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Machine Learning to Understand and Prevent Disease

HomeAll Posts...Machine Learning to Understand and Prevent Disease
06 10
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Barbara Engelhardt (she/her), PhD, is building machine-learning models and statistical tools to make use of that data and find ways to better understand, and even prevent, disease.

“Since I first learned about Gladstone during my postdoc, it’s always seemed like an oasis of amazing science,” says Engelhardt.

Engelhardt’s team will propose new approaches, the collaborators will try them and report back, and they’ll continue to work together to find the method that can generate the best results.

Engelhardt also studies how traumatic events that occur in your life are stored in your cells, how they may affect your genome, and how this can eventually lead to disease.

Engelhardt is using all the data available about these families to understand how traumatic events get stored in their cells, in order to find a way to erase the records and prevent disease outcomes.

“Given those three things—the state, action, and reward—our goal is essentially to design a protocol that will lead to the best rewards,” Engelhardt says.

“So by building a model that can analyze all that data, we want to predict a set of actions for a patient’s given state that will lead to the best outcome for their health.”

Engelhardt’s group is currently collaborating with two large hospitals that have provided anonymized electronic health care record data from nearly 400,000 patients.

“Half of these patients are Black, so we’re specifically building models to understand the differences in how doctors treat Black and White patients and how this may lead to different outcomes,” says Engelhardt.

“I think we can learn overall lessons from this data too, particularly about how the hospital system can best tackle an emerging disease like COVID-19,” she says.

Although Engelhardt grew up in New York City, moving to San Francisco to run her Gladstone lab feels almost like returning home, she says.

Engelhardt is also looking forward to building new collaborations at Gladstone, not only with investigators, but with nearby universities and hospitals as well.

“There are amazing wet labs here doing the most cutting-edge development of methods and technologies, a direct connection with hospitals and access to patient data, and really exciting applications to disease—all of that is the dream,” she says.

“I see Gladstone as a place that can catalyze the impact of the more theoretical work from my group, so that my research can actually help real patients,” says Engelhardt.

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