“Steroids are cheap and effective in the short term. Convincing payers that steroid-sparing therapies are worth the upfront cost is still a practical challenge.”
Albert Whangbo, PhD, leads the global Evidence Generation practice at ZS Associates, a role he describes as an intersection of scientific rigor and strategic influence. A civil engineer by training, Whangbo’s journey into life sciences consulting might seem unexpected. Still, it’s a trajectory driven by his passion for using data and evidence to influence real-world decisions and improve patient outcomes.
“We support pharma clients across the lifecycle of real-world evidence studies, from planning and feasibility to execution, publication, and strategy - particularly around health economics and outcomes research.”
Turning data into decisions
It’s a mission that found meaningful alignment in ZS’s collaboration with Argenx and Steritas, where Whangbo’s team applied the Steritas GTI-MD to quantify the steroid-toxicity using real-world data burden in a way never previously possible:
“The GTI-MD allowed us to take what many already know about steroid harms, often anecdotally, and translate that into sensitive, quantitative insights using widely available clinical data. Even with a reduced set of domains, we were able to detect meaningful toxicity changes over relatively short timeframes.”
This collaboration didn’t just validate the GTI-MD approach. It provided a powerful proof of concept: that real-world datasets can yield high-fidelity insights into the cumulative damage of steroid use, bolstering the case for steroid-sparing therapies.
“Using the GTI-MD, we could turn what clinicians intuitively know about steroid-toxicity into quantifiable evidence – and we did it with data that were already sitting in EHRs.”
Before the development of the GTI and GTI-MD, direct measurement of steroid-toxicity was out of reach. Clinicians were left to rely on dose as a proxy, despite wide variation in individual responses and the well-known but imprecise link between dose, duration, and harm. Yet challenges remain in bridging the gap between clinical relevance and payer priorities.
“Despite its potential, the GTI isn’t yet routine in clinical practice. There’s still a learning curve. Clinicians aren’t always sure how a particular GTI score should translate into actionable decisions.”
He also highlights the broader challenge of payer engagement.
“Even when we can quantify toxicity, and even when the cost implications are compelling, there's skepticism, especially when comparing high-cost novel treatments to low-cost, high-efficacy steroids.”
Part of the issue, Whangbo explains, lies in time horizons. While steroid harms accrue over years, payers often evaluate cost-effectiveness over much shorter terms, and attribution remains complicated in poly-treated, comorbid populations.
“Steroids are cheap and effective in the short term. Convincing payers that steroid-sparing therapies are worth the upfront cost is still a practical challenge.
The GTI-MD is a bridge that gets us part of the way. Decision-makers still want the link to hard outcomes: future costs, hospitalizations, quality-of-life.”
Challenging inertia and informing action
Despite these hurdles, Whangbo remains optimistic and motivated.
“There’s an enormous opportunity to keep building the bridge from toxicity metrics to patient outcomes and economic consequences. The data exists. The analytical tools are here. What’s needed now is collective will and storytelling.”
For Whangbo, that’s the real ambition: to help weave the disparate strands of steroid-toxicity evidence into a cohesive, persuasive narrative that can resonate across clinical, academic, and payer audiences.
“It’s time to complete the story. One that’s not told by any single company or study, but by a broader coalition of stakeholders all committed to reducing harm and enabling better options for patients.
The tools are there – it’s doable. We just need to build the consensus to get it done.”
Albert Whangbo, PhD is a Principal at ZS Associates and leads ZS’s Evidence Generation practice area, which is a global team with expertise spanning real-world data strategy, prospective and retrospective studies, economic modeling, advanced analytics, and scientific communications.
Albert focuses on helping life sciences companies make sound decisions and demonstrate value through thoughtful research and analysis. He brings over 20 years of consulting experience across a wide range of issues, including business development strategy, HEOR and value proposition development, forecasting, sales and marketing resource optimization, and analytics capability building. Prior to ZS, Albert conducted mathematical modeling and process optimization research at the General Motors Technical Center.
Albert holds a PhD in Management Science from Stanford University. He also has an MS in Operations Research from Stanford and a BS in Civil Engineering from NC State University.
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