5 Q’s Interview with Jonathan Grinstein, CEO of PAC Dynamic – Center for Data Innovation

The Center for Data Innovation spoke with Jonathan Grinstein, CEO of PAC Dynamic, a Chicago-based company that uses AI to personalize heart failure treatment. Grinstein discussed how PAC Dynamic analyzes heart function through data about blood flow and energy use in the body to help doctors make better decisions and optimize treatments for individual patients. 

David Kertai: What does PAC Dynamic do?

Jonathan Grinstein: At PAC Dynamic, our mission is to put patients at the center of heart failure care. Our goal is to bring more objectivity to evaluating and managing heart failure in real time, helping doctors make better-informed decisions.

We start by analyzing a patient’s hemodynamic signals, the pressures and flows inside their heart. From this data, we calculate how efficiently the heart is using energy to pump blood. This is what we call the energetic profile, a set of measurements that show the heart’s workload, oxygen use, and overall efficiency. These insights aren’t typically available in routine clinical practice.

By combining this hemodynamic and energetic information in a machine learning model, we can categorize a patient’s heart function, predict their risk of worsening heart failure, and recommend treatments tailored to their specific needs.

Kertai: How does PAC Dynamic help predict how patients will respond to heart failure treatments?

Grinstein: We build a computer simulation of a patient’s blood circulation using their medical data, such as blood pressure and blood flow measurements. This allows us to recreate how their heart is functioning in real life.

To fully understand a patient’s heart function, we don’t just look at isolated test results, we use those test results to build a detailed model of how their heart is working as a whole. This lets us calculate things that aren’t normally measured in routine care, like how much energy the heart uses to pump blood and how efficiently it maintains circulation.

We also developed an AI algorithm trained on a large database of past patients, including their heart conditions and treatment responses. When a new patient comes in, our AI compares their heart data to similar cases and predicts how they will likely respond to different treatments. This helps doctors make more precise therapy decisions tailored to each patient.

Kertai: How does PAC Dynamic use data and real-time analytics to improve smart medical devices?

Grinstein: Every treatment, whether a medication or a medical device, has a specific range where it works most effectively, meaning it provides the intended benefits without causing unnecessary side effects. In heart failure treatment, this balance is especially important because the cardiovascular system is interconnected; adjusting one part of heart function can unintentionally affect other parts. The ideal settings for a device depend on the patient’s condition and the specific type of support being provided.

Our algorithms focus on helping the heart recover efficiently by balancing these complex interactions. This ensures that medical devices provide the right level of support without overloading the heart or causing complications. In the future, we plan to fully automate this process with a closed-loop system, allowing medical devices to adjust their settings in real time to optimize heart function and support recovery.

Kertai: Can you share a real-world example of how PAC Dynamic’s innovations have made an impact?

Grinstein: As a medical startup, we are still in the process of obtaining FDA clearance for our technology, so our direct clinical impact is currently limited. However, the scientific principles behind our algorithms, such as the use of advanced hemodynamic metrics and cardiac energetics, are already being applied in the medical field. For example, at the University of Chicago, doctors are using these tools to better identify patients who may need heart replacement therapies at an earlier stage, before their condition worsens to severe heart failure or shock. This approach is helping improve risk assessment and treatment timing, which can make a significant difference in patient outcomes.

Kertai: What is your vision for the future of PAC Dynamic and AI in healthcare? 

Grinstein: Our technology is designed to optimize heart function across all stages of heart disease. Our first product, the Virtual Patient Simulator, focuses on the sickest patients, those with advanced heart failure and cardiogenic shock, who have the greatest unmet medical needs.

In the near future, we plan to expand this technology to help all heart failure patients, even in the earlier stages of the disease. By analyzing each patient’s unique heart function, we aim to provide personalized treatment recommendations that can slow down or even reverse heart failure. Our approach guides doctors in selecting the best therapies to improve heart efficiency and energy use. Ultimately, we strive to make treatment patient-specific, ensuring that the right therapy reaches the right patient at the right time.