Institute for Data Science in Oncology

One of the biggest challenges I face daily in my job at Meta is how to deal with problems at scale while also making the experience feel personalized for the billions of people using our apps. One of the keys is being tech-forward in thinking about how to reach those goals.   

Having a background in technology has been very useful as a member of MD Anderson’s Board of Visitors and as chair of its Institute for Data Science in Oncology (IDSO) Signature Priority Committee. After all, the power of IDSO lies in taking data from many different sources and analyzing it to find patterns and trends that we can learn from.   

But data doesn’t just mean data about medical imaging or treatment outcomes, although, of course, that is important. If you think about all of the components that go into a person’s experience at MD Anderson, you start to think about other data, such as how quickly a patient got that first phone call back, or how they felt about their interactions with their care team. And if you think about individualized treatment, you start thinking about genomic data and data about a person’s clinical history. 

Making sense of all the data

When we train artificial intelligence (AI) to sort through the tremendous amount of data that MD Anderson generates, we can learn from it in ways that will benefit cancer patients and their families at every part of their journey.   

IDSO launched two years ago. And I believe it holds the key to unlocking advancement in many areas as MD Anderson works to end cancer.   

Making an inherently uncomfortable process more comfortable 

Receiving a cancer diagnosis is super intimidating. So is being at a large hospital system. I know this firsthand. My late husband, Philip Guentert, was diagnosed with stage IV kidney cancer in 2012.  

Phil was a lawyer and a powerful courtroom litigator. He was a very eloquent speaker. But when it came to cancer, he was often speechless. Sometimes, he’d just sit and wring his hands during appointments, absorbing what he was hearing but not asking the questions I knew he had. He often couldn’t participate meaningfully in conversations with his care team because he was so overwhelmed.  

How do you make people feel comfortable while navigating an inherently uncomfortable process? This becomes even more difficult when a patient is facing the process without close friends or family, or when a patient is young or dealing with a language barrier or other challenges. And, how do you incorporate technology in such a way that the patient feels empowered to help themselves on the easy stuff but still has somewhere to turn when it’s not easy?   

This is the constant challenge all hospitals face. The standard experience is not as personalized as anyone would like it to be.

MD Anderson is using data and technology to figure out how to better manage these challenges. For instance, we’re using technology to reduce wait times and make appointments more convenient, something that really matters to the patient experience. We’re also using AI to analyze the surgical process to identify which parts are taking too long and improve efficiency, so patients don’t have to be under anesthesia for as much time.

Making research more approachable 

As IDSO signature priority committee chair, part of my job involves educating people about what IDSO actually is to make it more attractive to a broader community of donors. If we’re able to showcase some of the work being done here through IDSO and make it approachable, then even people who don’t know anything about MD Anderson, AI or data science will become interested — and be willing to play a role, even if just a small one — in funding these initiatives.   

Those supporters, in turn, will become ambassadors for both IDSO and MD Anderson, which will lead to more funding to support more projects down the line. If we do this right, it will become a self-perpetuating cycle.  

For instance, right now, IDSO is working on two very exciting initiatives where donors can get involved at whatever level is comfortable for them. First, we’re using AI to make anesthesia safer. Specifically, MD Anderson is using it to analyze 19 different variables to see if we can predict which patients will develop a condition called intraoperative hypotension. This is a dangerous yet mysterious drop in blood pressure that occurs in almost two-thirds of all surgical procedures involving general anesthesia. It can create all sorts of problems for patients, but because the cause of the condition itself is still unknown, it’s almost impossible to prevent. If MD Anderson’s anesthesiologists can find a way to detect the storm building, then perhaps they can stop the tornado from striking at all. That would offer a clear benefit to patients.  

The second project is looking at ways to measure overall tumor volume, rather than just the tumor’s size, and using that data to determine if a cancer is active or inactive. MD Anderson clinicians could steer a patient’s treatment in a totally different direction much earlier with this information, coupled with insights provided by a digital twin – that is, a digital model that uses individual patient’s data from clinic assessments, genetic results, and imaging and lab tests to simulate how a tumor may respond to various combinations of chemotherapy, radiation and immunotherapies in a virtual environment. This has the potential to save both time and lives. 

Making the most of the data we have

AI and big data are here to stay. They’re in the news almost every day, and people everywhere are eager to understand what a future involving these tools will look like. Showing people what’s only possible here at MD Anderson — in a way that’s relevant to everybody — is a real opportunity.   

I look at IDSO as a very exciting part of MD Anderson’s mission to end cancer. This is our future. And IDSO is paving the way for us to get there. 

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