Dr. Jeremy Rassen is an epidemiologist and computer scientist with over 25 years of experience in causal inference, artificial intelligence (AI), and real-world evidence (RWE). As co-founder of Aetion, he has worked with global biopharma, regulators, and payers to apply RWE in drug development, regulatory approvals, and patient care—ensuring decisions are grounded in rigorous science.
During the COVID-19 pandemic, he led Aetion’s collaborations with the U.S. Food and Drug Administration (FDA), shaping how RWE informed public health decisions. Previously, as an assistant professor at Harvard Medical School, he developed advanced analytic methods to improve the validity of real-world data (RWD) studies, pioneering techniques to reduce bias and strengthen causal inference in observational research.
Dr. Rassen began his career in Silicon Valley as the first employee at Epiphany Inc., building data-driven technology for Fortune 50 companies. He holds degrees in Computer Science and Epidemiology from Harvard University and is a fellow and board member of the International Society for Pharmacoepidemiology.
Dr. Jeremy Rassen, co-founder and CEO of Aetion, leads a company at the forefront of an area known as real-world evidence (RWE) generation, which helps regulators, life sciences organizations, and healthcare payers make high-stakes healthcare decisions with speed and confidence, and often without the need for a randomized clinical trial. In this conversation with NY CityBiz, Dr. Rassen discusses the increasing role of real-world data (RWD) in drug development, how Aetion couples AI and scientific rigor to advance evidence generation, and what the future holds for data-driven decision-making in healthcare.
Aetion’s Role in Transforming Healthcare Decision-Making |Real-world evidence is playing a growing role in healthcare. How does Aetion fit into this shift?
Healthcare decisions are becoming more complex, and the stakes are too high to rely on guesswork. Drug and device regulators, healthcare payers, and healthcare providers need to know—not just assume—how treatments perform in real-world settings. Clinical trials set a baseline by telling you about how a drug might work in a controlled environment, but they don’t address how that drug might work differently when used in patients’ real world. It’s good science to control the environment when first testing a drug, but it’s good practice to go beyond trials’ generally small selection of patient populations, which often don’t reflect the full range of individuals who will ultimately receive a treatment. That’s where our focus on real-world evidence comes in.
At Aetion, our vision is a world where we know which treatments work, for whom, and what we should pay for them — and we do that through understanding data from the real world and creating evidence that medical decision-makers can rely on. Achieving that requires a scientifically rigorous approach that can be applied in weeks, not months or years. Our Aetion Evidence Platform is designed to transform de-identified real-world healthcare data into credible evidence that meets the highest scientific and regulatory standards.
Real-world evidence is shaping critical decisions across the healthcare ecosystem. Biopharma companies use it to accelerate drug development, support regulatory submissions, and demonstrate the value of new therapies. Healthcare payers rely on it to assess treatment effectiveness, guide reimbursement decisions, and refine value-based care models. Regulatory agencies use real-world evidence for safety surveillance, policy development, and public health initiatives.
From Randomized Controlled Trials to Real-World Evidence | You co-founded Aetion in 2013. What problem were you solving?
When we started Aetion, healthcare was at a crossroads. Randomized controlled trials—the gold standard for testing new treatments—were too slow, too expensive, and often too narrow in scope. Simply put, they took too long, cost too much, and included only select patients. And that’s often still the case. But at the same time, an enormous amount of real-world healthcare data was starting to be generated but no one had developed a scientifically rigorous way to turn that raw data into evidence that decision-makers could trust.
Trials are certainly essential, but they often exclude key patient populations—older adults, people with multiple conditions, or those taking multiple medications. That makes it difficult to predict how a treatment will perform once it reaches a broader population. Real-world evidence helps close that gap by providing insights into how treatments work across different settings and patient groups.
We founded Aetion to bring scientific discipline to real-world evidence, making it reliable, scalable, and fit for high-stakes decisions. Our goal was simple: to provide decision-makers with the confidence to use real-world evidence alongside clinical trial data to inform the full spectrum of healthcare decisions.
High-quality, real-world evidence isn’t a nice-to-have—it’s essential. Regulators, payers, and providers need clear, credible insights on how drugs compare to one another with respect to safety, effectiveness, and cost. Aetion was built for this, ensuring healthcare decisions rest on the strongest possible evidence. That requires rigorous methods, transparency, and scientific reproducibility—without them, it’s information but not evidence.
Aetion’s Technology and Scientific Leadership | Aetion is recognized for its scientific rigor. What sets your platform apart from traditional analytics?
Science is our foundation. Aetion was built by epidemiologists, scientists who are grounded in discerning the difference between correlation and causation. This means we ensure that every analysis is grounded in rigorous methodology and can inform care. (Prior to the COVID pandemic, most people thought that epidemiologists studied the skin; now, more people know what we do!)
Good science leads to good decisions—but the opposite holds as well. Our Aetion Evidence Platform ensures transparency, reproducibility, and regulatory trust. Our studies meet FDA and EMA standards, supporting approvals, reimbursement, and clinical decisions.
Take statins. In real-world data, patients on statins appear to have higher rates of heart disease, not lower. Does that mean statins don’t work, or worse, that they cause heart disease? Of course not—it means doctors prescribe statins to patients who need them, patients at higher cardiovascular risk. Our software addresses the fundamental differences between patient groups (patients on statins versus patients who are not, in this case) and, through well-accepted methods, identifies and adjusts for these “confounding factors,” revealing the true impact of treatment so decision-makers get answers they can trust. And if you do it right, you see clearly that statins work, quite well in fact.
Real-world evidence is essential to healthcare decision-making, but rigor alone isn’t enough—for it to be accepted evidence, it must also be transparent (how was the evidence generated?) and reproducible (if I run the same study, will I get the same answer?). Treatments must be evaluated, priced, and monitored with the strongest possible science. Decision-makers need more than conclusions—they need to see the full process. Aetion Evidence Platform provides clear, auditable pathways from data selection to results, delivering science that holds up where it matters most.
Privacy and Trust in Real-World Evidence | One of the biggest concerns with real-world data is privacy. How does Aetion protect patient information?
This is a critical issue, and it should be. Patients deserve to know their data is protected. At Aetion, the vast majority of our work is de-identified, meaning that it meets accepted standards to make sure no data item can be traced back to an individual.
Beyond that, we follow strict security protocols and regulatory guidelines to ensure that data is handled responsibly. The healthcare system depends on trust, and we take that responsibility seriously. Our role is to extract meaningful evidence while maintaining the highest standards of privacy and security.
Ensuring privacy is built into our technology. Our Aetion® Generate product ensures that data is and remains de-identified while preserving the statistical integrity needed for rigorous analysis. The ability to derive insights from real-world data without exposing sensitive information is essential for the future of evidence generation, and we continue to engineer our solutions to meet the highest standards of security and regulatory compliance.
AI’s Role in Real-World Evidence Generation | AI is transforming many areas of healthcare. How is Aetion incorporating AI into real-world evidence generation?
AI has enormous potential in healthcare, but its value depends on how it’s applied. It must strengthen how we generate and interpret evidence—not just automate processes. AI alone doesn’t create credible, regulatory-grade evidence; it must be embedded in a structured, scientifically validated framework with the right level of human oversight.
We incorporate AI into RWE generation in three critical ways:
First, AI helps ensure real-world evidence reflects reality. As with the statin example correlation almost never implies causation. Remember that patients taking a medication are usually at higher risk for complications, so simple correlations make it seem like the drug isn’t working when, in fact, it may well be doing its job quite well. Aetion’s AI-driven methods help researchers find and correct these biases, so that regulators, payers, and clinicians can make informed decisions.
Second, AI enhances how we can use existing evidence to predict future outcomes. By analyzing vast datasets, AI helps identify particularly high-risk patients who may benefit from intense early intervention, determine which treatments are most effective for different groups, and anticipate long-term health outcomes. These insights support drug developers in optimizing clinical trials, help regulators evaluate therapies beyond the ends of clinical trials, and enable insurers to assess the real-world value of treatments.
Third, AI protects privacy while preserving the power of real-world data. Aetion’s AI-powered de-identification techniques ensure that patient data remains secure while retaining the scientific integrity needed for high-quality research. This enables stakeholders to generate evidence at scale without compromising patient confidentiality.
When applied responsibly, AI enhances the quality, speed, and impact of scientific inquiry. The challenge isn’t developing AI tools; it’s ensuring they are used within a framework that upholds trust, transparency, and scientific rigor. That’s the approach we take at Aetion.
The Future of RWE and Healthcare Decision-Making | Looking ahead, what are the biggest opportunities for real-world evidence?
The demand for high-quality, regulator-trusted evidence isn’t slowing down—quite the opposite, in fact. Three major trends are shaping our next steps.
First, regulators are integrating real-world evidence into drug approvals and ongoing safety monitoring. That raises the bar for study quality, transparency, and reliability. The industry can no longer rely on fragmented or inconsistent data—decision-makers need evidence that is well-documented, scientifically sound, and tailored to the questions at hand. Organizations that generate transparent, reliable, and regulatory-grade evidence will be better equipped to achieve faster approvals, maintain compliance, and adapt to evolving requirements.
Second, insurers and government health agencies—those making the calls on which treatments get covered—are demanding stronger proof of value. It’s no longer enough to show a drug works; companies must demonstrate how well it works in real-world patient populations and whether it justifies the cost compared to other alternatives. Real-world evidence is becoming central to pricing and reimbursement decisions, meaning the ability to generate credible, defensible evidence is critical.
Third, real-world evidence is reshaping medical innovation. It’s accelerating rare disease research, helping regulators set pathways for cell and gene therapies, and expanding our understanding of how treatments perform in patient populations that traditional trials often overlook. As precision medicine evolves, real-world evidence will be key to ensuring that the right treatments reach the right patients—leading to more personalized care, better outcomes, and a more efficient healthcare system.
At Aetion, we’re focused on making real-world evidence a trusted, transparent, and reproducible foundation for decision-making. When used effectively, it leads to better, faster, and more confident choices—whether in the lab, at the regulatory table, or in clinical practice.
