In the rapidly evolving landscape of digital health technologies (DHTs), one challenge looms larger than most: proving that innovative solutions actually work. While pharmaceutical companies have long followed rigorous evidence generation roadmaps, digital health companies have often navigated without such structured guidance—until now.

At the intersection of artificial intelligence and cancer diagnostics, Lunit stands as an example of how embracing structured evidence planning can transform a company’s strategic approach. Through their implementation of Integrated Evidence Plans (IEPs), they’re demonstrating that pharmaceutical-grade evidence strategies can be powerfully adapted for the digital health world.

Lunit’s evidence approach
“Lunit is just very, very dedicated to evidence,” explains Terri Kim, Head of Strategy and Corporate Development at Lunit. This commitment isn’t merely aspirational—it’s woven into the company’s DNA with hundreds of peer-reviewed journal publications across their radiology and pathology-focused business lines.

Founded in 2013, Lunit has established itself as a pioneer in AI-powered cancer diagnostics, advancing both imaging analysis and precision oncology solutions. Their technology examines radiology and pathology images to identify patterns associated with cancer, providing clinical decision support that aims to improve detection rates and treatment outcomes.

Yet despite this foundational commitment to scientific validation, Kim recognized that Lunit’s approach to evidence generation needed to evolve. “Previously, resources were limited, and we primarily focused on proving the technology worked,” she reflects. “But now that we’re actively in the market—where rubber meets the road—we’re realizing we need evidence that speaks directly to customer and payor requirements too.” 

This realization mirrors a broader challenge facing digital health companies. Many startups pour resources into technological development and initial validation studies, but struggle to produce the comprehensive evidence needed for successful commercialization, reimbursement, and clinical adoption. Without structured evidence planning, promising technologies can fail to reach their full potential—or fail entirely.

Learning from pharma: The value of IEPs
The pharmaceutical industry’s methodical approach to evidence generation—mapping out clinical, economic, and real-world evidence needs across a product’s lifecycle—has proven extraordinarily effective at navigating complex approval and commercialization landscapes. DiMe’s Integrated Evidence Plan framework adapts these principles for digital technologies, providing structure without sacrificing the agility that makes digital health innovation possible.

For Lunit, the appeal was clear. “We wanted to see what we can learn from that process,” Kim explains, referring to pharmaceutical evidence development. “That’s kind of what we expected going into IEP.”

What distinguishes DiMe’s approach is its recognition that evidence needs for digital health technologies differ from those of pharmaceuticals. While drug developers might focus heavily on randomized controlled trials, digital health developers often require diverse evidence types—technical validation, clinical utility studies, implementation research, and economic analyses—all operating on compressed timelines.

From resources to real-world impact
When DiMe released its IEP resources, Kim immediately saw their potential to transform internal conversations. During strategic discussions about pipeline products, she found herself advocating for comprehensive evidence planning, then reinforcing her position with DiMe’s frameworks: “This isn’t just our opinion—there’s formal thinking behind this, and we’ve actually contributed to shaping it.”

This moment illustrates one of the most powerful yet underappreciated aspects of structured evidence frameworks: they don’t just guide external validation, they reshape internal priorities. “It legitimizes my voice,” Kim notes, explaining how having recognized industry frameworks helped gain buy-in from stakeholders who might otherwise have prioritized quicker regulatory approvals or immediate commercialization over long-term evidence generation.

The impact has been particularly meaningful for senior leaders less familiar with U.S. market requirements. Kim shares how one medical leader now running a business unit embraced the resources: “He’ll just consume this information and make it his. While I’m not in every single conversation he’s in, I’m sure in other conversations he’s in, he’s probably thinking about, ‘Have you thought of this? Are we thinking about that?'”

This ripple effect—where evidence planning principles gradually infuse broader organizational thinking—represents exactly the kind of cultural shift that can differentiate successful digital health companies from those that struggle to achieve sustainable growth.

Looking Ahead: The next phase of evidence planning
Lunit’s story resonates because it reflects broader market dynamics. Kim points to competitors in the health tech imaging space who secured substantial investor funding but struggled to demonstrate product-market fit once in the market. “A lot of us have just not been able to really show the product-market fit,” she observes, attributing this partly to insufficient early investment in understanding “the nuanced challenges that could exist with the service and the product.”

By embracing structured evidence planning, Lunit aims to avoid these pitfalls. For existing products, the IEP framework has helped them retrospectively evaluate market access opportunities they hadn’t initially explored. For pipeline products, it’s enabling more strategic planning from the outset, potentially avoiding costly pivots later.

Kim emphasizes that DiMe’s IEP resources represent “just the beginning of things, and there’s so much more to unpack.” She recommends companies leverage DiMe’s broader collection of resources, particularly those addressing regulatory considerations, to build comprehensive evidence strategies.

As digital health technologies grow increasingly sophisticated, the bar for evidence will only rise. Payers, providers, and patients are no longer satisfied with promises of theoretical benefits—they demand robust proof of clinical, economic, and experiential value. Companies that embrace structured evidence planning now position themselves for long-term success in this evolving landscape.

Lunit’s journey with DiMe’s IEP framework illustrates that pharmaceutical-grade evidence planning isn’t just applicable to digital health—it’s essential. By bridging the evidence gap between validation and value, companies like Lunit aren’t just advancing their own commercial prospects; they’re helping the entire field mature into one where digital innovations reliably deliver on their promises to transform care.

And in a healthcare ecosystem hungry for solutions that truly work, that might be the most valuable evidence of all.