said Dr. Bob Zambon, Vice President of Technology Strategy and Strategic Partnerships at Syneos Health. pharmaceutical company executive Data is one of the most important topics in the pharmaceutical industry. New technologies change the game, bringing both great opportunities and new challenges.
Pharmaceutical Executive: Data is a bit of a broad term in the life sciences industry, and data collected by different sources can often vary widely. How can digital health technology help with this?
Bob Zambon: This is very important because when you look at data formats, research and development, and even the overall picture of what is considered medical data in general, data is often categorized into different groups. For example, we have real-world data, and we can also buy research data, so it's in line with that. All of them must interact in some way from a total value perspective. Bringing real-world data from someone in the healthcare process back into research and design, identifying molecules and pathways, therapeutic functions and other new ways to treat patients is something many companies are trying to connect. This is an important loop. Some people have varying degrees of success. The key is to make the data interactive, or at least analyzeable in a meaningful way. This means understanding what the limitations of real-world data are, the layering of analysis, and the ability to process fields in a standardized way. We'll look at a variety of standard approaches to things like real-world data that are starting to follow that path. This means converting data into a standardized format that everyone can understand. By doing this, you won't have to restandardize, rebaseline, and remaster all your data every time you run a research project.
Instead, have everything in a format that works with each other. Much of the research done so far started with natural language processing many years ago. Even something as simple as technically converting a physical document into a digital format using OCR or NLP to begin the process can still be difficult. There are differences to consider in different types of medical records, such as what some of the open text fields mean.
There may be data that someone has just been diagnosed with cancer, or that this particular lab test returned this particular result. This is all part of following a path of taking all the data and making it more accessible so that additional algorithms, machine learning, and AI can be applied. Everything that people are building on top of that is exactly where we're going. In some cases, you may already be doing it.
PE: How do some issues related to data impact performance-based contracting?
Zambon: As we focus on real-world data and the ability to leverage that data in more practical and direct ways, we are changing the way we think about how we reimburse and pay for therapeutics. Previously, the model was to OK the drug every time a treatment was applied. You'll find out things like his price per pill for a particular drug. We are moving toward performance-based care and contracting, where one of the key issues is deciding how to measure performance.
How can we measure performance in a way that payers, patients, physicians, and hospital systems agree on treatment performance?
PE: How has the growth of the wearables market changed the way data is collected?
Zambon: It's a great field and a rapidly evolving field. Part of it has to do with what the wearable actually contains and the data it collects. How patients interact with healthcare has changed over time. COVID-19 has caused people to become more involved in healthcare decisions. They are getting advice online, from doctors and other caregivers. Patients are starting to wear health and fitness trackers more regularly. As the hardware itself becomes increasingly optimized and sophisticated, additional algorithms are built into it. If you look at something like an Apple Watch, you can use it to get an electrocardiogram. We can now see our actual heart rate, along with temperature, pulse, and all sorts of other fun metrics, where these variables and devices previously only tracked simple things.
These devices are not just tracking basic measurements, but are starting to detect real signals that are useful from a treatment perspective to drive much more impactful decision-making. Knowing your daily, and even minute-by-minute, heart rate will revolutionize the way you think about personalizing healthcare.