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Big Data, Digital Health, and the Future of Medicine: A Conversation with Charles Wolfus

A smartphone with a caduceus rising out of it; digital health concept

“We are on the cusp of a renaissance, where therapies will be more effective, and disease will be a smaller, more manageable part of our lives.”

Charles Wolfus’ career trajectory has brought him to the cutting edge of medicine, at the intersection of technology and health.

With digital health, AI, medical devices, and biotechnology, young, hungry companies are making enormous strides as they bring medicine into the 21st century, and they’re dragging established medical/pharmaceutical companies with them.

From Law to IT to Biotech

While pursuing a career in law, Charles found himself working in IT to pay the bills. Turns out he had quite an aptitude for computers, and technology, and science, and....data.

He stuck with the technology track, and moved to San Francisco with a growing company. However, when they wanted to transfer him to Florida, he jumped to another company, a biotech company. He had developed an interest in science early on, and was surrounded by friends in scientific fields. With his lifelong interest in science he was a perfect fit, and his transition into the life sciences began.

“I've spent almost 20 years working to bring technical capabilities to the drug discovery and drug development process.”

In 2000, Charles joined a pharmaceutical company as IT manager. He's curious, and always learning, so he started absorbing everything he could about their science, drug discovery, and drug development. Because of that his role expanded rapidly, moving beyond traditional IT to include research informatics.

“I learned more about how science is done, what we do and don't understand about diseases, and how we create therapies to improve the experiences and outcomes of people suffering with those diseases.”

Charles spent the last 20 years expanding his knowledge in biotechnology, and what's changed over the course of that time is the technology. With the rise of the internet, the massive growth of data, the improvement in computer technology and the ability to analyze that data, and the more recent application of machine learning / AI to these data sets, drug development has become a very different world.

“I've spent almost 20 years working to bring technical capabilities to the drug discovery and drug development process.”

“Our understanding of disease is accelerating because we are better able to measure what is happening.”

Digital Health

For Charles, digital health started when he was at Onyx Pharmaceuticals in 2014. He co-authored an article on the use of Google Glass in medicine, bringing together cutting-edge technology and oncology. He says, “It was early days, and while Google Glass wasn’t the answer it was clear to me that this, and tools like it, were the future of health.”

At his next company, MyoKardia, he pitched management on building a digital health team and investing in digital health wearable technologies as part of the drug development process. It was a unique opportunity to learn more about patients by using consumer wearables in interventional clinical trials.

“People would ask me, ‘Why, as a leader in wearables, are you not applying your skills at a tech company?’ What people don't realize is that biotech and pharmaceutical companies have a built-in advantage for making these tools useful. The core of their business is focused on successfully running clinical trials where they get deep access to high quality medical data collected regularly using gold standard medical assessments. Linked to wearables, it's a unique opportunity to evaluate the quality of digital health data. Meanwhile, digital health brings something that has never existed before in the practice of medicine--continuous or longitudinal monitoring of people in their everyday lives. So this is the opportunity to work with high quality data for the benefit of patients”

And the opportunities go beyond clinical development of new therapies. Most of us see our doctor once a year, for an annual checkup where they measure your weight and blood pressure and maybe take some other measurements. They do this to assess your health and make important decisions about your care. But, as Charles points out, these are highly fluctuating measurements. Blood pressure varies not just from day-to-day or hour-to-hour, but minute-to-minute. And yet your doctor is measuring it just once a year as the basis for health care decisions.

“With digital health tools we can measure heart rate and related measures dozens of times a minute without being wired to a monitor. At MyoKardia we did this to measure patient blood flow continuously for five minutes to compare with medical measures. What if we could do this in people's everyday lives? It's something medicine isn’t doing right now.”

This kind of monitoring, and the knowledge it will bring, will have a fundamental impact on how we think about disease and what is happening with our bodies.

People don't really appreciate how little we understand about health and the human body. We assume that our doctors know our bodies and what disease we may have, but they really know very little. With digital health, continuous monitoring is leading us to better understand disease.

Charles shares an example from the last company he worked at: Recently MyoKardia published an article (co-authored by Charles) on a digital health study conducted as part of a hereditary heart disease clinical trial. The study determined that continuous monitoring using a wrist-worn photoplethysmography (PPG) digital health device from a commercially available fitness tracker could identify the disease with very high accuracy. In the future, we could be using these devices to identify this disease before people have a significant, life-threatening cardiac event. This is game-changing in a situation where it is believed that 85% of people with the disease are undiagnosed.

The Tech Perspective

Being technology-focused, Charles tends to have a different perspective than many he works with. Interestingly, he points out that one of the things he does is to fight the view of new tech as "cool". He says, "It is cool, and I can see why people feel that way, but that's not what's important. Putting ourselves in a position where there is as much high-quality data as possible, and then understanding how that data can be used, is what matters."

IT leaders are uniquely positioned to help biotech companies achieve the full benefit of digital health technologies because they have to understand all the different parts of the business. A Chief Medical Officer understands the breadth of the organization, but is very focused on developing that drug. The Chief Commercial Officer is really cares about making sure that drug is discovered and developed, but is primarily focused on making sure they understand the market and how to get that drug to the patient. A Chief Scientific Officer is much earlier in that process and so is focused on making sure they can move the science forward and that they are introducing the newest ideas. IT leaders work with all of them, understanding each one’s focus and needs, and how it fits into the broader mission. That creates a unique opportunity, when talking about portability and reuse of data, for IT to say, hey, we don't just want to do something "cool". We want to put our data to work in a number of different ways. We want to gather data now to identify endpoints that will support our clinical trial and the approval of our therapy. But we also want to leverage that data to go even further; perhaps to identify patients that are under-diagnosed, or to identify when drug therapies need to be increased or reduced, or to know when people aren't taking their drugs at all.

“We can be the ones who refocus the big data conversation onto what matters, and remind everyone of the many possibilities that all this data offers,” says Charles.

“I believe we are on the cusp of a renaissance, where therapies will be more effective, and disease will be a smaller, more manageable part of our lives.”

The Renaissance, the Future

"I've been around long enough to see disease outcomes dramatically improve thanks to good medical science. HIV is one example, where the disease has gone from a terrifying killer to a manageable, chronic disease."

He was at Onyx Pharmaceuticals when Kyprolis was approved for treating multiple myeloma, a blood cancer. It had previously been a death sentence to be diagnosed with multiple myeloma, but with the approval of that drug, and weeks later a similar drug from another company, it went from death sentence to chronic disease. This means people get to meet their grandkids, and watch their sons and daughters get married and start families.

“Putting ourselves in a position where there is as much high-quality data as possible, and then understanding how that data can be used, that's what matters."

"This progress with treatments for diseases is being amplified, as we speak, by digital health and the data it allows us to analyze."

There are now mobile apps out there, approved by the FDA, to help treat diseases. "Diabetes is an example. It's a disease that is growing and spreading, but now there are approved mobile apps that make it easier for patients to manage their insulin levels and dosing, as well as their nutritional intake and exercise."

There are smoking cessation apps, and apps in development to support people with depression.

"Every business is a data business now. Information is what has the value."

It took this big data revolution and tech companies to realize tjat if we collect enough data then we can use machine learning and AI to find correlations that are meaningful.

Could we detect that someone's blood pressure is going up without physically monitoring them? Could we detect that someone is depressed just by the way they interact with their social media? Yes, and that could be used to help them.

Charles points out that we are just at the beginning of this data "gold rush", and that there are many opportunities to develop new business models for data analysis.

Sub-studies
One of the things that is already starting to happen, and Charles expects will just get more commonplace, is adding digital health sub-studies to clinical trials. The methods and means for collecting data are becoming less and less expensive, so, for example, putting a wearable on a patient, or some other digital monitoring device, costs less than traditional measures, like an MRI. The cost is low, and benefit is high, including benefits that can't be identified at the start, so there is a lot of incentive.

Of course, it’s a challenge to ensure you are measuring the right things and that you can reuse the data you capture, but when you do get the right data it's providing the ability to make better decisions for patients, caregivers, care partners, and for the companies that are developing the therapies.

Data Scientists
The need for data scientists is only going to increase. It's been a hot job for a few years, and now the medical device and biotech companies are getting in line behind all the other industries that need data analysis, like tech companies, the banks, the energy sector, retail, telecom, and VCs, to name just a few. There are a lot of boutique data analysis companies popping up with a narrow focus on biotech because of this. But to be good at this you have to have an understanding of what the data is. You can't just take, say, a Wall Street data scientist and toss them into a biotech company and tell them to run some machine learning algorithm against some data source you found and expect to get really good results. “It is the tight collaboration between disease experts and data analysts that yields the best insights.”

After Wearables
Wearables are a way to collect more data. It is their low cost, ease of use, and ability to constantly measure us that makes them so powerful. So Charles posits that the next way to gather more data will be via something that isn't actually on you. Camera data, for example, is becoming increasingly valuable. He points to some sleep studies where they used cameras instead of wearables. Of course, it's not just a camera: "You can train a machine learning algorithm to get good enough at detecting when someone is awake by their movements and what the movements look like. I think there are going to be more opportunities for this kind of data tool in medical practice."

Getting Social
Charles also sees social media as another potential source of usable data, not just for advertising, but also for digital health applications like gaining disease awareness and deepening that understanding.

He says, "Wearables are gathering data for us right now, but at the end of the day we are basically just dropping data all over the place, so I think that the future ultimately involves moving to where the data is."

The Magic is in the Data

The magic here is in gathering more data that is high-quality. Wearables are doing that, and in a way that allows us to correlate it with other data sources that we already understand. This really speaks to the data managers out there, who work hard to ensure that data is clean, high-quality, and usable, and then hand it to those who understand the data and what is meaningful and what isn't.

“We can be the ones who refocus the big data conversation to what matters most, and remind everyone of the many possibilities that all this data offers."

Machine learning and AI in this context are super important tools that allow us to do things we couldn't do before, but they are just tools, they aren't magic. In biotech, these technologies are creating more work, where more people can be part of helping humanity.

 
An innovative thinker and leader on the future of clinical research, medicine, and digital health, Charles Wolfus currently serves as VP of Technology and Digital Health at Alector.

Find him on LinkedIn and Twitter.

   
 

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