Seeing What's Hidden: Cross-Domain Estimation of the Global T2 Inflammation Patient Population

The global Type 2 inflammation patient population is among the most consequential and poorly characterized in life sciences — not for lack of evidence, but for lack of structural framing. Existing estimates fail because the boundary problem has never been formally resolved: without a tiered definitional framework distinguishing confirmed, probable, and undiagnosed populations, any estimate is measuring something different than it claims to measure.

CCG diagnosed the structural source of estimation failure, developed a tiered definitional framework to resolve the boundary problem, and applied five methodological approaches drawn from ecology, epidemiology, and actuarial science to produce credible regional estimates where direct data is sparse. This project was selected by Wazoku/InnoCentive from a global solver pool for a challenge seeking credible estimation of the worldwide Type 2 inflammation patient population.

Relevant consulting applications:

• Patient population sizing and market estimation for pharmaceutical and biotech companies

• Diagnostic framework development where disease boundaries are contested or poorly defined

• Cross-domain methodological synthesis for research teams where within-domain approaches have reached a ceiling

• Regulatory and commercial strategy informed by structurally defensible epidemiological estimates