Gosia Leitch, VP of Engagement Solutions at Diaceutics, shares key highlights and takeaways from Fierce Pharma Week 2025 in Philadelphia.
Key Takeaway 1: AI’s Present Reality
What role do you see AI playing in pharma marketing?
“AI is no longer a future promise in pharma marketing—it’s the present reality. One thing is clear the industry is undergoing a seismic shift in how we engage HCPs and AI is at the heart of it.”
Key Takeaway 2: Dynamic Segmentation
What’s changing in how we segment and engage HCPs?
“From static NPI lists to dynamic, behavior-based segmentation, we're finally treating HCPs as individuals—not just prescribers. AI is enabling us to:
Predict engagement and prescribing behavior with real-time data
Personalize content and channel mix based on generational and contextual preferences
Automate campaign orchestration while staying compliant”
Key Takeaway 3: Personalization & Automation
How is AI helping us personalize and automate our campaigns?
“It’s all about tailoring the experience. AI allows us to personalize content and channel mix based on generational and contextual preferences and automate campaign orchestration while staying compliant.”
Discussion Point: Diagnostics Data
You raised an important point about diagnostics data. Why isn’t it being used more widely in real-time HCP targeting?
“What strikes me is that no one is discussing the role of prospective diagnostics data like lab and genomic signals in HCP targeting.
There’s a simple truth: sophisticated algorithms allowing very precise behavioral segmentation are not going to help if you're targeting content that is not timely and therefore not relevant. It makes a huge difference if you provide timely engagement with information on the treatment that the patient in front of them qualifies for.
Here’s why prospective diagnostics data matters:
Unlike claims data, which reflects past events, lab and genomic data offer real-time clinical relevance. This enables:
HCP engagement before treatment decisions are made—often within <2 days, compared to a week or more with claims data
Higher HCP response rates 30–45% vs. 10–15%
Greater Rx lift to 20% compared to 10% with traditional approaches
These are not just incremental gains, they’re transformative. Here at Diaceutics we can see the difference this makes for commercial teams aiming to make a difference to patient treatment options”
Our current situation
What do you think is holding teams back from using diagnostics data in real-time targeting?
“Great question. Here are the main barriers:
Data Access & Integration Challenges – Lab and genomic data often reside in fragmented systems. Integrating these feeds into commercial platforms requires partnerships, infrastructure, and compliance safeguards.
Legacy Mindsets – Pharma has long relied on claims and EMR data. These sources are familiar, standardized, and embedded in existing workflows.
Regulatory & Privacy Concerns – Real-time diagnostics data is sensitive. Navigating HIPAA, GDPR, and internal compliance reviews can slow adoption, especially when teams lack clear frameworks.
Misaligned KPIs – Many commercial teams still measure success using volume-based metrics (e.g., reach, impressions) rather than clinical relevance or time-to-action.
Underdeveloped Commercial Use Cases – While oncology and rare disease brands are leading the way, broader therapeutic areas haven’t yet built robust playbooks for using diagnostics data in engagement strategies.”
It’s clear that AI and diagnostics data have the potential to transform pharma engagement, but we need to overcome key barriers to unlock that value.
Let’s start the conversation about what’s holding your team back from using diagnostics data in real-time targeting for patients and HCPs? We’d enjoy the opportunity of sharing our use cases and exploring what a difference this would make. .
