Pharma's Digital Transformation: Where It's Really At
By John Oncea, Chief Editor, Clinical Tech Leader
Ask pharma executives whether digital transformation is on track, and most will tell you yes. Ask Victoria Gamerman, and you’ll get a more complicated answer, one that’s simultaneously more optimistic and more honest about what’s hard.
“Across the industry, the digital transformation journey is both further along and further behind than anticipated,” says Gamerman, Global Head of Digital Transformation for Clinical Development Operations at Boehringer Ingelheim. The tools are better than anyone expected. The human side of the equation is harder than most organizations planned for.
That gap between technological capability and organizational readiness is the defining tension in clinical trial digitization right now. After years of intense AI investment and discussion, the industry has reached a point where return on investment can no longer be theoretical. The pressure to show value is real, and organizations that built on weak human foundations are starting to feel it.
Why Clinical Data Transformation Stalls At Culture, Not Code
Here is the uncomfortable truth Gamerman keeps returning to: deploying advanced data infrastructure doesn’t transform an organization. People do. And people are slow.
The pattern is familiar. A major pharma organization invests in a sophisticated clinical data platform. The architecture is sound, the vendor is credible, and the demo looked great. Eighteen months later, teams are still operating in silos, still reluctant to share data across functions, still running shadow spreadsheets alongside the new system. The technology didn’t fail. The organizational conditions to use it well never materialized.
Gamerman points to an early signal: when the new tool doesn’t reduce friction for the end user on day one, adoption stalls. Consider a clinical operations team asked to shift from a familiar data entry process to a new integrated system that requires different tagging, different governance steps, and different approval flows. Even if the downstream value is real, the immediate experience is more work, not less. That perception – “this makes my job harder” – is where transformation goes to die.
The flip side of that diagnosis is equally clear. What gives Gamerman genuine optimism is a generational shift she’s watching take hold: a cohort of emerging leaders who understand data as a strategic asset instinctively, who ask questions about context and governance at the design stage rather than retrofitting them after the fact. That shift in instinct, from data as compliance overhead to data as competitive infrastructure, is the leading indicator that something real is changing.
From Project Mindset To Product Mindset: What It Takes
Gamerman draws a sharp distinction between project thinking and product thinking, and it explains a lot about why digital transformation has underdelivered.
Project thinking funds a discrete initiative: define the scope, build the thing, ship it, close the budget line. It’s how IT has historically been governed in large pharma organizations, and it produces exactly what it’s designed to produce: a point-in-time deliverable that may or may not continue to improve after launch. Product thinking is different. It funds a continuous value stream: the tool gets better, the team stays engaged, and adoption is a metric that matters as much as delivery. A clinical data governance program run as a product doesn’t just get deployed; it evolves as trial complexity evolves.
Making that shift operationally requires three concrete changes, in Gamerman’s framing. First, data governance has to move from a compliance exercise to a strategic enabler – embedded in routine workflow, designed to make it easy for teams to do the right thing with data rather than creating friction they’ll route around. In practice, that means governance touchpoints built into the tools clinical teams already use, not maintained in separate documentation systems nobody reads.
Second, the communication gap between technical teams and business leadership has to be actively bridged. Data scientists need to translate their work into the language of revenue, risk, and reputation. Executives need enough data literacy to ask useful questions, not to become analysts, but to stop nodding along when they should be pushing back. Organizations that invest in developing internal translators, people fluent in both vocabularies, accelerate faster than those that try to upskill everyone broadly.
Third, and most practically: if a new tool doesn’t make the end user’s job meaningfully easier, it won’t get adopted regardless of its technical sophistication. That’s not a soft cultural observation; it’s a hard implementation constraint. The clinical research community has watched expensive technology fail at the adoption stage often enough to know that “brilliant but ignored” is a real outcome category.
What Genuine Clinical Trial Digitization Success Looks Like
When Gamerman describes what success looks like, she doesn’t reach for a metric. She reaches for a linguistic one.
The milestone that signals genuine transformation is the day the industry stops talking about “digital trials” and just talks about “trials.” Right now, digital is an adjective; a modifier applied to a traditional process, signaling that something extra has been layered on. The real shift happens when digital and data-driven approaches are the invisible operating foundation of every program, not the headline feature.
In practice, that world looks like this: protocol design is routinely simulated against integrated real-world and genomic data before a single site is selected. Predictive analytics for enrollment and safety monitoring are standard, as unremarkable as a descriptive statistics table in a study report. The underlying data ecosystem at every organization is AI-ready, not AI-adjacent, because the governance, integration work, and cultural shifts happened before the algorithms arrived.
The path to that milestone runs directly through the three shifts Gamerman identifies: governance as enabler, not compliance; communication as a two-way bridge between technical and business; and technology deployed around the human, not at them. Organizations doing that work now – methodically, without waiting for a perfect platform or a perfect moment – are the ones who will find the milestone within reach. Everyone else will still be announcing digital transformation initiatives long after it should have simply become the way trials are run.
Victoria Gamerman, Ph.D., is Global Head of Digital Transformation, Clinical Development Operations, at Boehringer Ingelheim. She is also the principal of RWD Insights, LLC.