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Benchmarks top biopharma companies across R&D productivity, development risk, market access and commercial performance.
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Our new podcast series, “Real-World Data After Dark,” blends deep insights with light late-night talk show banter.
The article argues that relying on a single data source can't reliably identify patients who need attention, so connecting claims, lab, and EHR data at scale with AI, while experts decide what level of evidence justifies action, is the next evolution of real-world evidence.
See how NorstellaLinQ helped a biopharma company identify rare pediatric cancer patients beyond the limits of claims data.
Explores how connected RWD and AI help commercial teams identify patients, target HCPs and act on emerging market signals.
Explores how depression and anxiety in type 1 diabetes are linked to poorer glycemic control and greater complication risk.
Explore how Norstella Atlas uses agentic AI and connected life sciences data to deliver faster, decision-ready insights across biopharma.
Explores how real-world data reveals antidepressant use and withdrawal patterns to support safer, informed patient care.
Explores why pharma AI falls short and how decision-ready data and trusted context can turn AI into real productivity gains.
Explores how AI and richer real-world data will transform predictive analytics, pharma strategy and patient care.
Explores how connected RWD and AI help commercial teams identify patients, target HCPs and act on emerging market signals.
Explores how unstructured EHR data and AI reveal deeper patient insights to improve targeting, treatment and access strategies.
Explores how AI and real-world data help pharma find patients earlier, predict treatment changes and improve targeting.
Explores how trusted AI and real-world data can accelerate evidence generation, patient identification and pharma decision-making.
Real-world data: Closing the strategy gap