of the uniqueness of disease pathways in individual patients,” says Jackson. “Mathematical modeling is playing a more and more important role in personalizing those decisions."

Last winter, Trachette Jackson, a professor in the Department of Mathematics, could hardly bear the suspense. In December 2019, she’d learned that her research was in the running to receive a grant from the National Institutes of Health (NIH). “Waiting two months to find out if the award would be officially funded was agonizing,” she says.

But in February, while working at her office in East Hall, the email Jackson hoped to receive finally arrived: I’m extremely pleased to let you know… She was beyond words. “The type of interdisciplinary research I do can easily fall through the cracks between funding agencies,” Jackson explains. “It was nice to have this type of validation.”

The relationship between mathematics, computation, and cancer may not be immediately apparent, but Jackson has been working to build it for more than 20 years. With her colleagues at the University of Chicago and Michigan Medicine, Jackson creates mathematical models for a treatment approach known as targeted molecular therapeutics, a kind of personalized medical therapy that hones in on the forces that drive the way different kinds of cancer develop in different people.

“Mathematical modeling has been involved in studying every aspect of tumor growth for decades, but now we know so much more about molecular drivers that are specific to cancer cells and different from normal cells,” Jackson says. “We can use those molecular targets as a guide and use modeling to pinpoint, with laser focus, our therapeutic attack.”

It may seem that mathematical research—creating equations, setting their parameters, entering them into computer programs, and analyzing their outcomes in graphs—is a long way from treating patients in a hospital. But Jackson says that, at the heart of it, her work harnesses the power of math and computation to help people.

“Historically, treatment decisions have relied on clinical studies that statistically compare different options among large groups of patients who have similar pathologies, regardless of the uniqueness of disease pathways in individual patients,” says Jackson. “Mathematical modeling is playing a more and more important role in personalizing those decisions."

 

 

 

 

 

Numbers, Molecules, People

Jackson studied pure mathematics as an undergraduate—“Proving theorems and trying to understand abstract features of mathematical constructs, that kind of thing,” she says—and it wasn’t until late in college, when she attended a lecture on the role of mathematics in predicting cellular patterns in developmental biology, that she first learned of a connection between math and biology.

Now she spends much of her time navigating between these two worlds, translating biological data gathered from real individuals into mathematical equations that she runs as computational simulations to develop models of how tumors grow and respond to therapy. She collaborates with the medical oncologists on her team: hearing their questions and problems and trying to understand what mathematical modeling could do for their particular situation.

It takes a lot of time and effort before Jackson feels comfortable using the models as a predictive tool for medical outcomes, but her approach allows her to tease out intricacies in the biological data that would otherwise be difficult to achieve with experiments alone.

“Experimental technologies are advancing at an accelerated pace, but even still there are so many interconnected pieces working together that it is hard to disentangle the most important ones for any specific situation with an isolated experiment,” she says. “With mathematical models, we can simulate network interactions to try to extract the most important features.

Numbers, Molecules, People

Jackson studied pure mathematics as an undergraduate—“Proving theorems and trying to understand abstract features of mathematical constructs, that kind of thing,” she says—and it wasn’t until late in college, when she attended a lecture on the role of mathematics in predicting cellular patterns in developmental biology, that she first learned of a connection between math and biology.

Now she spends much of her time navigating between these two worlds, translating biological data gathered from real individuals into mathematical equations that she runs as computational simulations to develop models of how tumors grow and respond to therapy. She collaborates with the medical oncologists on her team: hearing their questions and problems and trying to understand what mathematical modeling could do for their particular situation.

It takes a lot of time and effort before Jackson feels comfortable using the models as a predictive tool for medical outcomes, but her approach allows her to tease out intricacies in the biological data that would otherwise be difficult to achieve with experiments alone.

“Experimental technologies are advancing at an accelerated pace, but even still there are so many interconnected pieces working together that it is hard to disentangle the most important ones for any specific situation with an isolated experiment,” she says. “With mathematical models, we can simulate network interactions to try to extract the most important features.

 

 

Modeling Medicine

Most recently, Jackson developed a mathematical model to investigate the optimal time to deliver targeted cancer therapies alongside traditional chemotherapy. The type of targeted therapy Jackson studied had been used to treat arthritis but not cancer, so oncologists were still learning to administer it in a cancer setting. Customarily, researchers begin by giving the targeted therapy and traditional chemotherapy simultaneously. “But in this case,” Jackson explains, “that didn’t really work as well as expected.”

It turns out that co-treatment using traditional dosing schedules—giving both drugs at the same time following a certain schedule—were actually ineffective when targeting this particular cancer stem cell population. “But the mathematical model predicted that, instead, administering repeated cycles of pretreating with the targeted therapy followed by chemotherapy a week later leads to synergistic responses,” explains Jackson. “We were able to pinpoint a dosing strategy that counteracted the antagonism of giving these two drugs at the same time.”

Jackson’s NIH grant, which aims to develop predictive methods for optimizing immunotherapy and targeted molecular therapies, will allow Jackson to continue her efforts in gaining a more robust understanding of the mechanisms that enable different drugs to work well together and improving the ability to combine promising anticancer agents for clinical trials. A long time can pass before the results of Jackson’s work actually reach patients, but she says the work is worth it.

Modeling Medicine

Most recently, Jackson developed a mathematical model to investigate the optimal time to deliver targeted cancer therapies alongside traditional chemotherapy. The type of targeted therapy Jackson studied had been used to treat arthritis but not cancer, so oncologists were still learning to administer it in a cancer setting. Customarily, researchers begin by giving the targeted therapy and traditional chemotherapy simultaneously. “But in this case,” Jackson explains, “that didn’t really work as well as expected.”

It turns out that co-treatment using traditional dosing schedules—giving both drugs at the same time following a certain schedule—were actually ineffective when targeting this particular cancer stem cell population. “But the mathematical model predicted that, instead, administering repeated cycles of pretreating with the targeted therapy followed by chemotherapy a week later leads to synergistic responses,” explains Jackson. “We were able to pinpoint a dosing strategy that counteracted the antagonism of giving these two drugs at the same time.”

Jackson’s NIH grant, which aims to develop predictive methods for optimizing immunotherapy and targeted molecular therapies, will allow Jackson to continue her efforts in gaining a more robust understanding of the mechanisms that enable different drugs to work well together and improving the ability to combine promising anticancer agents for clinical trials. A long time can pass before the results of Jackson’s work actually reach patients, but she says the work is worth it.


From the Fringe to the Center

Zaman went on to get a Ph.D. in computer science and ecology, evolutionary biology and behavior at Michigan State University, and became an LSA Collegiate Fellow in the Center for the Study of Complex Systems in 2017. In 2020, he became assistant professor in the Department of Ecology and Evolutionary Biology (EEB) and in Complex Systems. Now he splits his research time between computational systems and a wet lab that uses live viruses and microbes.

Zaman’s interdisciplinary approach to research is still considered unique in his field. Similar research practices have been around for a while, he says, but they haven’t often been embraced by a core biology group: because they were often more grounded in computational sciences, or perhaps they asked biological questions but lacked the appropriate context, they were relegated to the fringe.

“But now we’re taking what used to be considered artificial intelligence, artificial life, and abstract computational ideas, and putting them into a traditional biological framework to push our understanding of the natural world with systems that we never would have found in nature,” Zaman says.

He stresses the importance of being open-minded and searching for connections between fields to advance a scientific understanding of how the world works.

 

 

 

Mentor Math

LSA Professor Trachette Jackson mentors high school and college students to pursue their math education, rethink how math could fit into their careers, and create spaces where all students feel welcome in the world of math.

Professor Trachette Jackson spends a lot of time inspiring young mathematicians to think about math and all the ways to use it through the Michigan Math and Science Scholars Program, which is designed to introduce high school students to research in the sciences.

“I talk to students about the connections between math and science as early as possible. I really try to stress how now, in today’s society and in today’s educational system, interdisciplinarity and team science is just beginning to flourish,” Jackson says. “Now students don't have to limit themselves to just math or biology. For example, if a student enjoys math but also has aspirations in medicine, they can recognize the value of having a solid set of mathematical tools in their back pocket and see a way to use that quantitative machinery in their medical career. One of the best parts of my job is sparking excitement in others, especially students, about this kind of work.”

In 2011, Jackson created the Marjorie Lee Browne Scholars Program to prepare students interested in getting a doctoral degree in mathematics. “It’s designed to give students two years of protected time to build the foundation they need to explore research options and become comfortable with the mathematics graduate setting so they’re able to smoothly transition to a Ph.D. program,” says Jackson.

The program has admitted nine cohorts of students, and the fall 2020 term will welcome the tenth.

“We strive to do what’s best for the students. We have a high completion rate, and several of our graduates have gone on to pursue doctoral degrees at top universities,” says Jackson. The program focuses on students whose backgrounds and life experiences are not traditionally represented in the discipline of mathematics. “We have been able to impact the lives and trajectories of 34 students so far,” Jackson says.

In her undergraduate and graduate education, Jackson felt nurtured by programs that supported women and underrepresented minorities in math and science, and she wanted to find a way to offer programs with similar goals at the University of Michigan.

 
 
 
Illustrations and animation by Ravi Teja Bandaru

 

 


 


 

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Starting college looks a lot different this year for first-year students like J.J., with many courses and activities meeting online. The LSA Annual Fund provides support for tuition, room, and board, as well as the technology and tools necessary to connect to classes and campus. Your support means LSA students won’t miss a beat.


 

 

 

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Release Date: 10/26/2020
Category: Faculty; Research
Tags: LSA; Mathematics; Natural Sciences; LSA Magazine; Anna Megdell; Ravi Teja Bandaru