Stephanie Reisinger, SVP of Real-World Evidence at Flatiron Health, on the VatorNews podcast

Steven Loeb · July 5, 2024 · Short URL:

Flatiron Health focuses on accelerating cancer research and improving patient care

Steven Loeb and Bambi Francisco Roizen talk with Stephanie Reisinger, SVP and General Manager, Real-World Evidence at Flatiron Health, a healthcare technology and services company focused on accelerating cancer research and improving patient care

Some highlights from the call:

0:38 - Reisinger talks about her career: She started as a software engineer before moving into the healthcare space in 2000 when the human genome was first sequenced. Reisinger went to one of the very first genomic companies of the time and got hooked on healthcare data, and what tech could do for healthcare data. Her focus ever since has been working at the intersection of patient data, technology and analytics, mostly focused on the life science or biopharma industry. 

3:32 - Why she joined Flatiron: Flatiron is known as a leader and innovator in the real world data space, and part of the business is having an electronic health record system, which gives them very unique access to patient data for their research. Also, Flatiron focuses on oncology which has impacted her family pretty significantly, so it's personally satisfying for Reisinger to work every day on something that can make a difference. Finally, Flatiron has a really powerful mission, which is learning from the experience of every person with cancer. 

4:59 - How data is being made actionable: When Reisinger started in this space, there were three healthcare insurance claims databases that were commercial and that's the only thing they used for research. In 2010, electronic health records were adopted so now almost every person in the US has electronic health records that can be leveraged for research, genomic data, and even data coming off of personal devices. Every aspect of healthcare delivery in our country is getting digitized and throwing off data, so we have a huge opportunity. The challenge is data is very siloed: each source of data tells a specific story, but that story is only part of the story of the patient's healthcare journey. The challenge in the future is how do we best pull this data together.

13:15 - Defining real-world evidence: Data captured for the purposes of providing healthcare services is called real world care, which is where the term real world data comes from. Flatiron repurposes this data and uses it to understand healthcare in the real world. It's a rapidly evolving field as more and more healthcare gets digitized, more and more data becomes available, and real world data is the exhaust that comes out of providing digital healthcare services. Reisinger's job is to really lead the strategy and team that takes that data exhaust and turns it into valuable data and research and insights.

17:25 - Working with biopharma companies: Flatiron’s primary customers, from a revenue generation perspective, are biopharma companies, because Flatiron is helping them to answer questions and understand their drugs and their patients from the time the drug is first discovered all the way through end of patent life. Flatiron also partners with academic medical centers and, as part of that partnership, it will pull their data out of their EHRs, clean it up, and we provide that data back to those academic medical centers to power their research. The company calls using data for good. 

19:05 - In vitro studies: In vitro studies are really important targeted studies that help you understand specific mechanisms, whereas the large data studies, especially in drug discovery, are more about understanding patterns, and narrowing down the choices of drug targets and populations those targets will go after. For instance, Flatiron has a partnership where it links its clinical data to genomic data, and one of the exciting benefits of that is that it can identify patterns of patients that have the same genetic traits, and it can link outcomes from patients with diseases to the genetic traits that they have. It's hypothesis generating, rather than hypothesis testing, that is really trying to understand sub-populations of patients, that might be more or less likely to be impacted by a drug.

27:50 - The impact of data: Drug discovery today is more sophisticated and harder than it was 20 years ago. It's hard to say why the cost keeps going up, but it's much more sophisticated, difficult, and our cancer drugs are so much more effective and so much better that so much fewer adverse events than they used to be. It's just a much more complicated discovery process than it used to be.

32:52 - AI and machine learning: Flatiron created an initiative called Liberate Our Data, taking the highly curated datasets of 22 different tumor types and then using them to train ML algorithms. So, instead of using nurse abstractors, it’s going after the full data set with its ML algorithms with really good results. The company recently launched the first two tumor types, breast and lung, that are ML generated datasets, almost 10 times bigger than sample data sets. Now it can start leveraging millions and millions of patients and billions of data points that Flatiron has access to, which it couldn't unlock before because the technology just wasn't available. The company is also leveraging ML and AI is for physicians who want to participate in clinical trials: one of the things that Flatiron developed for those physicians is software and technology that looks at the patients that they have in their population, matches them up to clinical trial inclusion and exclusion criteria, and alerts the physicians of patients that they have coming in that may be available for trials that are ongoing.

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